Patent Publication Number: US-11656941-B2

Title: Retrieval of data objects with a common trait in a storage network

Description:
CROSS REFERENCE TO RELATED PATENTS 
     The present U.S. Utility Patent Application claims priority pursuant to 35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No. 17/195,150, entitled “Combining Data Objects in a Vast Data Storage Network”, filed Mar. 8, 2021, which is a continuation of U.S. Utility application Ser. No. 17/081,056, entitled “Concatenating Data Objects in a Vast Data Storage Network”, filed Oct. 27, 2020, issued as U.S. Pat. No. 10,977,127 on Apr. 13, 2021, which is a continuation of U.S. Utility application Ser. No. 16/988,247, entitled “Concatenating Data Objects For Storage In A Vast Data Storage Network”, filed Aug. 7, 2020, issued as U.S. Pat. No. 10,853,172 on Dec. 1, 2020, which is a continuation of U.S. Utility application Ser. No. 16/171,794, entitled “Concatenating Data Objects for Storage in a Dispersed Storage Network”, filed Oct. 26, 2018, issued as U.S. Pat. No. 10,776,204 on Sep. 15, 2020, which is a continuation of U.S. Utility application Ser. No. 15/679,569, entitled “Concatenating Data Objects for Storage in a Dispersed Storage Network”, filed Aug. 17, 2017, issued as U.S. Pat. No. 10,169,150 on Jan. 1, 2019, which is a continuation of U.S. Utility application Ser. No. 15/351,628, entitled “Concatenating Data Objects for Storage in a Dispersed Storage Network”, filed Nov. 15, 2016, issued as U.S. Pat. No. 9,798,619 on Oct. 24, 2017, which is a continuation of U.S. Utility application Ser. No. 14/589,391, entitled “Concatenating Data Objects for Storage in a Dispersed Storage Network”, filed Jan. 5, 2015, issued as U.S. Pat. No. 9,529,834 on Dec. 27, 2016, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No. 61/944,742, entitled “Executing Tasks in a Distributed Storage and Task Network”, filed Feb. 26, 2014, all of which are hereby incorporated herein by reference in their entirety and made part of the present U.S. Utility Patent Application for all purposes. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     Not applicable. 
     INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC 
     Not applicable. 
     BACKGROUND OF THE INVENTION 
     Technical Field of the Invention 
     This invention relates generally to computer networks and more particularly to dispersed storage of data and distributed task processing of data. 
     Description of Related Art 
     Computing devices are known to communicate data, process data, and/or store data. Such computing devices range from wireless smart phones, laptops, tablets, personal computers (PC), work stations, and video game devices, to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing device includes a central processing unit (CPU), a memory system, user input/output interfaces, peripheral device interfaces, and an interconnecting bus structure. 
     As is further known, a computer may effectively extend its CPU by using “cloud computing” to perform one or more computing functions (e.g., a service, an application, an algorithm, an arithmetic logic function, etc.) on behalf of the computer. Further, for large services, applications, and/or functions, cloud computing may be performed by multiple cloud computing resources in a distributed manner to improve the response time for completion of the service, application, and/or function. For example, Hadoop is an open source software framework that supports distributed applications enabling application execution by thousands of computers. 
     In addition to cloud computing, a computer may use “cloud storage” as part of its memory system. As is known, cloud storage enables a user, via its computer, to store files, applications, etc., on an Internet storage system. The Internet storage system may include a RAID (redundant array of independent disks) system and/or a dispersed storage system that uses an error correction scheme to encode data for storage. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S) 
         FIG.  1    is a schematic block diagram of an embodiment of a distributed computing system in accordance with the present invention; 
         FIG.  2    is a schematic block diagram of an embodiment of a computing core in accordance with the present invention; 
         FIG.  3    is a diagram of an example of a distributed storage and task processing in accordance with the present invention; 
         FIG.  4    is a schematic block diagram of an embodiment of an outbound distributed storage and/or task (DST) processing in accordance with the present invention; 
         FIG.  5    is a logic diagram of an example of a method for outbound DST processing in accordance with the present invention; 
         FIG.  6    is a schematic block diagram of an embodiment of a dispersed error encoding in accordance with the present invention; 
         FIG.  7    is a diagram of an example of a segment processing of the dispersed error encoding in accordance with the present invention; 
         FIG.  8    is a diagram of an example of error encoding and slicing processing of the dispersed error encoding in accordance with the present invention; 
         FIG.  9    is a diagram of an example of grouping selection processing of the outbound DST processing in accordance with the present invention; 
         FIG.  10    is a diagram of an example of converting data into slice groups in accordance with the present invention; 
         FIG.  11    is a schematic block diagram of an embodiment of a DST execution unit in accordance with the present invention; 
         FIG.  12    is a schematic block diagram of an example of operation of a DST execution unit in accordance with the present invention; 
         FIG.  13    is a schematic block diagram of an embodiment of an inbound distributed storage and/or task (DST) processing in accordance with the present invention; 
         FIG.  14    is a logic diagram of an example of a method for inbound DST processing in accordance with the present invention; 
         FIG.  15    is a diagram of an example of de-grouping selection processing of the inbound DST processing in accordance with the present invention; 
         FIG.  16    is a schematic block diagram of an embodiment of a dispersed error decoding in accordance with the present invention; 
         FIG.  17    is a diagram of an example of de-slicing and error decoding processing of the dispersed error decoding in accordance with the present invention; 
         FIG.  18    is a diagram of an example of a de-segment processing of the dispersed error decoding in accordance with the present invention; 
         FIG.  19    is a diagram of an example of converting slice groups into data in accordance with the present invention; 
         FIG.  20    is a diagram of an example of a distributed storage within the distributed computing system in accordance with the present invention; 
         FIG.  21    is a schematic block diagram of an example of operation of outbound distributed storage and/or task (DST) processing for storing data in accordance with the present invention; 
         FIG.  22    is a schematic block diagram of an example of a dispersed error encoding for the example of  FIG.  21    in accordance with the present invention; 
         FIG.  23    is a diagram of an example of converting data into pillar slice groups for storage in accordance with the present invention; 
         FIG.  24    is a schematic block diagram of an example of a storage operation of a DST execution unit in accordance with the present invention; 
         FIG.  25    is a schematic block diagram of an example of operation of inbound distributed storage and/or task (DST) processing for retrieving dispersed error encoded data in accordance with the present invention; 
         FIG.  26    is a schematic block diagram of an example of a dispersed error decoding for the example of  FIG.  25    in accordance with the present invention; 
         FIG.  27    is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module storing a plurality of data and a plurality of task codes in accordance with the present invention; 
         FIG.  28    is a schematic block diagram of an example of the distributed computing system performing tasks on stored data in accordance with the present invention; 
         FIG.  29    is a schematic block diagram of an embodiment of a task distribution module facilitating the example of  FIG.  28    in accordance with the present invention; 
         FIG.  30    is a diagram of a specific example of the distributed computing system performing tasks on stored data in accordance with the present invention; 
         FIG.  31    is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module storing data and task codes for the example of  FIG.  30    in accordance with the present invention; 
         FIG.  32    is a diagram of an example of DST allocation information for the example of  FIG.  30    in accordance with the present invention; 
         FIGS.  33 - 38    are schematic block diagrams of the DSTN module performing the example of  FIG.  30    in accordance with the present invention; 
         FIG.  39    is a diagram of an example of combining result information into final results for the example of  FIG.  30    in accordance with the present invention; 
         FIGS.  40 A-B  are schematic block diagrams of an embodiment of a dispersed storage network (DSN) illustrating an example of executing tasks in accordance with the present invention; 
         FIG.  40 C  is a flowchart illustrating an example of executing tasks in accordance with the present invention; 
         FIGS.  41 A , G, and H are schematic block diagrams of another embodiment of a dispersed storage network (DSN) in accordance with the present invention; 
         FIG.  41 B  is a diagram illustrating an example of encoding a concatenated object into a plurality of data blocks in accordance with the present invention; 
         FIG.  41 C  is a diagram illustrating an example of matrix multiplication of an encoding matrix and a data matrix using a dispersed storage error coding function to produce a coded matrix in accordance with the present invention; 
         FIG.  41 D  is a diagram illustrating another example of matrix multiplication of an encoding matrix and a data matrix using a dispersed storage error coding function to produce a coded matrix in accordance with the present invention; 
         FIG.  41 E  is a diagram illustrating another example of matrix multiplication of an encoding matrix and a data matrix using a dispersed storage error coding function to produce a coded matrix in accordance with the present invention; 
         FIG.  41 F  is a diagram illustrating an example of mapping data objects to a concatenated object in accordance with the present invention; 
         FIG.  41 I  is a flowchart illustrating an example of concatenating data objects for storage in accordance with the present invention; 
         FIGS.  42 A-B  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating an example of storing data in accordance with the present invention; 
         FIG.  42 C  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) illustrating an example of retrieving data in accordance with the present invention; 
         FIG.  42 D  is a flowchart illustrating another example of accessing data in accordance with the present invention; 
         FIG.  43 A  is a schematic block diagram of an embodiment of a storage service access system in accordance with the present invention; 
         FIG.  43 B  is a flowchart illustrating an example of authentication access to a storage service in accordance with the present invention; 
         FIGS.  44 A-B  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating another example of storing data in accordance with the present invention; 
         FIG.  44 C  is a flowchart illustrating another example of storing data in accordance with the present invention; 
         FIGS.  45 A-B  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating an example of rebuilding stored data in accordance with the present invention; 
         FIG.  45 C  is a flowchart illustrating an example of rebuilding stored data in accordance with the present invention; 
         FIGS.  46 A-B  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating another example of storing data in accordance with the present invention; 
         FIG.  46 C  is a flowchart illustrating another example of storing data in accordance with the present invention; 
         FIG.  47 A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) in accordance with the present invention; 
         FIG.  47 B  is a flowchart illustrating an example of resolving write conflicts in accordance with the present invention; 
         FIG.  48 A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) in accordance with the present invention; and 
         FIG.  48 B  is a flowchart illustrating an example of storing a plurality of correlated data in accordance with the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       FIG.  1    is a schematic block diagram of an embodiment of a distributed computing system  10  that includes a user device  12  and/or a user device  14 , a distributed storage and/or task (DST) processing unit  16 , a distributed storage and/or task network (DSTN) managing unit  18 , a DST integrity processing unit  20 , and a distributed storage and/or task network (DSTN) module  22 . The components of the distributed computing system  10  are coupled via a network  24 , which may include one or more wireless and/or wire lined communication systems; one or more private intranet systems and/or public intern&amp; systems; and/or one or more local area networks (LAN) and/or wide area networks (WAN). 
     The DSTN module  22  includes a plurality of distributed storage and/or task (DST) execution units  36  that may be located at geographically different sites (e.g., one in Chicago, one in Milwaukee, etc.). Each of the DST execution units is operable to store dispersed error encoded data and/or to execute, in a distributed manner, one or more tasks on data. The tasks may be a simple function (e.g., a mathematical function, a logic function, an identify function, a find function, a search engine function, a replace function, etc.), a complex function (e.g., compression, human and/or computer language translation, text-to-voice conversion, voice-to-text conversion, etc.), multiple simple and/or complex functions, one or more algorithms, one or more applications, etc. 
     Each of the user devices  12 - 14 , the DST processing unit  16 , the DSTN managing unit  18 , and the DST integrity processing unit  20  include a computing core  26  and may be a portable computing device and/or a fixed computing device. A portable computing device may be a social networking device, a gaming device, a cell phone, a smart phone, a personal digital assistant, a digital music player, a digital video player, a laptop computer, a handheld computer, a tablet, a video game controller, and/or any other portable device that includes a computing core. A fixed computing device may be a personal computer (PC), a computer server, a cable set-top box, a satellite receiver, a television set, a printer, a fax machine, home entertainment equipment, a video game console, and/or any type of home or office computing equipment. User device  12  and DST processing unit  16  are configured to include a DST client module  34 . 
     With respect to interfaces, each interface  30 ,  32 , and  33  includes software and/or hardware to support one or more communication links via the network  24  indirectly and/or directly. For example, interface  30  supports a communication link (e.g., wired, wireless, direct, via a LAN, via the network  24 , etc.) between user device  14  and the DST processing unit  16 . As another example, interface  32  supports communication links (e.g., a wired connection, a wireless connection, a LAN connection, and/or any other type of connection to/from the network  24 ) between user device  12  and the DSTN module  22  and between the DST processing unit  16  and the DSTN module  22 . As yet another example, interface  33  supports a communication link for each of the DSTN managing unit  18  and DST integrity processing unit  20  to the network  24 . 
     The distributed computing system  10  is operable to support dispersed storage (DS) error encoded data storage and retrieval, to support distributed task processing on received data, and/or to support distributed task processing on stored data. In general and with respect to DS error encoded data storage and retrieval, the distributed computing system  10  supports three primary operations: storage management, data storage and retrieval (an example of which will be discussed with reference to  FIGS.  20 - 26   ), and data storage integrity verification. In accordance with these three primary functions, data can be encoded, distributedly stored in physically different locations, and subsequently retrieved in a reliable and secure manner. Such a system is tolerant of a significant number of failures (e.g., up to a failure level, which may be greater than or equal to a pillar width minus a decode threshold minus one) that may result from individual storage device failures and/or network equipment failures without loss of data and without the need for a redundant or backup copy. Further, the system allows the data to be stored for an indefinite period of time without data loss and does so in a secure manner (e.g., the system is very resistant to attempts at hacking the data). 
     The second primary function (i.e., distributed data storage and retrieval) begins and ends with a user device  12 - 14 . For instance, if a second type of user device  14  has data  40  to store in the DSTN module  22 , it sends the data  40  to the DST processing unit  16  via its interface  30 . The interface  30  functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). In addition, the interface  30  may attach a user identification code (ID) to the data  40 . 
     To support storage management, the DSTN managing unit  18  performs DS management services. One such DS management service includes the DSTN managing unit  18  establishing distributed data storage parameters (e.g., vault creation, distributed storage parameters, security parameters, billing information, user profile information, etc.) for a user device  12 - 14  individually or as part of a group of user devices. For example, the DSTN managing unit  18  coordinates creation of a vault (e.g., a virtual memory block) within memory of the DSTN module  22  for a user device, a group of devices, or for public access and establishes per vault dispersed storage (DS) error encoding parameters for a vault. The DSTN managing unit  18  may facilitate storage of DS error encoding parameters for each vault of a plurality of vaults by updating registry information for the distributed computing system  10 . The facilitating includes storing updated registry information in one or more of the DSTN module  22 , the user device  12 , the DST processing unit  16 , and the DST integrity processing unit  20 . 
     The DS error encoding parameters (e.g., or dispersed storage error coding parameters) include data segmenting information (e.g., how many segments data (e.g., a file, a group of files, a data block, etc.) is divided into), segment security information (e.g., per segment encryption, compression, integrity checksum, etc.), error coding information (e.g., pillar width, decode threshold, read threshold, write threshold, etc.), slicing information (e.g., the number of encoded data slices that will be created for each data segment); and slice security information (e.g., per encoded data slice encryption, compression, integrity checksum, etc.). 
     The DSTN managing unit  18  creates and stores user profile information (e.g., an access control list (ACL)) in local memory and/or within memory of the DSTN module  22 . The user profile information includes authentication information, permissions, and/or the security parameters. The security parameters may include encryption/decryption scheme, one or more encryption keys, key generation scheme, and/or data encoding/decoding scheme. 
     The DSTN managing unit  18  creates billing information for a particular user, a user group, a vault access, public vault access, etc. For instance, the DSTN managing unit  18  tracks the number of times a user accesses a private vault and/or public vaults, which can be used to generate a per-access billing information. In another instance, the DSTN managing unit  18  tracks the amount of data stored and/or retrieved by a user device and/or a user group, which can be used to generate a per-data-amount billing information. 
     Another DS management service includes the DSTN managing unit  18  performing network operations, network administration, and/or network maintenance. Network operations includes authenticating user data allocation requests (e.g., read and/or write requests), managing creation of vaults, establishing authentication credentials for user devices, adding/deleting components (e.g., user devices, DST execution units, and/or DST processing units) from the distributed computing system  10 , and/or establishing authentication credentials for DST execution units  36 . Network administration includes monitoring devices and/or units for failures, maintaining vault information, determining device and/or unit activation status, determining device and/or unit loading, and/or determining any other system level operation that affects the performance level of the system  10 . Network maintenance includes facilitating replacing, upgrading, repairing, and/or expanding a device and/or unit of the system  10 . 
     To support data storage integrity verification within the distributed computing system  10 , the DST integrity processing unit  20  performs rebuilding of ‘bad’ or missing encoded data slices. At a high level, the DST integrity processing unit  20  performs rebuilding by periodically attempting to retrieve/list encoded data slices, and/or slice names of the encoded data slices, from the DSTN module  22 . For retrieved encoded slices, they are checked for errors due to data corruption, outdated version, etc. If a slice includes an error, it is flagged as a ‘bad’ slice. For encoded data slices that were not received and/or not listed, they are flagged as missing slices. Bad and/or missing slices are subsequently rebuilt using other retrieved encoded data slices that are deemed to be good slices to produce rebuilt slices. The rebuilt slices are stored in memory of the DSTN module  22 . Note that the DST integrity processing unit  20  may be a separate unit as shown, it may be included in the DSTN module  22 , it may be included in the DST processing unit  16 , and/or distributed among the DST execution units  36 . 
     To support distributed task processing on received data, the distributed computing system  10  has two primary operations: DST (distributed storage and/or task processing) management and DST execution on received data (an example of which will be discussed with reference to  FIGS.  3 - 19   ). With respect to the storage portion of the DST management, the DSTN managing unit  18  functions as previously described. With respect to the tasking processing of the DST management, the DSTN managing unit  18  performs distributed task processing (DTP) management services. One such DTP management service includes the DSTN managing unit  18  establishing DTP parameters (e.g., user-vault affiliation information, billing information, user-task information, etc.) for a user device  12 - 14  individually or as part of a group of user devices. 
     Another DTP management service includes the DSTN managing unit  18  performing DTP network operations, network administration (which is essentially the same as described above), and/or network maintenance (which is essentially the same as described above). Network operations include, but are not limited to, authenticating user task processing requests (e.g., valid request, valid user, etc.), authenticating results and/or partial results, establishing DTP authentication credentials for user devices, adding/deleting components (e.g., user devices, DST execution units, and/or DST processing units) from the distributed computing system, and/or establishing DTP authentication credentials for DST execution units. 
     To support distributed task processing on stored data, the distributed computing system  10  has two primary operations: DST (distributed storage and/or task) management and DST execution on stored data. With respect to the DST execution on stored data, if the second type of user device  14  has a task request  38  for execution by the DSTN module  22 , it sends the task request  38  to the DST processing unit  16  via its interface  30 . An example of DST execution on stored data will be discussed in greater detail with reference to  FIGS.  27 - 39   . With respect to the DST management, it is substantially similar to the DST management to support distributed task processing on received data. 
       FIG.  2    is a schematic block diagram of an embodiment of a computing core  26  that includes a processing module  50 , a memory controller  52 , main memory  54 , a video graphics processing unit  55 , an input/output (TO) controller  56 , a peripheral component interconnect (PCI) interface  58 , an  10  interface module  60 , at least one  10  device interface module  62 , a read only memory (ROM) basic input output system (BIOS)  64 , and one or more memory interface modules. The one or more memory interface module(s) includes one or more of a universal serial bus (USB) interface module  66 , a host bus adapter (HBA) interface module  68 , a network interface module  70 , a flash interface module  72 , a hard drive interface module  74 , and a DSTN interface module  76 . 
     The DSTN interface module  76  functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). The DSTN interface module  76  and/or the network interface module  70  may function as the interface  30  of the user device  14  of  FIG.  1   . Further note that the  10  device interface module  62  and/or the memory interface modules may be collectively or individually referred to as 10 ports. 
       FIG.  3    is a diagram of an example of the distributed computing system performing a distributed storage and task processing operation. The distributed computing system includes a DST (distributed storage and/or task) client module  34  (which may be in user device  14  and/or in DST processing unit  16  of  FIG.  1   ), a network  24 , a plurality of DST execution units  1 - n  that includes two or more DST execution units  36  of  FIG.  1    (which form at least a portion of DSTN module  22  of  FIG.  1   ), a DST managing module (not shown), and a DST integrity verification module (not shown). The DST client module  34  includes an outbound DST processing section  80  and an inbound DST processing section  82 . Each of the DST execution units  1 - n  includes a controller  86 , a processing module  84 , memory  88 , a DT (distributed task) execution module  90 , and a DST client module  34 . 
     In an example of operation, the DST client module  34  receives data  92  and one or more tasks  94  to be performed upon the data  92 . The data  92  may be of any size and of any content, where, due to the size (e.g., greater than a few Terabytes), the content (e.g., secure data, etc.), and/or task(s) (e.g., MIPS intensive), distributed processing of the task(s) on the data is desired. For example, the data  92  may be one or more digital books, a copy of a company&#39;s emails, a large-scale Internet search, a video security file, one or more entertainment video files (e.g., television programs, movies, etc.), data files, and/or any other large amount of data (e.g., greater than a few Terabytes). 
     Within the DST client module  34 , the outbound DST processing section  80  receives the data  92  and the task(s)  94 . The outbound DST processing section  80  processes the data  92  to produce slice groupings  96 . As an example of such processing, the outbound DST processing section  80  partitions the data  92  into a plurality of data partitions. For each data partition, the outbound DST processing section  80  dispersed storage (DS) error encodes the data partition to produce encoded data slices and groups the encoded data slices into a slice grouping  96 . In addition, the outbound DST processing section  80  partitions the task  94  into partial tasks  98 , where the number of partial tasks  98  may correspond to the number of slice groupings  96 . 
     The outbound DST processing section  80  then sends, via the network  24 , the slice groupings  96  and the partial tasks  98  to the DST execution units  1 - n  of the DSTN module  22  of  FIG.  1   . For example, the outbound DST processing section  80  sends slice group  1  and partial task  1  to DST execution unit  1 . As another example, the outbound DST processing section  80  sends slice group #n and partial task #n to DST execution unit #n. 
     Each DST execution unit performs its partial task  98  upon its slice group  96  to produce partial results  102 . For example, DST execution unit # 1  performs partial task # 1  on slice group # 1  to produce a partial result # 1 , for results. As a more specific example, slice group # 1  corresponds to a data partition of a series of digital books and the partial task # 1  corresponds to searching for specific phrases, recording where the phrase is found, and establishing a phrase count. In this more specific example, the partial result # 1  includes information as to where the phrase was found and includes the phrase count. 
     Upon completion of generating their respective partial results  102 , the DST execution units send, via the network  24 , their partial results  102  to the inbound DST processing section  82  of the DST client module  34 . The inbound DST processing section  82  processes the received partial results  102  to produce a result  104 . Continuing with the specific example of the preceding paragraph, the inbound DST processing section  82  combines the phrase count from each of the DST execution units  36  to produce a total phrase count. In addition, the inbound DST processing section  82  combines the ‘where the phrase was found’ information from each of the DST execution units  36  within their respective data partitions to produce ‘where the phrase was found’ information for the series of digital books. 
     In another example of operation, the DST client module  34  requests retrieval of stored data within the memory of the DST execution units  36  (e.g., memory of the DSTN module). In this example, the task  94  is retrieve data stored in the memory of the DSTN module. Accordingly, the outbound DST processing section  80  converts the task  94  into a plurality of partial tasks  98  and sends the partial tasks  98  to the respective DST execution units  1 - n.    
     In response to the partial task  98  of retrieving stored data, a DST execution unit  36  identifies the corresponding encoded data slices  100  and retrieves them. For example, DST execution unit # 1  receives partial task # 1  and retrieves, in response thereto, retrieved slices # 1 . The DST execution units  36  send their respective retrieved slices  100  to the inbound DST processing section  82  via the network  24 . 
     The inbound DST processing section  82  converts the retrieved slices  100  into data  92 . For example, the inbound DST processing section  82  de-groups the retrieved slices  100  to produce encoded slices per data partition. The inbound DST processing section  82  then DS error decodes the encoded slices per data partition to produce data partitions. The inbound DST processing section  82  de-partitions the data partitions to recapture the data  92 . 
       FIG.  4    is a schematic block diagram of an embodiment of an outbound distributed storage and/or task (DST) processing section  80  of a DST client module  34   FIG.  1    coupled to a DSTN module  22  of a  FIG.  1    (e.g., a plurality of n DST execution units  36 ) via a network  24 . The outbound DST processing section  80  includes a data partitioning module  110 , a dispersed storage (DS) error encoding module  112 , a grouping selector module  114 , a control module  116 , and a distributed task control module  118 . 
     In an example of operation, the data partitioning module  110  partitions data  92  into a plurality of data partitions  120 . The number of partitions and the size of the partitions may be selected by the control module  116  via control  160  based on the data  92  (e.g., its size, its content, etc.), a corresponding task  94  to be performed (e.g., simple, complex, single step, multiple steps, etc.), DS encoding parameters (e.g., pillar width, decode threshold, write threshold, segment security parameters, slice security parameters, etc.), capabilities of the DST execution units  36  (e.g., processing resources, availability of processing recourses, etc.), and/or as may be inputted by a user, system administrator, or other operator (human or automated). For example, the data partitioning module  110  partitions the data  92  (e.g., 100 Terabytes) into 100,000 data segments, each being 1 Gigabyte in size. Alternatively, the data partitioning module  110  partitions the data  92  into a plurality of data segments, where some of data segments are of a different size, are of the same size, or a combination thereof. 
     The DS error encoding module  112  receives the data partitions  120  in a serial manner, a parallel manner, and/or a combination thereof. For each data partition  120 , the DS error encoding module  112  DS error encodes the data partition  120  in accordance with control information  160  from the control module  116  to produce encoded data slices  122 . The DS error encoding includes segmenting the data partition into data segments, segment security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC), etc.), error encoding, slicing, and/or per slice security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC), etc.). The control information  160  indicates which steps of the DS error encoding are active for a given data partition and, for active steps, indicates the parameters for the step. For example, the control information  160  indicates that the error encoding is active and includes error encoding parameters (e.g., pillar width, decode threshold, write threshold, read threshold, type of error encoding, etc.). 
     The grouping selector module  114  groups the encoded slices  122  of a data partition into a set of slice groupings  96 . The number of slice groupings corresponds to the number of DST execution units  36  identified for a particular task  94 . For example, if five DST execution units  36  are identified for the particular task  94 , the grouping selector module groups the encoded slices  122  of a data partition into five slice groupings  96 . The grouping selector module  114  outputs the slice groupings  96  to the corresponding DST execution units  36  via the network  24 . 
     The distributed task control module  118  receives the task  94  and converts the task  94  into a set of partial tasks  98 . For example, the distributed task control module  118  receives a task to find where in the data (e.g., a series of books) a phrase occurs and a total count of the phrase usage in the data. In this example, the distributed task control module  118  replicates the task  94  for each DST execution unit  36  to produce the partial tasks  98 . In another example, the distributed task control module  118  receives a task to find where in the data a first phrase occurs, where in the data a second phrase occurs, and a total count for each phrase usage in the data. In this example, the distributed task control module  118  generates a first set of partial tasks  98  for finding and counting the first phrase and a second set of partial tasks for finding and counting the second phrase. The distributed task control module  118  sends respective first and/or second partial tasks  98  to each DST execution unit  36 . 
       FIG.  5    is a logic diagram of an example of a method for outbound distributed storage and task (DST) processing that begins at step  126  where a DST client module receives data and one or more corresponding tasks. The method continues at step  128  where the DST client module determines a number of DST units to support the task for one or more data partitions. For example, the DST client module may determine the number of DST units to support the task based on the size of the data, the requested task, the content of the data, a predetermined number (e.g., user indicated, system administrator determined, etc.), available DST units, capability of the DST units, and/or any other factor regarding distributed task processing of the data. The DST client module may select the same DST units for each data partition, may select different DST units for the data partitions, or a combination thereof. 
     The method continues at step  130  where the DST client module determines processing parameters of the data based on the number of DST units selected for distributed task processing. The processing parameters include data partitioning information, DS encoding parameters, and/or slice grouping information. The data partitioning information includes a number of data partitions, size of each data partition, and/or organization of the data partitions (e.g., number of data blocks in a partition, the size of the data blocks, and arrangement of the data blocks). The DS encoding parameters include segmenting information, segment security information, error encoding information (e.g., dispersed storage error encoding function parameters including one or more of pillar width, decode threshold, write threshold, read threshold, generator matrix), slicing information, and/or per slice security information. The slice grouping information includes information regarding how to arrange the encoded data slices into groups for the selected DST units. As a specific example, if the DST client module determines that five DST units are needed to support the task, then it determines that the error encoding parameters include a pillar width of five and a decode threshold of three. 
     The method continues at step  132  where the DST client module determines task partitioning information (e.g., how to partition the tasks) based on the selected DST units and data processing parameters. The data processing parameters include the processing parameters and DST unit capability information. The DST unit capability information includes the number of DT (distributed task) execution units, execution capabilities of each DT execution unit (e.g., MIPS capabilities, processing resources (e.g., quantity and capability of microprocessors, CPUs, digital signal processors, co-processor, microcontrollers, arithmetic logic circuitry, and/or any other analog and/or digital processing circuitry), availability of the processing resources, memory information (e.g., type, size, availability, etc.)), and/or any information germane to executing one or more tasks. 
     The method continues at step  134  where the DST client module processes the data in accordance with the processing parameters to produce slice groupings. The method continues at step  136  where the DST client module partitions the task based on the task partitioning information to produce a set of partial tasks. The method continues at step  138  where the DST client module sends the slice groupings and the corresponding partial tasks to respective DST units. 
       FIG.  6    is a schematic block diagram of an embodiment of the dispersed storage (DS) error encoding module  112  of an outbound distributed storage and task (DST) processing section. The DS error encoding module  112  includes a segment processing module  142 , a segment security processing module  144 , an error encoding module  146 , a slicing module  148 , and a per slice security processing module  150 . Each of these modules is coupled to a control module  116  to receive control information  160  therefrom. 
     In an example of operation, the segment processing module  142  receives a data partition  120  from a data partitioning module and receives segmenting information as the control information  160  from the control module  116 . The segmenting information indicates how the segment processing module  142  is to segment the data partition  120 . For example, the segmenting information indicates how many rows to segment the data based on a decode threshold of an error encoding scheme, indicates how many columns to segment the data into based on a number and size of data blocks within the data partition  120 , and indicates how many columns to include in a data segment  152 . The segment processing module  142  segments the data  120  into data segments  152  in accordance with the segmenting information. 
     The segment security processing module  144 , when enabled by the control module  116 , secures the data segments  152  based on segment security information received as control information  160  from the control module  116 . The segment security information includes data compression, encryption, watermarking, integrity check (e.g., cyclic redundancy check (CRC), etc.), and/or any other type of digital security. For example, when the segment security processing module  144  is enabled, it may compress a data segment  152 , encrypt the compressed data segment, and generate a CRC value for the encrypted data segment to produce a secure data segment  154 . When the segment security processing module  144  is not enabled, it passes the data segments  152  to the error encoding module  146  or is bypassed such that the data segments  152  are provided to the error encoding module  146 . 
     The error encoding module  146  encodes the secure data segments  154  in accordance with error correction encoding parameters received as control information  160  from the control module  116 . The error correction encoding parameters (e.g., also referred to as dispersed storage error coding parameters) include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an online coding algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction encoding parameters identify a specific error correction encoding scheme, specifies a pillar width of five, and specifies a decode threshold of three. From these parameters, the error encoding module  146  encodes a data segment  154  to produce an encoded data segment  156 . 
     The slicing module  148  slices the encoded data segment  156  in accordance with the pillar width of the error correction encoding parameters received as control information  160 . For example, if the pillar width is five, the slicing module  148  slices an encoded data segment  156  into a set of five encoded data slices. As such, for a plurality of encoded data segments  156  for a given data partition, the slicing module outputs a plurality of sets of encoded data slices  158 . The per slice security processing module  150 , when enabled by the control module  116 , secures each encoded data slice  158  based on slice security information received as control information  160  from the control module  116 . The slice security information includes data compression, encryption, watermarking, integrity check (e.g., CRC, etc.), and/or any other type of digital security. For example, when the per slice security processing module  150  is enabled, it compresses an encoded data slice  158 , encrypts the compressed encoded data slice, and generates a CRC value for the encrypted encoded data slice to produce a secure encoded data slice  122 . When the per slice security processing module  150  is not enabled, it passes the encoded data slices  158  or is bypassed such that the encoded data slices  158  are the output of the DS error encoding module  112 . Note that the control module  116  may be omitted and each module stores its own parameters. 
       FIG.  7    is a diagram of an example of a segment processing of a dispersed storage (DS) error encoding module. In this example, a segment processing module  142  receives a data partition  120  that includes 45 data blocks (e.g., d 1 -d 45 ), receives segmenting information (i.e., control information  160 ) from a control module, and segments the data partition  120  in accordance with the control information  160  to produce data segments  152 . Each data block may be of the same size as other data blocks or of a different size. In addition, the size of each data block may be a few bytes to megabytes of data. As previously mentioned, the segmenting information indicates how many rows to segment the data partition into, indicates how many columns to segment the data partition into, and indicates how many columns to include in a data segment. 
     In this example, the decode threshold of the error encoding scheme is three; as such the number of rows to divide the data partition into is three. The number of columns for each row is set to 15, which is based on the number and size of data blocks. The data blocks of the data partition are arranged in rows and columns in a sequential order (i.e., the first row includes the first 15 data blocks; the second row includes the second 15 data blocks; and the third row includes the last 15 data blocks). 
     With the data blocks arranged into the desired sequential order, they are divided into data segments based on the segmenting information. In this example, the data partition is divided into 8 data segments; the first 7 include 2 columns of three rows and the last includes 1 column of three rows. Note that the first row of the 8 data segments is in sequential order of the first 15 data blocks; the second row of the 8 data segments in sequential order of the second 15 data blocks; and the third row of the 8 data segments in sequential order of the last 15 data blocks. Note that the number of data blocks, the grouping of the data blocks into segments, and size of the data blocks may vary to accommodate the desired distributed task processing function. 
       FIG.  8    is a diagram of an example of error encoding and slicing processing of the dispersed error encoding processing the data segments of  FIG.  7   . In this example, data segment  1  includes 3 rows with each row being treated as one word for encoding. As such, data segment  1  includes three words for encoding: word  1  including data blocks d 1  and d 2 , word  2  including data blocks d 16  and d 17 , and word  3  including data blocks d 31  and d 32 . Each of data segments  2 - 7  includes three words where each word includes two data blocks. Data segment  8  includes three words where each word includes a single data block (e.g., d 15 , d 30 , and d 45 ). 
     In operation, an error encoding module  146  and a slicing module  148  convert each data segment into a set of encoded data slices in accordance with error correction encoding parameters as control information  160 . More specifically, when the error correction encoding parameters indicate a unity matrix Reed-Solomon based encoding algorithm, 5 pillars, and decode threshold of 3, the first three encoded data slices of the set of encoded data slices for a data segment are substantially similar to the corresponding word of the data segment. For instance, when the unity matrix Reed-Solomon based encoding algorithm is applied to data segment  1 , the content of the first encoded data slice (DS 1 _d 1 &amp; 2 ) of the first set of encoded data slices (e.g., corresponding to data segment  1 ) is substantially similar to content of the first word (e.g., d 1  &amp; d 2 ); the content of the second encoded data slice (DS 1 _d 16 &amp; 17 ) of the first set of encoded data slices is substantially similar to content of the second word (e.g., d 16  &amp; d 17 ); and the content of the third encoded data slice (DS 1 _d 31 &amp; 32 ) of the first set of encoded data slices is substantially similar to content of the third word (e.g., d 31  &amp; d 32 ). 
     The content of the fourth and fifth encoded data slices (e.g., ES 1 _ 1  and ES 1 _ 2 ) of the first set of encoded data slices include error correction data based on the first-third words of the first data segment. With such an encoding and slicing scheme, retrieving any three of the five encoded data slices allows the data segment to be accurately reconstructed. 
     The encoding and slicing of data segments  2 - 7  yield sets of encoded data slices similar to the set of encoded data slices of data segment  1 . For instance, the content of the first encoded data slice (DS 2 _d 3 &amp; 4 ) of the second set of encoded data slices (e.g., corresponding to data segment  2 ) is substantially similar to content of the first word (e.g., d 3  &amp; d 4 ); the content of the second encoded data slice (DS 2 _d 18 &amp; 19 ) of the second set of encoded data slices is substantially similar to content of the second word (e.g., d 18  &amp; d 19 ); and the content of the third encoded data slice (DS 2 _d 33 &amp; 34 ) of the second set of encoded data slices is substantially similar to content of the third word (e.g., d 33  &amp; d 34 ). The content of the fourth and fifth encoded data slices (e.g., ES 1 _ 1  and ES 1 _ 2 ) of the second set of encoded data slices includes error correction data based on the first-third words of the second data segment. 
       FIG.  9    is a diagram of an example of grouping selection processing of an outbound distributed storage and task (DST) processing in accordance with grouping selector information as control information  160  from a control module. Encoded slices for data partition  122  are grouped in accordance with the control information  160  to produce slice groupings  96 . In this example, a grouping selector module  114  organizes the encoded data slices into five slice groupings (e.g., one for each DST execution unit of a distributed storage and task network (DSTN) module). As a specific example, the grouping selector module  114  creates a first slice grouping for a DST execution unit # 1 , which includes first encoded slices of each of the sets of encoded slices. As such, the first DST execution unit receives encoded data slices corresponding to data blocks  1 - 15  (e.g., encoded data slices of contiguous data). 
     The grouping selector module  114  also creates a second slice grouping for a DST execution unit # 2 , which includes second encoded slices of each of the sets of encoded slices. As such, the second DST execution unit receives encoded data slices corresponding to data blocks  16 - 30 . The grouping selector module  114  further creates a third slice grouping for DST execution unit # 3 , which includes third encoded slices of each of the sets of encoded slices. As such, the third DST execution unit receives encoded data slices corresponding to data blocks  31 - 45 . 
     The grouping selector module  114  creates a fourth slice grouping for DST execution unit # 4 , which includes fourth encoded slices of each of the sets of encoded slices. As such, the fourth DST execution unit receives encoded data slices corresponding to first error encoding information (e.g., encoded data slices of error coding (EC) data). The grouping selector module  114  further creates a fifth slice grouping for DST execution unit # 5 , which includes fifth encoded slices of each of the sets of encoded slices. As such, the fifth DST execution unit receives encoded data slices corresponding to second error encoding information. 
       FIG.  10    is a diagram of an example of converting data  92  into slice groups that expands on the preceding figures. As shown, the data  92  is partitioned in accordance with a partitioning function  164  into a plurality of data partitions ( 1 - x , where x is an integer greater than 4). Each data partition (or chunkset of data) is encoded and grouped into slice groupings as previously discussed by an encoding and grouping function  166 . For a given data partition, the slice groupings are sent to distributed storage and task (DST) execution units. From data partition to data partition, the ordering of the slice groupings to the DST execution units may vary. 
     For example, the slice groupings of data partition # 1  is sent to the DST execution units such that the first DST execution receives first encoded data slices of each of the sets of encoded data slices, which corresponds to a first continuous data chunk of the first data partition (e.g., refer to  FIG.  9   ), a second DST execution receives second encoded data slices of each of the sets of encoded data slices, which corresponds to a second continuous data chunk of the first data partition, etc. 
     For the second data partition, the slice groupings may be sent to the DST execution units in a different order than it was done for the first data partition. For instance, the first slice grouping of the second data partition (e.g., slice group  2 _ 1 ) is sent to the second DST execution unit; the second slice grouping of the second data partition (e.g., slice group  2 _ 2 ) is sent to the third DST execution unit; the third slice grouping of the second data partition (e.g., slice group  2 _ 3 ) is sent to the fourth DST execution unit; the fourth slice grouping of the second data partition (e.g., slice group  2 _ 4 , which includes first error coding information) is sent to the fifth DST execution unit; and the fifth slice grouping of the second data partition (e.g., slice group  2 _ 5 , which includes second error coding information) is sent to the first DST execution unit. 
     The pattern of sending the slice groupings to the set of DST execution units may vary in a predicted pattern, a random pattern, and/or a combination thereof from data partition to data partition. In addition, from data partition to data partition, the set of DST execution units may change. For example, for the first data partition, DST execution units  1 - 5  may be used; for the second data partition, DST execution units  6 - 10  may be used; for the third data partition, DST execution units  3 - 7  may be used; etc. As is also shown, the task is divided into partial tasks that are sent to the DST execution units in conjunction with the slice groupings of the data partitions. 
       FIG.  11    is a schematic block diagram of an embodiment of a DST (distributed storage and/or task) execution unit that includes an interface  169 , a controller  86 , memory  88 , one or more DT (distributed task) execution modules  90 , and a DST client module  34 . The memory  88  is of sufficient size to store a significant number of encoded data slices (e.g., thousands of slices to hundreds-of-millions of slices) and may include one or more hard drives and/or one or more solid-state memory devices (e.g., flash memory, DRAM, etc.). 
     In an example of storing a slice group, the DST execution module receives a slice grouping  96  (e.g., slice group # 1 ) via interface  169 . The slice grouping  96  includes, per partition, encoded data slices of contiguous data or encoded data slices of error coding (EC) data. For slice group # 1 , the DST execution module receives encoded data slices of contiguous data for partitions # 1  and #x (and potentially others between 3 and x) and receives encoded data slices of EC data for partitions # 2  and # 3  (and potentially others between 3 and x). Examples of encoded data slices of contiguous data and encoded data slices of error coding (EC) data are discussed with reference to  FIG.  9   . The memory  88  stores the encoded data slices of slice groupings  96  in accordance with memory control information  174  it receives from the controller  86 . 
     The controller  86  (e.g., a processing module, a CPU, etc.) generates the memory control information  174  based on a partial task(s)  98  and distributed computing information (e.g., user information (e.g., user ID, distributed computing permissions, data access permission, etc.), vault information (e.g., virtual memory assigned to user, user group, temporary storage for task processing, etc.), task validation information, etc.). For example, the controller  86  interprets the partial task(s)  98  in light of the distributed computing information to determine whether a requestor is authorized to perform the task  98 , is authorized to access the data, and/or is authorized to perform the task on this particular data. When the requestor is authorized, the controller  86  determines, based on the task  98  and/or another input, whether the encoded data slices of the slice grouping  96  are to be temporarily stored or permanently stored. Based on the foregoing, the controller  86  generates the memory control information  174  to write the encoded data slices of the slice grouping  96  into the memory  88  and to indicate whether the slice grouping  96  is permanently stored or temporarily stored. 
     With the slice grouping  96  stored in the memory  88 , the controller  86  facilitates execution of the partial task(s)  98 . In an example, the controller  86  interprets the partial task  98  in light of the capabilities of the DT execution module(s)  90 . The capabilities include one or more of MIPS capabilities, processing resources (e.g., quantity and capability of microprocessors, CPUs, digital signal processors, co-processor, microcontrollers, arithmetic logic circuitry, and/or any other analog and/or digital processing circuitry), availability of the processing resources, etc. If the controller  86  determines that the DT execution module(s)  90  have sufficient capabilities, it generates task control information  176 . 
     The task control information  176  may be a generic instruction (e.g., perform the task on the stored slice grouping) or a series of operational codes. In the former instance, the DT execution module  90  includes a co-processor function specifically configured (fixed or programmed) to perform the desired task  98 . In the latter instance, the DT execution module  90  includes a general processor topology where the controller stores an algorithm corresponding to the particular task  98 . In this instance, the controller  86  provides the operational codes (e.g., assembly language, source code of a programming language, object code, etc.) of the algorithm to the DT execution module  90  for execution. 
     Depending on the nature of the task  98 , the DT execution module  90  may generate intermediate partial results  102  that are stored in the memory  88  or in a cache memory (not shown) within the DT execution module  90 . In either case, when the DT execution module  90  completes execution of the partial task  98 , it outputs one or more partial results  102 . The partial results  102  may also be stored in memory  88 . 
     If, when the controller  86  is interpreting whether capabilities of the DT execution module(s)  90  can support the partial task  98 , the controller  86  determines that the DT execution module(s)  90  cannot adequately support the task  98  (e.g., does not have the right resources, does not have sufficient available resources, available resources would be too slow, etc.), it then determines whether the partial task  98  should be fully offloaded or partially offloaded. 
     If the controller  86  determines that the partial task  98  should be fully offloaded, it generates DST control information  178  and provides it to the DST client module  34 . The DST control information  178  includes the partial task  98 , memory storage information regarding the slice grouping  96 , and distribution instructions. The distribution instructions instruct the DST client module  34  to divide the partial task  98  into sub-partial tasks  172 , to divide the slice grouping  96  into sub-slice groupings  170 , and identify other DST execution units. The DST client module  34  functions in a similar manner as the DST client module  34  of  FIGS.  3 - 10    to produce the sub-partial tasks  172  and the sub-slice groupings  170  in accordance with the distribution instructions. 
     The DST client module  34  receives DST feedback  168  (e.g., sub-partial results), via the interface  169 , from the DST execution units to which the task was offloaded. The DST client module  34  provides the sub-partial results to the DST execution unit, which processes the sub-partial results to produce the partial result(s)  102 . 
     If the controller  86  determines that the partial task  98  should be partially offloaded, it determines what portion of the task  98  and/or slice grouping  96  should be processed locally and what should be offloaded. For the portion that is being locally processed, the controller  86  generates task control information  176  as previously discussed. For the portion that is being offloaded, the controller  86  generates DST control information  178  as previously discussed. 
     When the DST client module  34  receives DST feedback  168  (e.g., sub-partial results) from the DST executions units to which a portion of the task was offloaded, it provides the sub-partial results to the DT execution module  90 . The DT execution module  90  processes the sub-partial results with the sub-partial results it created to produce the partial result(s)  102 . 
     The memory  88  may be further utilized to retrieve one or more of stored slices  100 , stored results  104 , partial results  102  when the DT execution module  90  stores partial results  102  and/or results  104  in the memory  88 . For example, when the partial task  98  includes a retrieval request, the controller  86  outputs the memory control  174  to the memory  88  to facilitate retrieval of slices  100  and/or results  104 . 
       FIG.  12    is a schematic block diagram of an example of operation of a distributed storage and task (DST) execution unit storing encoded data slices and executing a task thereon. To store the encoded data slices of a partition  1  of slice grouping  1 , a controller  86  generates write commands as memory control information  174  such that the encoded slices are stored in desired locations (e.g., permanent or temporary) within memory  88 . 
     Once the encoded slices are stored, the controller  86  provides task control information  176  to a distributed task (DT) execution module  90 . As a first step of executing the task in accordance with the task control information  176 , the DT execution module  90  retrieves the encoded slices from memory  88 . The DT execution module  90  then reconstructs contiguous data blocks of a data partition. As shown for this example, reconstructed contiguous data blocks of data partition  1  include data blocks  1 - 15  (e.g., d 1 -d 15 ). 
     With the contiguous data blocks reconstructed, the DT execution module  90  performs the task on the reconstructed contiguous data blocks. For example, the task may be to search the reconstructed contiguous data blocks for a particular word or phrase, identify where in the reconstructed contiguous data blocks the particular word or phrase occurred, and/or count the occurrences of the particular word or phrase on the reconstructed contiguous data blocks. The DST execution unit continues in a similar manner for the encoded data slices of other partitions in slice grouping  1 . Note that with using the unity matrix error encoding scheme previously discussed, if the encoded data slices of contiguous data are uncorrupted, the decoding of them is a relatively straightforward process of extracting the data. 
     If, however, an encoded data slice of contiguous data is corrupted (or missing), it can be rebuilt by accessing other DST execution units that are storing the other encoded data slices of the set of encoded data slices of the corrupted encoded data slice. In this instance, the DST execution unit having the corrupted encoded data slices retrieves at least three encoded data slices (of contiguous data and of error coding data) in the set from the other DST execution units (recall for this example, the pillar width is 5 and the decode threshold is 3). The DST execution unit decodes the retrieved data slices using the DS error encoding parameters to recapture the corresponding data segment. The DST execution unit then re-encodes the data segment using the DS error encoding parameters to rebuild the corrupted encoded data slice. Once the encoded data slice is rebuilt, the DST execution unit functions as previously described. 
       FIG.  13    is a schematic block diagram of an embodiment of an inbound distributed storage and/or task (DST) processing section  82  of a DST client module coupled to DST execution units of a distributed storage and task network (DSTN) module via a network  24 . The inbound DST processing section  82  includes a de-grouping module  180 , a DS (dispersed storage) error decoding module  182 , a data de-partitioning module  184 , a control module  186 , and a distributed task control module  188 . Note that the control module  186  and/or the distributed task control module  188  may be separate modules from corresponding ones of outbound DST processing section or may be the same modules. 
     In an example of operation, the DST execution units have completed execution of corresponding partial tasks on the corresponding slice groupings to produce partial results  102 . The inbound DST processing section  82  receives the partial results  102  via the distributed task control module  188 . The inbound DST processing section  82  then processes the partial results  102  to produce a final result, or results  104 . For example, if the task was to find a specific word or phrase within data, the partial results  102  indicate where in each of the prescribed portions of the data the corresponding DST execution units found the specific word or phrase. The distributed task control module  188  combines the individual partial results  102  for the corresponding portions of the data into a final result  104  for the data as a whole. 
     In another example of operation, the inbound DST processing section  82  is retrieving stored data from the DST execution units (i.e., the DSTN module). In this example, the DST execution units output encoded data slices  100  corresponding to the data retrieval requests. The de-grouping module  180  receives retrieved slices  100  and de-groups them to produce encoded data slices per data partition  122 . The DS error decoding module  182  decodes, in accordance with DS error encoding parameters, the encoded data slices per data partition  122  to produce data partitions  120 . 
     The data de-partitioning module  184  combines the data partitions  120  into the data  92 . The control module  186  controls the conversion of retrieved slices  100  into the data  92  using control signals  190  to each of the modules. For instance, the control module  186  provides de-grouping information to the de-grouping module  180 , provides the DS error encoding parameters to the DS error decoding module  182 , and provides de-partitioning information to the data de-partitioning module  184 . 
       FIG.  14    is a logic diagram of an example of a method that is executable by distributed storage and task (DST) client module regarding inbound DST processing. The method begins at step  194  where the DST client module receives partial results. The method continues at step  196  where the DST client module retrieves the task corresponding to the partial results. For example, the partial results include header information that identifies the requesting entity, which correlates to the requested task. 
     The method continues at step  198  where the DST client module determines result processing information based on the task. For example, if the task were to identify a particular word or phrase within the data, the result processing information would indicate to aggregate the partial results for the corresponding portions of the data to produce the final result. As another example, if the task were to count the occurrences of a particular word or phrase within the data, results of processing the information would indicate to add the partial results to produce the final results. The method continues at step  200  where the DST client module processes the partial results in accordance with the result processing information to produce the final result or results. 
       FIG.  15    is a diagram of an example of de-grouping selection processing of an inbound distributed storage and task (DST) processing section of a DST client module. In general, this is an inverse process of the grouping module of the outbound DST processing section of  FIG.  9   . Accordingly, for each data partition (e.g., partition # 1 ), the de-grouping module retrieves the corresponding slice grouping from the DST execution units (EU) (e.g., DST  1 - 5 ). 
     As shown, DST execution unit # 1  provides a first slice grouping, which includes the first encoded slices of each of the sets of encoded slices (e.g., encoded data slices of contiguous data of data blocks  1 - 15 ); DST execution unit # 2  provides a second slice grouping, which includes the second encoded slices of each of the sets of encoded slices (e.g., encoded data slices of contiguous data of data blocks  16 - 30 ); DST execution unit # 3  provides a third slice grouping, which includes the third encoded slices of each of the sets of encoded slices (e.g., encoded data slices of contiguous data of data blocks  31 - 45 ); DST execution unit # 4  provides a fourth slice grouping, which includes the fourth encoded slices of each of the sets of encoded slices (e.g., first encoded data slices of error coding (EC) data); and DST execution unit # 5  provides a fifth slice grouping, which includes the fifth encoded slices of each of the sets of encoded slices (e.g., first encoded data slices of error coding (EC) data). 
     The de-grouping module de-groups the slice groupings (e.g., received slices  100 ) using a de-grouping selector  180  controlled by a control signal  190  as shown in the example to produce a plurality of sets of encoded data slices (e.g., retrieved slices for a partition into sets of slices  122 ). Each set corresponding to a data segment of the data partition. 
       FIG.  16    is a schematic block diagram of an embodiment of a dispersed storage (DS) error decoding module  182  of an inbound distributed storage and task (DST) processing section. The DS error decoding module  182  includes an inverse per slice security processing module  202 , a de-slicing module  204 , an error decoding module  206 , an inverse segment security module  208 , a de-segmenting processing module  210 , and a control module  186 . 
     In an example of operation, the inverse per slice security processing module  202 , when enabled by the control module  186 , unsecures each encoded data slice  122  based on slice de-security information received as control information  190  (e.g., the compliment of the slice security information discussed with reference to  FIG.  6   ) received from the control module  186 . The slice security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC verification, etc.), and/or any other type of digital security. For example, when the inverse per slice security processing module  202  is enabled, it verifies integrity information (e.g., a CRC value) of each encoded data slice  122 , it decrypts each verified encoded data slice, and decompresses each decrypted encoded data slice to produce slice encoded data  158 . When the inverse per slice security processing module  202  is not enabled, it passes the encoded data slices  122  as the sliced encoded data  158  or is bypassed such that the retrieved encoded data slices  122  are provided as the sliced encoded data  158 . 
     The de-slicing module  204  de-slices the sliced encoded data  158  into encoded data segments  156  in accordance with a pillar width of the error correction encoding parameters received as control information  190  from the control module  186 . For example, if the pillar width is five, the de-slicing module  204  de-slices a set of five encoded data slices into an encoded data segment  156 . The error decoding module  206  decodes the encoded data segments  156  in accordance with error correction decoding parameters received as control information  190  from the control module  186  to produce secure data segments  154 . The error correction decoding parameters include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction decoding parameters identify a specific error correction encoding scheme, specify a pillar width of five, and specify a decode threshold of three. 
     The inverse segment security processing module  208 , when enabled by the control module  186 , unsecures the secured data segments  154  based on segment security information received as control information  190  from the control module  186 . The segment security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC, etc.) verification, and/or any other type of digital security. For example, when the inverse segment security processing module  208  is enabled, it verifies integrity information (e.g., a CRC value) of each secure data segment  154 , it decrypts each verified secured data segment, and decompresses each decrypted secure data segment to produce a data segment  152 . When the inverse segment security processing module  208  is not enabled, it passes the decoded data segment  154  as the data segment  152  or is by-passed. 
     The de-segment processing module  210  receives the data segments  152  and receives de-segmenting information as control information  190  from the control module  186 . The de-segmenting information indicates how the de-segment processing module  210  is to de-segment the data segments  152  into a data partition  120 . For example, the de-segmenting information indicates how the rows and columns of data segments are to be rearranged to yield the data partition  120 . 
       FIG.  17    is a diagram of an example of de-slicing and error decoding processing of a dispersed error decoding module. A de-slicing module  204  receives at least a decode threshold number of encoded data slices  158  for each data segment in accordance with control information  190  and provides encoded data  156 . In this example, a decode threshold is three. As such, each set of encoded data slices  158  is shown to have three encoded data slices per data segment. The de-slicing module  204  may receive three encoded data slices per data segment because an associated distributed storage and task (DST) client module requested retrieving only three encoded data slices per segment or selected three of the retrieved encoded data slices per data segment. As shown, which is based on the unity matrix encoding previously discussed with reference to  FIG.  8   , an encoded data slice may be a data-based encoded data slice (e.g., DS 1 _d 1 &amp;d 2 ) or an error code based encoded data slice (e.g., ES 3 _ 1 ). 
     An error decoding module  206  decodes the encoded data  156  of each data segment in accordance with the error correction decoding parameters of control information  190  to produce secured segments  154 . In this example, data segment  1  includes 3 rows with each row being treated as one word for encoding. As such, data segment  1  includes three words: word  1  including data blocks d 1  and d 2 , word  2  including data blocks d 16  and d 17 , and word  3  including data blocks d 31  and d 32 . Each of data segments  2 - 7  includes three words where each word includes two data blocks. Data segment  8  includes three words where each word includes a single data block (e.g., d 15 , d 30 , and d 45 ). 
       FIG.  18    is a diagram of an example of de-segment processing of an inbound distributed storage and task (DST) processing. In this example, a de-segment processing module  210  receives data segments  152  (e.g.,  1 - 8 ) and rearranges the data blocks of the data segments into rows and columns in accordance with de-segmenting information of control information  190  to produce a data partition  120 . Note that the number of rows is based on the decode threshold (e.g., 3 in this specific example) and the number of columns is based on the number and size of the data blocks. 
     The de-segmenting module  210  converts the rows and columns of data blocks into the data partition  120 . Note that each data block may be of the same size as other data blocks or of a different size. In addition, the size of each data block may be a few bytes to megabytes of data. 
       FIG.  19    is a diagram of an example of converting slice groups into data  92  within an inbound distributed storage and task (DST) processing section. As shown, the data  92  is reconstructed from a plurality of data partitions ( 1 - x , where x is an integer greater than 4). Each data partition (or chunk set of data) is decoded and re-grouped using a de-grouping and decoding function  212  and a de-partition function  214  from slice groupings as previously discussed. For a given data partition, the slice groupings (e.g., at least a decode threshold per data segment of encoded data slices) are received from DST execution units. From data partition to data partition, the ordering of the slice groupings received from the DST execution units may vary as discussed with reference to  FIG.  10   . 
       FIG.  20    is a diagram of an example of a distributed storage and/or retrieval within the distributed computing system. The distributed computing system includes a plurality of distributed storage and/or task (DST) processing client modules  34  (one shown) coupled to a distributed storage and/or task processing network (DSTN) module, or multiple DSTN modules, via a network  24 . The DST client module  34  includes an outbound DST processing section  80  and an inbound DST processing section  82 . The DSTN module includes a plurality of DST execution units. Each DST execution unit includes a controller  86 , memory  88 , one or more distributed task (DT) execution modules  90 , and a DST client module  34 . 
     In an example of data storage, the DST client module  34  has data  92  that it desires to store in the DSTN module. The data  92  may be a file (e.g., video, audio, text, graphics, etc.), a data object, a data block, an update to a file, an update to a data block, etc. In this instance, the outbound DST processing module  80  converts the data  92  into encoded data slices  216  as will be further described with reference to  FIGS.  21 - 23   . The outbound DST processing module  80  sends, via the network  24 , to the DST execution units for storage as further described with reference to  FIG.  24   . 
     In an example of data retrieval, the DST client module  34  issues a retrieve request to the DST execution units for the desired data  92 . The retrieve request may address each DST executions units storing encoded data slices of the desired data, address a decode threshold number of DST execution units, address a read threshold number of DST execution units, or address some other number of DST execution units. In response to the request, each addressed DST execution unit retrieves its encoded data slices  100  of the desired data and sends them to the inbound DST processing section  82 , via the network  24 . 
     When, for each data segment, the inbound DST processing section  82  receives at least a decode threshold number of encoded data slices  100 , it converts the encoded data slices  100  into a data segment. The inbound DST processing section  82  aggregates the data segments to produce the retrieved data  92 . 
       FIG.  21    is a schematic block diagram of an embodiment of an outbound distributed storage and/or task (DST) processing section  80  of a DST client module coupled to a distributed storage and task network (DSTN) module (e.g., a plurality of DST execution units) via a network  24 . The outbound DST processing section  80  includes a data partitioning module  110 , a dispersed storage (DS) error encoding module  112 , a grouping selector module  114 , a control module  116 , and a distributed task control module  118 . 
     In an example of operation, the data partitioning module  110  is by-passed such that data  92  is provided directly to the DS error encoding module  112 . The control module  116  coordinates the by-passing of the data partitioning module  110  by outputting a bypass  220  message to the data partitioning module  110 . 
     The DS error encoding module  112  receives the data  92  in a serial manner, a parallel manner, and/or a combination thereof. The DS error encoding module  112  DS error encodes the data in accordance with control information  160  from the control module  116  to produce encoded data slices  218 . The DS error encoding includes segmenting the data  92  into data segments, segment security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC, etc.)), error encoding, slicing, and/or per slice security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC, etc.)). The control information  160  indicates which steps of the DS error encoding are active for the data  92  and, for active steps, indicates the parameters for the step. For example, the control information  160  indicates that the error encoding is active and includes error encoding parameters (e.g., pillar width, decode threshold, write threshold, read threshold, type of error encoding, etc.). 
     The grouping selector module  114  groups the encoded slices  218  of the data segments into pillars of slices  216 . The number of pillars corresponds to the pillar width of the DS error encoding parameters. In this example, the distributed task control module  118  facilitates the storage request. 
       FIG.  22    is a schematic block diagram of an example of a dispersed storage (DS) error encoding module  112  for the example of  FIG.  21   . The DS error encoding module  112  includes a segment processing module  142 , a segment security processing module  144 , an error encoding module  146 , a slicing module  148 , and a per slice security processing module  150 . Each of these modules is coupled to a control module  116  to receive control information  160  therefrom. 
     In an example of operation, the segment processing module  142  receives data  92  and receives segmenting information as control information  160  from the control module  116 . The segmenting information indicates how the segment processing module is to segment the data. For example, the segmenting information indicates the size of each data segment. The segment processing module  142  segments the data  92  into data segments  152  in accordance with the segmenting information. 
     The segment security processing module  144 , when enabled by the control module  116 , secures the data segments  152  based on segment security information received as control information  160  from the control module  116 . The segment security information includes data compression, encryption, watermarking, integrity check (e.g., CRC, etc.), and/or any other type of digital security. For example, when the segment security processing module  144  is enabled, it compresses a data segment  152 , encrypts the compressed data segment, and generates a CRC value for the encrypted data segment to produce a secure data segment. When the segment security processing module  144  is not enabled, it passes the data segments  152  to the error encoding module  146  or is bypassed such that the data segments  152  are provided to the error encoding module  146 . 
     The error encoding module  146  encodes the secure data segments in accordance with error correction encoding parameters received as control information  160  from the control module  116 . The error correction encoding parameters include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction encoding parameters identify a specific error correction encoding scheme, specifies a pillar width of five, and specifies a decode threshold of three. From these parameters, the error encoding module  146  encodes a data segment to produce an encoded data segment. 
     The slicing module  148  slices the encoded data segment in accordance with a pillar width of the error correction encoding parameters. For example, if the pillar width is five, the slicing module slices an encoded data segment into a set of five encoded data slices. As such, for a plurality of data segments, the slicing module  148  outputs a plurality of sets of encoded data slices as shown within encoding and slicing function  222  as described. 
     The per slice security processing module  150 , when enabled by the control module  116 , secures each encoded data slice based on slice security information received as control information  160  from the control module  116 . The slice security information includes data compression, encryption, watermarking, integrity check (e.g., CRC, etc.), and/or any other type of digital security. For example, when the per slice security processing module  150  is enabled, it may compress an encoded data slice, encrypt the compressed encoded data slice, and generate a CRC value for the encrypted encoded data slice to produce a secure encoded data slice tweaking. When the per slice security processing module  150  is not enabled, it passes the encoded data slices or is bypassed such that the encoded data slices  218  are the output of the DS error encoding module  112 . 
       FIG.  23    is a diagram of an example of converting data  92  into pillar slice groups utilizing encoding, slicing and pillar grouping function  224  for storage in memory of a distributed storage and task network (DSTN) module. As previously discussed the data  92  is encoded and sliced into a plurality of sets of encoded data slices; one set per data segment. The grouping selector module organizes the sets of encoded data slices into pillars of data slices. In this example, the DS error encoding parameters include a pillar width of 5 and a decode threshold of 3. As such, for each data segment, 5 encoded data slices are created. 
     The grouping selector module takes the first encoded data slice of each of the sets and forms a first pillar, which may be sent to the first DST execution unit. Similarly, the grouping selector module creates the second pillar from the second slices of the sets; the third pillar from the third slices of the sets; the fourth pillar from the fourth slices of the sets; and the fifth pillar from the fifth slices of the set. 
       FIG.  24    is a schematic block diagram of an embodiment of a distributed storage and/or task (DST) execution unit that includes an interface  169 , a controller  86 , memory  88 , one or more distributed task (DT) execution modules  90 , and a DST client module  34 . A computing core  26  may be utilized to implement the one or more DT execution modules  90  and the DST client module  34 . The memory  88  is of sufficient size to store a significant number of encoded data slices (e.g., thousands of slices to hundreds-of-millions of slices) and may include one or more hard drives and/or one or more solid-state memory devices (e.g., flash memory, DRAM, etc.). 
     In an example of storing a pillar of slices  216 , the DST execution unit receives, via interface  169 , a pillar of slices  216  (e.g., pillar # 1  slices). The memory  88  stores the encoded data slices  216  of the pillar of slices in accordance with memory control information  174  it receives from the controller  86 . The controller  86  (e.g., a processing module, a CPU, etc.) generates the memory control information  174  based on distributed storage information (e.g., user information (e.g., user ID, distributed storage permissions, data access permission, etc.), vault information (e.g., virtual memory assigned to user, user group, etc.), etc.). Similarly, when retrieving slices, the DST execution unit receives, via interface  169 , a slice retrieval request. The memory  88  retrieves the slice in accordance with memory control information  174  it receives from the controller  86 . The memory  88  outputs the slice  100 , via the interface  169 , to a requesting entity. 
       FIG.  25    is a schematic block diagram of an example of operation of an inbound distributed storage and/or task (DST) processing section  82  for retrieving dispersed error encoded data  92 . The inbound DST processing section  82  includes a de-grouping module  180 , a dispersed storage (DS) error decoding module  182 , a data de-partitioning module  184 , a control module  186 , and a distributed task control module  188 . Note that the control module  186  and/or the distributed task control module  188  may be separate modules from corresponding ones of an outbound DST processing section or may be the same modules. 
     In an example of operation, the inbound DST processing section  82  is retrieving stored data  92  from the DST execution units (i.e., the DSTN module). In this example, the DST execution units output encoded data slices corresponding to data retrieval requests from the distributed task control module  188 . The de-grouping module  180  receives pillars of slices  100  and de-groups them in accordance with control information  190  from the control module  186  to produce sets of encoded data slices  218 . The DS error decoding module  182  decodes, in accordance with the DS error encoding parameters received as control information  190  from the control module  186 , each set of encoded data slices  218  to produce data segments, which are aggregated into retrieved data  92 . The data de-partitioning module  184  is by-passed in this operational mode via a bypass signal  226  of control information  190  from the control module  186 . 
       FIG.  26    is a schematic block diagram of an embodiment of a dispersed storage (DS) error decoding module  182  of an inbound distributed storage and task (DST) processing section. The DS error decoding module  182  includes an inverse per slice security processing module  202 , a de-slicing module  204 , an error decoding module  206 , an inverse segment security module  208 , and a de-segmenting processing module  210 . The dispersed error decoding module  182  is operable to de-slice and decode encoded slices per data segment  218  utilizing a de-slicing and decoding function  228  to produce a plurality of data segments that are de-segmented utilizing a de-segment function  230  to recover data  92 . 
     In an example of operation, the inverse per slice security processing module  202 , when enabled by the control module  186  via control information  190 , unsecures each encoded data slice  218  based on slice de-security information (e.g., the compliment of the slice security information discussed with reference to  FIG.  6   ) received as control information  190  from the control module  186 . The slice de-security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC verification, etc.), and/or any other type of digital security. For example, when the inverse per slice security processing module  202  is enabled, it verifies integrity information (e.g., a CRC value) of each encoded data slice  218 , it decrypts each verified encoded data slice, and decompresses each decrypted encoded data slice to produce slice encoded data. When the inverse per slice security processing module  202  is not enabled, it passes the encoded data slices  218  as the sliced encoded data or is bypassed such that the retrieved encoded data slices  218  are provided as the sliced encoded data. 
     The de-slicing module  204  de-slices the sliced encoded data into encoded data segments in accordance with a pillar width of the error correction encoding parameters received as control information  190  from a control module  186 . For example, if the pillar width is five, the de-slicing module de-slices a set of five encoded data slices into an encoded data segment. Alternatively, the encoded data segment may include just three encoded data slices (e.g., when the decode threshold is 3). 
     The error decoding module  206  decodes the encoded data segments in accordance with error correction decoding parameters received as control information  190  from the control module  186  to produce secure data segments. The error correction decoding parameters include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction decoding parameters identify a specific error correction encoding scheme, specify a pillar width of five, and specify a decode threshold of three. 
     The inverse segment security processing module  208 , when enabled by the control module  186 , unsecures the secured data segments based on segment security information received as control information  190  from the control module  186 . The segment security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC, etc.) verification, and/or any other type of digital security. For example, when the inverse segment security processing module is enabled, it verifies integrity information (e.g., a CRC value) of each secure data segment, it decrypts each verified secured data segment, and decompresses each decrypted secure data segment to produce a data segment  152 . When the inverse segment security processing module  208  is not enabled, it passes the decoded data segment  152  as the data segment or is bypassed. The de-segmenting processing module  210  aggregates the data segments  152  into the data  92  in accordance with control information  190  from the control module  186 . 
       FIG.  27    is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module that includes a plurality of distributed storage and task (DST) execution units (# 1  through #n, where, for example, n is an integer greater than or equal to three). Each of the DST execution units includes a DST client module  34 , a controller  86 , one or more DT (distributed task) execution modules  90 , and memory  88 . 
     In this example, the DSTN module stores, in the memory of the DST execution units, a plurality of DS (dispersed storage) encoded data (e.g.,  1  through n, where n is an integer greater than or equal to two) and stores a plurality of DS encoded task codes (e.g.,  1  through k, where k is an integer greater than or equal to two). The DS encoded data may be encoded in accordance with one or more examples described with reference to  FIGS.  3 - 19    (e.g., organized in slice groupings) or encoded in accordance with one or more examples described with reference to  FIGS.  20 - 26    (e.g., organized in pillar groups). The data that is encoded into the DS encoded data may be of any size and/or of any content. For example, the data may be one or more digital books, a copy of a company&#39;s emails, a large-scale Internet search, a video security file, one or more entertainment video files (e.g., television programs, movies, etc.), data files, and/or any other large amount of data (e.g., greater than a few Terabytes). 
     The tasks that are encoded into the DS encoded task code may be a simple function (e.g., a mathematical function, a logic function, an identify function, a find function, a search engine function, a replace function, etc.), a complex function (e.g., compression, human and/or computer language translation, text-to-voice conversion, voice-to-text conversion, etc.), multiple simple and/or complex functions, one or more algorithms, one or more applications, etc. The tasks may be encoded into the DS encoded task code in accordance with one or more examples described with reference to  FIGS.  3 - 19    (e.g., organized in slice groupings) or encoded in accordance with one or more examples described with reference to  FIGS.  20 - 26    (e.g., organized in pillar groups). 
     In an example of operation, a DST client module of a user device or of a DST processing unit issues a DST request to the DSTN module. The DST request may include a request to retrieve stored data, or a portion thereof, may include a request to store data that is included with the DST request, may include a request to perform one or more tasks on stored data, may include a request to perform one or more tasks on data included with the DST request, etc. In the cases where the DST request includes a request to store data or to retrieve data, the client module and/or the DSTN module processes the request as previously discussed with reference to one or more of  FIGS.  3 - 19    (e.g., slice groupings) and/or  20 - 26  (e.g., pillar groupings). In the case where the DST request includes a request to perform one or more tasks on data included with the DST request, the DST client module and/or the DSTN module process the DST request as previously discussed with reference to one or more of  FIGS.  3 - 19   . 
     In the case where the DST request includes a request to perform one or more tasks on stored data, the DST client module and/or the DSTN module processes the DST request as will be described with reference to one or more of  FIGS.  28 - 39   . In general, the DST client module identifies data and one or more tasks for the DSTN module to execute upon the identified data. The DST request may be for a one-time execution of the task or for an on-going execution of the task. As an example of the latter, as a company generates daily emails, the DST request may be to daily search new emails for inappropriate content and, if found, record the content, the email sender(s), the email recipient(s), email routing information, notify human resources of the identified email, etc. 
       FIG.  28    is a schematic block diagram of an example of a distributed computing system performing tasks on stored data. In this example, two distributed storage and task (DST) client modules  1 - 2  are shown: the first may be associated with a user device and the second may be associated with a DST processing unit or a high priority user device (e.g., high priority clearance user, system administrator, etc.). Each DST client module includes a list of stored data  234  and a list of tasks codes  236 . The list of stored data  234  includes one or more entries of data identifying information, where each entry identifies data stored in the DSTN module  22 . The data identifying information (e.g., data ID) includes one or more of a data file name, a data file directory listing, DSTN addressing information of the data, a data object identifier, etc. The list of tasks  236  includes one or more entries of task code identifying information, when each entry identifies task codes stored in the DSTN module  22 . The task code identifying information (e.g., task ID) includes one or more of a task file name, a task file directory listing, DSTN addressing information of the task, another type of identifier to identify the task, etc. 
     As shown, the list of data  234  and the list of tasks  236  are each smaller in number of entries for the first DST client module than the corresponding lists of the second DST client module. This may occur because the user device associated with the first DST client module has fewer privileges in the distributed computing system than the device associated with the second DST client module. Alternatively, this may occur because the user device associated with the first DST client module serves fewer users than the device associated with the second DST client module and is restricted by the distributed computing system accordingly. As yet another alternative, this may occur through no restraints by the distributed computing system, it just occurred because the operator of the user device associated with the first DST client module has selected fewer data and/or fewer tasks than the operator of the device associated with the second DST client module. 
     In an example of operation, the first DST client module selects one or more data entries  238  and one or more tasks  240  from its respective lists (e.g., selected data ID and selected task ID). The first DST client module sends its selections to a task distribution module  232 . The task distribution module  232  may be within a stand-alone device of the distributed computing system, may be within the user device that contains the first DST client module, or may be within the DSTN module  22 . 
     Regardless of the task distribution module&#39;s location, it generates DST allocation information  242  from the selected task ID  240  and the selected data ID  238 . The DST allocation information  242  includes data partitioning information, task execution information, and/or intermediate result information. The task distribution module  232  sends the DST allocation information  242  to the DSTN module  22 . Note that one or more examples of the DST allocation information will be discussed with reference to one or more of  FIGS.  29 - 39   . 
     The DSTN module  22  interprets the DST allocation information  242  to identify the stored DS encoded data (e.g., DS error encoded data  2 ) and to identify the stored DS error encoded task code (e.g., DS error encoded task code  1 ). In addition, the DSTN module  22  interprets the DST allocation information  242  to determine how the data is to be partitioned and how the task is to be partitioned. The DSTN module  22  also determines whether the selected DS error encoded data  238  needs to be converted from pillar grouping to slice grouping. If so, the DSTN module  22  converts the selected DS error encoded data into slice groupings and stores the slice grouping DS error encoded data by overwriting the pillar grouping DS error encoded data or by storing it in a different location in the memory of the DSTN module  22  (i.e., does not overwrite the pillar grouping DS encoded data). 
     The DSTN module  22  partitions the data and the task as indicated in the DST allocation information  242  and sends the portions to selected DST execution units of the DSTN module  22 . Each of the selected DST execution units performs its partial task(s) on its slice groupings to produce partial results. The DSTN module  22  collects the partial results from the selected DST execution units and provides them, as result information  244 , to the task distribution module. The result information  244  may be the collected partial results, one or more final results as produced by the DSTN module  22  from processing the partial results in accordance with the DST allocation information  242 , or one or more intermediate results as produced by the DSTN module  22  from processing the partial results in accordance with the DST allocation information  242 . 
     The task distribution module  232  receives the result information  244  and provides one or more final results  104  therefrom to the first DST client module. The final result(s)  104  may be result information  244  or a result(s) of the task distribution module&#39;s processing of the result information  244 . 
     In concurrence with processing the selected task of the first DST client module, the distributed computing system may process the selected task(s) of the second DST client module on the selected data(s) of the second DST client module. Alternatively, the distributed computing system may process the second DST client module&#39;s request subsequent to, or preceding, that of the first DST client module. Regardless of the ordering and/or parallel processing of the DST client module requests, the second DST client module provides its selected data  238  and selected task  240  to a task distribution module  232 . If the task distribution module  232  is a separate device of the distributed computing system or within the DSTN module, the task distribution modules  232  coupled to the first and second DST client modules may be the same module. The task distribution module  232  processes the request of the second DST client module in a similar manner as it processed the request of the first DST client module. 
       FIG.  29    is a schematic block diagram of an embodiment of a task distribution module  232  facilitating the example of  FIG.  28   . The task distribution module  232  includes a plurality of tables it uses to generate distributed storage and task (DST) allocation information  242  for selected data and selected tasks received from a DST client module. The tables include data storage information  248 , task storage information  250 , distributed task (DT) execution module information  252 , and task⇔sub-task mapping information  246 . 
     The data storage information table  248  includes a data identification (ID) field  260 , a data size field  262 , an addressing information field  264 , distributed storage (DS) information  266 , and may further include other information regarding the data, how it is stored, and/or how it can be processed. For example, DS encoded data # 1  has a data ID of 1, a data size of AA (e.g., a byte size of a few Terabytes or more), addressing information of Addr_ 1 _AA, and DS parameters of 3/5; SEG_ 1 ; and SLC_ 1 . In this example, the addressing information may be a virtual address corresponding to the virtual address of the first storage word (e.g., one or more bytes) of the data and information on how to calculate the other addresses, may be a range of virtual addresses for the storage words of the data, physical addresses of the first storage word or the storage words of the data, may be a list of slice names of the encoded data slices of the data, etc. The DS parameters may include identity of an error encoding scheme, decode threshold/pillar width (e.g., 3/5 for the first data entry), segment security information (e.g., SEG_ 1 ), per slice security information (e.g., SLC_ 1 ), and/or any other information regarding how the data was encoded into data slices. 
     The task storage information table  250  includes a task identification (ID) field  268 , a task size field  270 , an addressing information field  272 , distributed storage (DS) information  274 , and may further include other information regarding the task, how it is stored, and/or how it can be used to process data. For example, DS encoded task # 2  has a task ID of 2, a task size of XY, addressing information of Addr_ 2 _XY, and DS parameters of 3/5; SEG_ 2 ; and SLC_ 2 . In this example, the addressing information may be a virtual address corresponding to the virtual address of the first storage word (e.g., one or more bytes) of the task and information on how to calculate the other addresses, may be a range of virtual addresses for the storage words of the task, physical addresses of the first storage word or the storage words of the task, may be a list of slices names of the encoded slices of the task code, etc. The DS parameters may include identity of an error encoding scheme, decode threshold/pillar width (e.g., 3/5 for the first data entry), segment security information (e.g., SEG_ 2 ), per slice security information (e.g., SLC_ 2 ), and/or any other information regarding how the task was encoded into encoded task slices. Note that the segment and/or the per-slice security information include a type of encryption (if enabled), a type of compression (if enabled), watermarking information (if enabled), and/or an integrity check scheme (if enabled). 
     The task⇔sub-task mapping information table  246  includes a task field  256  and a sub-task field  258 . The task field  256  identifies a task stored in the memory of a distributed storage and task network (DSTN) module and the corresponding sub-task fields  258  indicates whether the task includes sub-tasks and, if so, how many and if any of the sub-tasks are ordered. In this example, the task⇔sub-task mapping information table  246  includes an entry for each task stored in memory of the DSTN module (e.g., task  1  through task k). In particular, this example indicates that task  1  includes 7 sub-tasks; task  2  does not include sub-tasks, and task k includes r number of sub-tasks (where r is an integer greater than or equal to two). 
     The DT execution module table  252  includes a DST execution unit ID field  276 , a DT execution module ID field  278 , and a DT execution module capabilities field  280 . The DST execution unit ID field  276  includes the identity of DST units in the DSTN module. The DT execution module ID field  278  includes the identity of each DT execution unit in each DST unit. For example, DST unit  1  includes three DT executions modules (e.g.,  1 _ 1 ,  1 _ 2 , and  1 _ 3 ). The DT execution capabilities field  280  includes identity of the capabilities of the corresponding DT execution unit. For example, DT execution module  1 _ 1  includes capabilities X, where X includes one or more of MIPS capabilities, processing resources (e.g., quantity and capability of microprocessors, CPUs, digital signal processors, co-processor, microcontrollers, arithmetic logic circuitry, and/or any other analog and/or digital processing circuitry), availability of the processing resources, memory information (e.g., type, size, availability, etc.), and/or any information germane to executing one or more tasks. 
     From these tables, the task distribution module  232  generates the DST allocation information  242  to indicate where the data is stored, how to partition the data, where the task is stored, how to partition the task, which DT execution units should perform which partial task on which data partitions, where and how intermediate results are to be stored, etc. If multiple tasks are being performed on the same data or different data, the task distribution module factors such information into its generation of the DST allocation information. 
       FIG.  30    is a diagram of a specific example of a distributed computing system performing tasks on stored data as a task flow  318 . In this example, selected data  92  is data  2  and selected tasks are tasks  1 ,  2 , and  3 . Task  1  corresponds to analyzing translation of data from one language to another (e.g., human language or computer language); task  2  corresponds to finding specific words and/or phrases in the data; and task  3  corresponds to finding specific translated words and/or phrases in translated data. 
     In this example, task  1  includes 7 sub-tasks: task  1 _ 1 —identify non-words (non-ordered); task  1 _ 2 —identify unique words (non-ordered); task  1 _ 3 —translate (non-ordered); task  1 _ 4 —translate back (ordered after task  1 _ 3 ); task  1 _ 5 —compare to ID errors (ordered after task  1 - 4 ); task  1 _ 6 —determine non-word translation errors (ordered after task  1 _ 5  and  1 _ 1 ); and task  1 _ 7 —determine correct translations (ordered after  1 _ 5  and  1 _ 2 ). The sub-task further indicates whether they are an ordered task (i.e., are dependent on the outcome of another task) or non-order (i.e., are independent of the outcome of another task). Task  2  does not include sub-tasks and task  3  includes two sub-tasks: task  3 _ 1  translate; and task  3 _ 2  find specific word or phrase in translated data. 
     In general, the three tasks collectively are selected to analyze data for translation accuracies, translation errors, translation anomalies, occurrence of specific words or phrases in the data, and occurrence of specific words or phrases on the translated data. Graphically, the data  92  is translated  306  into translated data  282 ; is analyzed for specific words and/or phrases  300  to produce a list of specific words and/or phrases  286 ; is analyzed for non-words  302  (e.g., not in a reference dictionary) to produce a list of non-words  290 ; and is analyzed for unique words  316  included in the data  92  (i.e., how many different words are included in the data) to produce a list of unique words  298 . Each of these tasks is independent of each other and can therefore be processed in parallel if desired. 
     The translated data  282  is analyzed (e.g., sub-task  3 _ 2 ) for specific translated words and/or phrases  304  to produce a list of specific translated words and/or phrases  288 . The translated data  282  is translated back  308  (e.g., sub-task  1 _ 4 ) into the language of the original data to produce re-translated data  284 . These two tasks are dependent on the translate task (e.g., task  1 _ 3 ) and thus must be ordered after the translation task, which may be in a pipelined ordering or a serial ordering. The re-translated data  284  is then compared  310  with the original data  92  to find words and/or phrases that did not translate (one way and/or the other) properly to produce a list of incorrectly translated words  294 . As such, the comparing task (e.g., sub-task  1 _ 5 )  310  is ordered after the translation  306  and re-translation tasks  308  (e.g., sub-tasks  1 _ 3  and  1 _ 4 ). 
     The list of words incorrectly translated  294  is compared  312  to the list of non-words  290  to identify words that were not properly translated because the words are non-words to produce a list of errors due to non-words  292 . In addition, the list of words incorrectly translated  294  is compared  314  to the list of unique words  298  to identify unique words that were properly translated to produce a list of correctly translated words  296 . The comparison may also identify unique words that were not properly translated to produce a list of unique words that were not properly translated. Note that each list of words (e.g., specific words and/or phrases, non-words, unique words, translated words and/or phrases, etc.,) may include the word and/or phrase, how many times it is used, where in the data it is used, and/or any other information requested regarding a word and/or phrase. 
       FIG.  31    is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module storing data and task codes for the example of  FIG.  30   . As shown, DS encoded data  2  is stored as encoded data slices across the memory (e.g., stored in memories  88 ) of DST execution units  1 - 5 ; the DS encoded task code  1  (of task  1 ) and DS encoded task  3  are stored as encoded task slices across the memory of DST execution units  1 - 5 ; and DS encoded task code  2  (of task  2 ) is stored as encoded task slices across the memory of DST execution units  3 - 7 . As indicated in the data storage information table and the task storage information table of  FIG.  29   , the respective data/task has DS parameters of 3/5 for their decode threshold/pillar width; hence spanning the memory of five DST execution units. 
       FIG.  32    is a diagram of an example of distributed storage and task (DST) allocation information  242  for the example of  FIG.  30   . The DST allocation information  242  includes data partitioning information  320 , task execution information  322 , and intermediate result information  324 . The data partitioning information  320  includes the data identifier (ID), the number of partitions to split the data into, address information for each data partition, and whether the DS encoded data has to be transformed from pillar grouping to slice grouping. The task execution information  322  includes tabular information having a task identification field  326 , a task ordering field  328 , a data partition field ID  330 , and a set of DT execution modules  332  to use for the distributed task processing per data partition. The intermediate result information  324  includes tabular information having a name ID field  334 , an ID of the DST execution unit assigned to process the corresponding intermediate result  336 , a scratch pad storage field  338 , and an intermediate result storage field  340 . 
     Continuing with the example of  FIG.  30   , where tasks  1 - 3  are to be distributedly performed on data  2 , the data partitioning information includes the ID of data  2 . In addition, the task distribution module determines whether the DS encoded data  2  is in the proper format for distributed computing (e.g., was stored as slice groupings). If not, the task distribution module indicates that the DS encoded data  2  format needs to be changed from the pillar grouping format to the slice grouping format, which will be done by the DSTN module. In addition, the task distribution module determines the number of partitions to divide the data into (e.g.,  2 _ 1  through  2 _ z ) and addressing information for each partition. 
     The task distribution module generates an entry in the task execution information section for each sub-task to be performed. For example, task  1 _ 1  (e.g., identify non-words on the data) has no task ordering (i.e., is independent of the results of other sub-tasks), is to be performed on data partitions  2 _ 1  through  2 _ z  by DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1 . For instance, DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  search for non-words in data partitions  2 _ 1  through  2 _ z  to produce task  1 _ 1  intermediate results (R 1 - 1 , which is a list of non-words). Task  1 _ 2  (e.g., identify unique words) has similar task execution information as task  1 _ 1  to produce task  1 _ 2  intermediate results (R 1 - 2 , which is the list of unique words). 
     Task  1 _ 3  (e.g., translate) includes task execution information as being non-ordered (i.e., is independent), having DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  translate data partitions  2 _ 1  through  2 _ 4  and having DT execution modules  1 _ 2 ,  2 _ 2 ,  3 _ 2 ,  4 _ 2 , and  5 _ 2  translate data partitions  2 _ 5  through  2 _ z  to produce task  1 _ 3  intermediate results (R 1 - 3 , which is the translated data). In this example, the data partitions are grouped, where different sets of DT execution modules perform a distributed sub-task (or task) on each data partition group, which allows for further parallel processing. 
     Task  1 _ 4  (e.g., translate back) is ordered after task  1 _ 3  and is to be executed on task  1 _ 3 &#39;s intermediate result (e.g., R 1 - 3 _ 1 ) (e.g., the translated data). DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  are allocated to translate back task  1 _ 3  intermediate result partitions R 1 - 3 _ 1  through R 1 - 3 _ 4  and DT execution modules  1 _ 2 ,  2 _ 2 ,  6 _ 1 ,  7 _ 1 , and  7 _ 2  are allocated to translate back task  1 _ 3  intermediate result partitions R 1 - 3 _ 5  through R 1 - 3 _z to produce task  1 - 4  intermediate results (R 1 - 4 , which is the translated back data). 
     Task  1 _ 5  (e.g., compare data and translated data to identify translation errors) is ordered after task  1 _ 4  and is to be executed on task  1 _ 4 &#39;s intermediate results (R 4 - 1 ) and on the data. DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  are allocated to compare the data partitions ( 2 _ 1  through  2 _ z ) with partitions of task  1 - 4  intermediate results partitions R 1 - 4 _ 1  through R 1 - 4 _ z  to produce task  1 _ 5  intermediate results (R 1 - 5 , which is the list words translated incorrectly). 
     Task  1 _ 6  (e.g., determine non-word translation errors) is ordered after tasks  1 _ 1  and  1 _ 5  and is to be executed on tasks  1 _ 1 &#39;s and  1 _ 5 &#39;s intermediate results (R 1 - 1  and R 1 - 5 ). DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  are allocated to compare the partitions of task  1 _ 1  intermediate results (R 1 - 1 _ 1  through R 1 - 1 _ z ) with partitions of task  1 - 5  intermediate results partitions (R 1 - 5 _ 1  through R 1 - 5 _ z ) to produce task  1 _ 6  intermediate results (R 1 - 6 , which is the list translation errors due to non-words). 
     Task  1 _ 7  (e.g., determine words correctly translated) is ordered after tasks  1 _ 2  and  1 _ 5  and is to be executed on tasks  1 _ 2 &#39;s and  1 _ 5 &#39;s intermediate results (R 1 - 1  and R 1 - 5 ). DT execution modules  1 _ 2 ,  2 _ 2 ,  3 _ 2 ,  4 _ 2 , and  5 _ 2  are allocated to compare the partitions of task  1 _ 2  intermediate results (R 1 - 2 _ 1  through R 1 - 2 _ z ) with partitions of task  1 - 5  intermediate results partitions (R 1 - 5 _ 1  through R 1 - 5 _ z ) to produce task  1 _ 7  intermediate results (R 1 - 7 , which is the list of correctly translated words). 
     Task  2  (e.g., find specific words and/or phrases) has no task ordering (i.e., is independent of the results of other sub-tasks), is to be performed on data partitions  2 _ 1  through  2 _ z  by DT execution modules  3 _ 1 ,  4 _ 1 ,  5 _ 1 ,  6 _ 1 , and  7 _ 1 . For instance, DT execution modules  3 _ 1 ,  4 _ 1 ,  5 _ 1 ,  6 _ 1 , and  7 _ 1  search for specific words and/or phrases in data partitions  2 _ 1  through  2 _ z  to produce task  2  intermediate results (R 2 , which is a list of specific words and/or phrases). 
     Task  3 _ 2  (e.g., find specific translated words and/or phrases) is ordered after task  1 _ 3  (e.g., translate) is to be performed on partitions R 1 - 3 _ 1  through R 1 - 3 _ z  by DT execution modules  1 _ 2 ,  2 _ 2 ,  3 _ 2 ,  4 _ 2 , and  5 _ 2 . For instance, DT execution modules  1 _ 2 ,  2 _ 2 ,  3 _ 2 ,  4 _ 2 , and  5 _ 2  search for specific translated words and/or phrases in the partitions of the translated data (R 1 - 3 _ 1  through R 1 - 3 _ z ) to produce task  3 _ 2  intermediate results (R 3 - 2 , which is a list of specific translated words and/or phrases). 
     For each task, the intermediate result information indicates which DST unit is responsible for overseeing execution of the task and, if needed, processing the partial results generated by the set of allocated DT execution units. In addition, the intermediate result information indicates a scratch pad memory for the task and where the corresponding intermediate results are to be stored. For example, for intermediate result R 1 - 1  (the intermediate result of task  1 _ 1 ), DST unit  1  is responsible for overseeing execution of the task  1 _ 1  and coordinates storage of the intermediate result as encoded intermediate result slices stored in memory of DST execution units  1 - 5 . In general, the scratch pad is for storing non-DS encoded intermediate results and the intermediate result storage is for storing DS encoded intermediate results. 
       FIGS.  33 - 38    are schematic block diagrams of the distributed storage and task network (DSTN) module performing the example of  FIG.  30   . In  FIG.  33   , the DSTN module accesses the data  92  and partitions it into a plurality of partitions  1 - z  in accordance with distributed storage and task network (DST) allocation information. For each data partition, the DSTN identifies a set of its DT (distributed task) execution modules  90  to perform the task (e.g., identify non-words (i.e., not in a reference dictionary) within the data partition) in accordance with the DST allocation information. From data partition to data partition, the set of DT execution modules  90  may be the same, different, or a combination thereof (e.g., some data partitions use the same set while other data partitions use different sets). 
     For the first data partition, the first set of DT execution modules (e.g.,  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  per the DST allocation information of  FIG.  32   ) executes task  1 _ 1  to produce a first partial result  102  of non-words found in the first data partition. The second set of DT execution modules (e.g.,  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  per the DST allocation information of  FIG.  32   ) executes task  1 _ 1  to produce a second partial result  102  of non-words found in the second data partition. The sets of DT execution modules (as per the DST allocation information) perform task  1 _ 1  on the data partitions until the “z” set of DT execution modules performs task  1 _ 1  on the “zth” data partition to produce a “zth” partial result  102  of non-words found in the “zth” data partition. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  1  is assigned to process the first through “zth” partial results to produce the first intermediate result (R 1 - 1 ), which is a list of non-words found in the data. For instance, each set of DT execution modules  90  stores its respective partial result in the scratchpad memory of DST execution unit  1  (which is identified in the DST allocation or may be determined by DST execution unit  1 ). A processing module of DST execution  1  is engaged to aggregate the first through “zth” partial results to produce the first intermediate result (e.g., R 1 _ 1 ). The processing module stores the first intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  1 . 
     DST execution unit  1  engages its DST client module to slice grouping based DS error encode the first intermediate result (e.g., the list of non-words). To begin the encoding, the DST client module determines whether the list of non-words is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions the first intermediate result (R 1 - 1 ) into a plurality of partitions (e.g., R 1 - 1 _ 1  through R 1 - 1 _ m ). If the first intermediate result is not of sufficient size to partition, it is not partitioned. 
     For each partition of the first intermediate result, or for the first intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  1 - 5 ). 
     In  FIG.  34   , the DSTN module is performing task  1 _ 2  (e.g., find unique words) on the data  92 . To begin, the DSTN module accesses the data  92  and partitions it into a plurality of partitions  1 - z  in accordance with the DST allocation information or it may use the data partitions of task  1 _ 1  if the partitioning is the same. For each data partition, the DSTN identifies a set of its DT execution modules to perform task  1 _ 2  in accordance with the DST allocation information. From data partition to data partition, the set of DT execution modules may be the same, different, or a combination thereof. For the data partitions, the allocated set of DT execution modules executes task  1 _ 2  to produce a partial results (e.g., 1 st  through “zth”) of unique words found in the data partitions. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  1  is assigned to process the first through “zth” partial results  102  of task  1 _ 2  to produce the second intermediate result (R 1 - 2 ), which is a list of unique words found in the data  92 . The processing module of DST execution  1  is engaged to aggregate the first through “zth” partial results of unique words to produce the second intermediate result. The processing module stores the second intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  1 . 
     DST execution unit  1  engages its DST client module to slice grouping based DS error encode the second intermediate result (e.g., the list of non-words). To begin the encoding, the DST client module determines whether the list of unique words is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions the second intermediate result (R 1 - 2 ) into a plurality of partitions (e.g., R 1 - 2 _ 1  through R 1 - 2 _ m ). If the second intermediate result is not of sufficient size to partition, it is not partitioned. 
     For each partition of the second intermediate result, or for the second intermediate results, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  1 - 5 ). 
     In  FIG.  35   , the DSTN module is performing task  1 _ 3  (e.g., translate) on the data  92 . To begin, the DSTN module accesses the data  92  and partitions it into a plurality of partitions  1 - z  in accordance with the DST allocation information or it may use the data partitions of task  1 _ 1  if the partitioning is the same. For each data partition, the DSTN identifies a set of its DT execution modules to perform task  1 _ 3  in accordance with the DST allocation information (e.g., DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  translate data partitions  2 _ 1  through  2 _ 4  and DT execution modules  1 _ 2 ,  2 _ 2 ,  3 _ 2 ,  4 _ 2 , and  5 _ 2  translate data partitions  2 _ 5  through  2 _z). For the data partitions, the allocated set of DT execution modules  90  executes task  1 _ 3  to produce partial results  102  (e.g., 1 st  through “zth”) of translated data. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  2  is assigned to process the first through “zth” partial results of task  1 _ 3  to produce the third intermediate result (R 1 - 3 ), which is translated data. The processing module of DST execution  2  is engaged to aggregate the first through “zth” partial results of translated data to produce the third intermediate result. The processing module stores the third intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  2 . 
     DST execution unit  2  engages its DST client module to slice grouping based DS error encode the third intermediate result (e.g., translated data). To begin the encoding, the DST client module partitions the third intermediate result (R 1 - 3 ) into a plurality of partitions (e.g., R 1 - 3 _ 1  through R 1 - 3 _ y ). For each partition of the third intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  2 - 6  per the DST allocation information). 
     As is further shown in  FIG.  35   , the DSTN module is performing task  1 _ 4  (e.g., retranslate) on the translated data of the third intermediate result. To begin, the DSTN module accesses the translated data (from the scratchpad memory or from the intermediate result memory and decodes it) and partitions it into a plurality of partitions in accordance with the DST allocation information. For each partition of the third intermediate result, the DSTN identifies a set of its DT execution modules  90  to perform task  1 _ 4  in accordance with the DST allocation information (e.g., DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1  are allocated to translate back partitions R 1 - 3 _ 1  through R 1 - 3 _ 4  and DT execution modules  1 _ 2 ,  2 _ 2 ,  6 _ 1 ,  7 _ 1 , and  7 _ 2  are allocated to translate back partitions R 1 - 3 _ 5  through R 1 - 3 _ z ). For the partitions, the allocated set of DT execution modules executes task  1 _ 4  to produce partial results  102  (e.g., 1 st  through “zth”) of re-translated data. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  3  is assigned to process the first through “zth” partial results of task  1 _ 4  to produce the fourth intermediate result (R 1 - 4 ), which is retranslated data. The processing module of DST execution  3  is engaged to aggregate the first through “zth” partial results of retranslated data to produce the fourth intermediate result. The processing module stores the fourth intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  3 . 
     DST execution unit  3  engages its DST client module to slice grouping based DS error encode the fourth intermediate result (e.g., retranslated data). To begin the encoding, the DST client module partitions the fourth intermediate result (R 1 - 4 ) into a plurality of partitions (e.g., R 1 - 4 _ 1  through R 1 - 4 _ z ). For each partition of the fourth intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  3 - 7  per the DST allocation information). 
     In  FIG.  36   , a distributed storage and task network (DSTN) module is performing task  1 _ 5  (e.g., compare) on data  92  and retranslated data of  FIG.  35   . To begin, the DSTN module accesses the data  92  and partitions it into a plurality of partitions in accordance with the DST allocation information or it may use the data partitions of task  1 _ 1  if the partitioning is the same. The DSTN module also accesses the retranslated data from the scratchpad memory, or from the intermediate result memory and decodes it, and partitions it into a plurality of partitions in accordance with the DST allocation information. The number of partitions of the retranslated data corresponds to the number of partitions of the data. 
     For each pair of partitions (e.g., data partition  1  and retranslated data partition  1 ), the DSTN identifies a set of its DT execution modules  90  to perform task  1 _ 5  in accordance with the DST allocation information (e.g., DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1 ). For each pair of partitions, the allocated set of DT execution modules executes task  1 _ 5  to produce partial results  102  (e.g., 1 st  through “zth”) of a list of incorrectly translated words and/or phrases. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  1  is assigned to process the first through “zth” partial results of task  1 _ 5  to produce the fifth intermediate result (R 1 - 5 ), which is the list of incorrectly translated words and/or phrases. In particular, the processing module of DST execution  1  is engaged to aggregate the first through “zth” partial results of the list of incorrectly translated words and/or phrases to produce the fifth intermediate result. The processing module stores the fifth intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  1 . 
     DST execution unit  1  engages its DST client module to slice grouping based DS error encode the fifth intermediate result. To begin the encoding, the DST client module partitions the fifth intermediate result (R 1 - 5 ) into a plurality of partitions (e.g., Rt- 5 _ 1  through R 1 - 5 _ z ). For each partition of the fifth intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  1 - 5  per the DST allocation information). 
     As is further shown in  FIG.  36   , the DSTN module is performing task  1 _ 6  (e.g., translation errors due to non-words) on the list of incorrectly translated words and/or phrases (e.g., the fifth intermediate result R 1 - 5 ) and the list of non-words (e.g., the first intermediate result R 1 - 1 ). To begin, the DSTN module accesses the lists and partitions them into a corresponding number of partitions. 
     For each pair of partitions (e.g., partition Rt- 1 _ 1  and partition R 1 - 5 _ 1 ), the DSTN identifies a set of its DT execution modules  90  to perform task  1 _ 6  in accordance with the DST allocation information (e.g., DT execution modules  1 _ 1 ,  2 _ 1 ,  3 _ 1 ,  4 _ 1 , and  5 _ 1 ). For each pair of partitions, the allocated set of DT execution modules executes task  1 _ 6  to produce partial results  102  (e.g., 1 st  through “zth”) of a list of incorrectly translated words and/or phrases due to non-words. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  2  is assigned to process the first through “zth” partial results of task  1 _ 6  to produce the sixth intermediate result (R 1 - 6 ), which is the list of incorrectly translated words and/or phrases due to non-words. In particular, the processing module of DST execution  2  is engaged to aggregate the first through “zth” partial results of the list of incorrectly translated words and/or phrases due to non-words to produce the sixth intermediate result. The processing module stores the sixth intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  2 . 
     DST execution unit  2  engages its DST client module to slice grouping based DS error encode the sixth intermediate result. To begin the encoding, the DST client module partitions the sixth intermediate result (R 1 - 6 ) into a plurality of partitions (e.g., Rt- 6 _ 1  through R 1 - 6 _ z ). For each partition of the sixth intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  2 - 6  per the DST allocation information). 
     As is still further shown in  FIG.  36   , the DSTN module is performing task  1 _ 7  (e.g., correctly translated words and/or phrases) on the list of incorrectly translated words and/or phrases (e.g., the fifth intermediate result R 1 - 5 ) and the list of unique words (e.g., the second intermediate result R 1 - 2 ). To begin, the DSTN module accesses the lists and partitions them into a corresponding number of partitions. 
     For each pair of partitions (e.g., partition R 1 - 2 _ 1  and partition R 1 - 5 _ 1 ), the DSTN identifies a set of its DT execution modules  90  to perform task  1 _ 7  in accordance with the DST allocation information (e.g., DT execution modules  1 _ 2 ,  2 _ 2 ,  3 _ 2 ,  4 _ 2 , and  5 _ 2 ). For each pair of partitions, the allocated set of DT execution modules executes task  1 _ 7  to produce partial results  102  (e.g., 1 st  through “zth”) of a list of correctly translated words and/or phrases. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  3  is assigned to process the first through “zth” partial results of task  1 _ 7  to produce the seventh intermediate result (R 1 - 7 ), which is the list of correctly translated words and/or phrases. In particular, the processing module of DST execution  3  is engaged to aggregate the first through “zth” partial results of the list of correctly translated words and/or phrases to produce the seventh intermediate result. The processing module stores the seventh intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  3 . 
     DST execution unit  3  engages its DST client module to slice grouping based DS error encode the seventh intermediate result. To begin the encoding, the DST client module partitions the seventh intermediate result (R 1 - 7 ) into a plurality of partitions (e.g., R 1 - 7 _ 1  through R 1 - 7 _ z ). For each partition of the seventh intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  3 - 7  per the DST allocation information). 
     In  FIG.  37   , the distributed storage and task network (DSTN) module is performing task  2  (e.g., find specific words and/or phrases) on the data  92 . To begin, the DSTN module accesses the data and partitions it into a plurality of partitions  1 - z  in accordance with the DST allocation information or it may use the data partitions of task  1 _ 1  if the partitioning is the same. For each data partition, the DSTN identifies a set of its DT execution modules  90  to perform task  2  in accordance with the DST allocation information. From data partition to data partition, the set of DT execution modules may be the same, different, or a combination thereof. For the data partitions, the allocated set of DT execution modules executes task  2  to produce partial results  102  (e.g., 1 st  through “zth”) of specific words and/or phrases found in the data partitions. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  7  is assigned to process the first through “zth” partial results of task  2  to produce task  2  intermediate result (R 2 ), which is a list of specific words and/or phrases found in the data. The processing module of DST execution  7  is engaged to aggregate the first through “zth” partial results of specific words and/or phrases to produce the task  2  intermediate result. The processing module stores the task  2  intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  7 . 
     DST execution unit  7  engages its DST client module to slice grouping based DS error encode the task  2  intermediate result. To begin the encoding, the DST client module determines whether the list of specific words and/or phrases is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions the task  2  intermediate result (R 2 ) into a plurality of partitions (e.g., R 2 _ 1  through R 2 _ m ). If the task  2  intermediate result is not of sufficient size to partition, it is not partitioned. 
     For each partition of the task  2  intermediate result, or for the task  2  intermediate results, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  1 - 4 , and  7 ). 
     In  FIG.  38   , the distributed storage and task network (DSTN) module is performing task  3  (e.g., find specific translated words and/or phrases) on the translated data (R 1 - 3 ). To begin, the DSTN module accesses the translated data (from the scratchpad memory or from the intermediate result memory and decodes it) and partitions it into a plurality of partitions in accordance with the DST allocation information. For each partition, the DSTN identifies a set of its DT execution modules to perform task  3  in accordance with the DST allocation information. From partition to partition, the set of DT execution modules may be the same, different, or a combination thereof. For the partitions, the allocated set of DT execution modules  90  executes task  3  to produce partial results  102  (e.g., 1 st  through “zth”) of specific translated words and/or phrases found in the data partitions. 
     As indicated in the DST allocation information of  FIG.  32   , DST execution unit  5  is assigned to process the first through “zth” partial results of task  3  to produce task  3  intermediate result (R 3 ), which is a list of specific translated words and/or phrases found in the translated data. In particular, the processing module of DST execution  5  is engaged to aggregate the first through “zth” partial results of specific translated words and/or phrases to produce the task  3  intermediate result. The processing module stores the task  3  intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory of DST execution unit  7 . 
     DST execution unit  5  engages its DST client module to slice grouping based DS error encode the task  3  intermediate result. To begin the encoding, the DST client module determines whether the list of specific translated words and/or phrases is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions the task  3  intermediate result (R 3 ) into a plurality of partitions (e.g., R 3 _ 1  through R 3 _ m ). If the task  3  intermediate result is not of sufficient size to partition, it is not partitioned. 
     For each partition of the task  3  intermediate result, or for the task  3  intermediate results, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters of data  2 , which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units  1 - 4 ,  5 , and  7 ). 
       FIG.  39    is a diagram of an example of combining result information into final results  104  for the example of  FIG.  30   . In this example, the result information includes the list of specific words and/or phrases found in the data (task  2  intermediate result), the list of specific translated words and/or phrases found in the data (task  3  intermediate result), the list of non-words found in the data (task  1  first intermediate result R 1 - 1 ), the list of unique words found in the data (task  1  second intermediate result R 1 - 2 ), the list of translation errors due to non-words (task  1  sixth intermediate result R 1 - 6 ), and the list of correctly translated words and/or phrases (task  1  seventh intermediate result R 1 - 7 ). The task distribution module provides the result information to the requesting DST client module as the results  104 . 
       FIGS.  40 A-B  are schematic block diagrams of an embodiment of a dispersed storage network (DSN) illustrating an example of executing tasks. The DSN includes distributed storage and task (DST) client modules  1 -M, the network  24  of  FIG.  1   , and a DST execution unit set  350 . Each DST client module may be implemented utilizing the DST client module  34  of  FIG.  1   . Each DST client module includes the outbound dispersed storage (DS) processing module  80  and the inbound DS processing module  82  of  FIG.  3   . The outbound DS processing module  80  includes the distributed task control module  118  of  FIG.  4    and the DS error encoding  112  of  FIG.  4   . The inbound DS processing module  82  includes the distributed task control module  188  and the DS error decoding  182  of  FIG.  13   . The DST execution unit set  350  includes a set of DST execution units  1 - n . Each DST execution unit may be implemented using the DST execution unit  36  of  FIG.  1   . 
       FIG.  40 A  illustrates initial steps of the executing of the tasks. In an example of operation, the distributed task control module  118  of the DST client module  1  obtains a task  352 . The obtaining includes at least one of receiving and generating. The task  352  includes one or more of a task description, a task identifier, subtask descriptions, and subtask identifiers. The task description may include one or more of read data, process data, perform a selection, perform an identification, write data, retrieve data, manipulate data, store data, etc. The subtask description may include one or more of identifying a storage address, generate a retrieval request, send a retrieval request, receive retrieval responses, decode the retrieval responses, etc., when an associated task of the subtask includes the read data task. 
     Having obtained the task  352 , the distributed task control module  118  obtains a task object  354 . The obtaining includes retrieving an existing task object, retrieving an entry of a dispersed hierarchical index, and generating a new task object as the obtained task object. Having obtained the task object  354 , the distributed task control module  118  generates a task entry  356 - 358  etc., for the task object  354  based on the task. Each task object  354  includes one or more task entries. Each task entry  356  etc., includes a task, a rule set, and status. The rule set includes one or more of a precondition for task execution, a condition to maintain task execution, and one or more condition parameters. For example, the rule set indicates to execute the task after a certain time frame has elapsed. The status may include an execution owner identifier (ID) and a state of processing of the task. The state of the processing of the task includes at least one of a pending execution state, an active execution state, and an execution complete state. 
     The generating of the task entry includes generating the task entry in accordance with a task entry generation approach based on the task. As a specific example of generating the task entry, the distributed task control module  118  generates the task entry to indicate task  203 , rule set  2 , and the status to include the pending execution state (e.g., state 0) when the task entry generation approach indicates to utilize rule set  2  for task  203 . The distributed task control module  118  adds the generated task entry  356 ,  358 , etc., to the obtained task object  354  to produce the task object  354  for further processing. 
     The DS error encoding  112  dispersed storage error encodes the task object  354  to produce task slices  360 , where the task slices  360  includes a set of task slices  1 - n . Having produced the task slices  360 , the outbound DS processing module  80  sends, via the network  24 , the task slices  360  to the DST execution unit set  350  such that each of the DST execution units  1 - n  store a corresponding task slice of the set of task slices  1 - n . For example, the task slices are stored as a new object in the DST execution unit set. As another example, the task slices  360  are stored as a new entry within an index node of a dispersed hierarchical index structure stored in the DST execution unit set  350 . Having stored the task slices  360 , the task has been queued. 
       FIG.  40 B  illustrates further steps of the executing of the tasks. Having one or more tasks queued in the DST execution unit set  350 , the inbound DS processing module  82  of DST client module  2  retrieves at least a decode threshold number of task slices  360  from the DST execution unit set  350 . For example, the DS error decoding  182  issues a read threshold number of read slice requests to a read threshold number of the DST execution units  1 - n  to recover at least one of the data object associated with the task object and the index node of the dispersed hierarchical index that includes the index node entry associated with the task object. Having issued the read threshold number of read slice requests, the DS error decoding  182  receives at least a decode threshold number of read slice responses that includes the at least a decode threshold number of task slices  360 . 
     Having received the at least a decode threshold number of task slices  360 , the DS error decoding  182  dispersed storage error decodes the at least a decode threshold number of task slices  360  to produce a recovered task object  362 . The distributed task control module  188  determines whether to execute a task of the recovered task object. For example, the distributed task control module  188  selects a task entry of the recovered task object  362 , interprets the status to determine that the task is pending execution, analyzes the rule set to determine that the rule set has been satisfied begin execution, and that the DST client module  2  has sufficient available resources to execute the task of the task entry. 
     When the distributed task control module  188  determines to execute the task, the distributed task control module  188  initiates obtaining ownership of the task. For example, the distributed task control module  118  updates the status of the task entry to indicate ownership by DST client module  2  to produce an updated task object  370 . The DS error encoding  112  dispersed storage error encodes the updated task object  370  to produce a set of updated task slices  376 . The outbound DS processing module  80  issues, via the network  24 , a set of write slice requests that includes the set of updated task slices  376  to the DST execution units  1 - n  for storage of the set of updated task slices  376 , and receives, via the network  24 , at least a write threshold number of favorable write slice responses confirming ownership by the DST client module  1  of the task and storage of the updated task object in the DST execution unit set. 
     When receiving confirmation of ownership, the distributed task control module  188  facilitates initiation of execution of the task. The initiation of the execution of the task includes determining whether to utilize subtasks  368 . For example, the distributed task control module  188  determines to utilize the subtasks when the DST client module  2  does not have enough resources to fully execute the task. As another example, the distributed task control module  188  determines to utilize the subtasks when the rule set of the task entry indicates to utilize sub-tasks. 
     When utilizing the subtasks  368 , the distributed task control module  188  generates one or more subtasks  368  in accordance with the rule set and based on the task. The distributed task control module  118  further updates the updated task object  370  to produce a further updated task object  370  where the task entry  374  of the further updated task object  370  includes the sub-tasks. The DS error encoding  112  dispersed storage error encodes the further updated task object to produce further updated task slices  376 . The outbound DS processing module  80  facilitates storage of the further updated task slices  376  in the set of DST execution units  1 - n . The above process may continue where yet another DST client module accesses the further updated task object to retrieve a subtask, obtain ownership of the subtasks, execute a selected subtask and/or create further subtasks from the selected sub-task. 
       FIG.  40 C  is a flowchart illustrating an example of executing tasks. The method begins or continues at step  380  where a first module (e.g., of a first distributed storage and task (DST) client module) obtains a task object. For example, the first module searches a dispersed hierarchical index to identify an entry that includes the task object. The method continues at step  382  where the first module generates a task entry based on a task (e.g., a new task to be queued for subsequent execution). The method continues at step  384  where the first module updates the task object to include the task entry. The method continues at step  386  where the first module facilitates storing the task object in a dispersed storage network (DSN). For example, the first module dispersed storage error encodes the task object to produce a set of task slices for storage in an entry of the dispersed hierarchical index in a set of storage units of the DSN. 
     The method continues at step  388  where a second module (e.g., of a second distributed storage and task (DST) client module) recovers the task object from the DSN. For example, the second module searches the dispersed hierarchical index to identify the entry that includes the task object. The method continues at step  390  where the second module determines whether to execute the task of the task entry. For example, the processing module indicates to execute the task when status of the task indicates that ownership no longer exists, a rule set has been satisfied, and required resources are available. 
     When executing the task, the method continues at step  392  where the second module initiates obtaining ownership of the execution of the task. For example, the second module updates the status of the task entry to indicate ownership by the second module, updates the task object to include the updated task entry, dispersed storage error encodes the updated task object to produce a set of updated task slices, and issues a set of write slice requests to the set of storage units of the DSN, where the set of write slice requests includes the set of updated task slices. 
     When ownership is confirmed, the method continues at step  394  where the second module facilitates initiation of the execution of the task. The second module indicates that the ownership is confirmed when receiving at least a write threshold number of favorable write slice responses from the set of storage units with regards to the storage of the set of updated task slices. As an example of execution of the task, the second module determines whether to utilize sub-tasks. For instance, the second module indicates to utilize subtasks when available resources of the second module compare unfavorably (e.g., not enough) to required resources to fulfill execution of the task. As another instance, the second module executes the task when the available resources of the second module compare favorably to the required resources to fulfill the execution of the task. 
     When utilizing subtasks for the facilitation, the method continues at step  396  where the second module generates one or more subtasks in accordance with a subtask list and a rule set based on one or more of the subtask and available resources. For example, the second module generates two subtasks for execution by the second module and one more subtask for execution by another module. The method continues at step  398  where the second module updates the task object to include at least some of the one or more subtasks. For example, the second module generates a subtask entry for each subtask to be included in the task object. The method continues at step  400  where the second module stores the updated task object in the set of storage units of the DSN. For example, the second module encodes the updated task object to produce updated task slices and stores the updated task slices in the set of storage units. 
       FIGS.  41 A , G, and H is a schematic block diagram of another embodiment of a dispersed storage network (DSN) that includes the distributed storage and task (DST) client module  34  of  FIG.  1   , the network  24  of  FIG.  1   , and a DST execution (EX) unit set  402 . The DST client module  34  includes the outbound dispersed storage (DS) processing module  80  and the inbound DS processing module  82  of  FIG.  3   . The outbound DS processing module  80  includes the data partitioning  110  of  FIG.  4    and the DS error encoding  112  of  FIG.  4   . The inbound DS processing module  82  includes the data de-partitioning  184  and the DS error decoding  182  of  FIG.  13   . Each DST execution unit set  402  includes a set of DST EX units  1 - n . The set of DST EX units  1 - n  includes first set of DST execution units  1 - k  and a second set of DST EX units k+1 through n. Each DST execution unit may be implemented utilizing the DST execution unit  36  of  FIG.  1   . 
     The DSN functions to access stored data in the DSN. The accessing includes storing data in the DST execution unit set  402  as a set of encoded data slices utilizing a data concatenation approach. The accessing further includes retrieving the stored data from the DST execution unit set  402  in accordance with the data concatenation approach. The data may include a plurality of small data objects, where a size of each of a substantial number of the data objects is less than a size threshold level. Such a size threshold level may include a size of desired encoded data slice for storage in one of the DST execution units. Hereafter, the plurality of small data objects may be referred to interchangeably as a plurality of independent data objects. The plurality of independent data objects may be associated with a common trait. The common traits includes one or more of a size that is less than the size threshold level, a common subject matter, a common data types, a common time of arrival, a common data owner, a common date of creation, a common generation source, a common expected retrieving entity, etc. 
       FIG.  41 A  illustrates an example of operation of the storing of the data to produce the stored data, where the outbound DS processing module  80  receives the small data objects  404  for storage. Having received the plurality small data objects  404 , the outbound DS processing module  80  determines whether to utilize the data concatenation approach. The determining may be based on one or more of a predetermination, detecting that at least a decode threshold number of the small data objects have been received, receiving a message to concatenate the independent data objects, where the message is one of a user input message to group data objects having the common trait and a system message based on dispersed storage network conditions (e.g., the message indicating that an overload condition may exist, and detecting that a number of input/output operations of the DST client module  34  is greater than an input/output operations threshold level (e.g., inferring that the overload condition may exist). 
     When using the data concatenation approach, the data partitioning  110  concatenates the plurality of independent data objects  404  into a concatenated data object  406 , where the concatenating is based on a parameter of a dispersed storage error encoding function that indicates a number of data-based encoded data slices (e.g., a decode threshold number) resulting from performing the dispersed storage error encoding function. As a specific example, the data partitioning  110  identifies data objects  404  having the common trait and establishes the plurality of independent data objects from the data objects having the common trait. For instance, the data partitioning  110  selects a decode threshold number (e.g., k) of small data objects  404  to produce the plurality of independent data objects for concatenation. 
     Having selected the plurality of independent data objects for concatenation, the data partitioning  110  maps the independent data objects into “k” rows to produce the concatenated data object  406 . As a specific example of the mapping, the data partitioning  110  maps independent data objects into the “k” rows to produce the concatenated data object, where the “k” rows corresponds to the number of data-based encoded data slices resulting from performing the dispersed storage error encoding function and where an independent data object of the plurality of independent data objects is mapped to more than one row of the “k” rows (e.g., an independent data object wraps from one row to an adjacent row). 
     As another specific example of the mapping, the data partitioning  110  maps the independent data objects such that the “k” rows corresponds to a number of data-based encoded data slices (e.g., the decode threshold number) resulting from performing the dispersed storage error encoding function and where the one or more independent data objects is mapped to a single row of the “k” rows. As a specific example of generating the concatenated object  406  where the one or more independent data objects are mapped to the single row, the data partitioning  110  generates the concatenated object  406  to include small data object  1  in a first row, small data object  2  in a second row, small data object  3  in a third row, through small data object k in a “kth” row. Having mapped one small data object to each row, the data partitioning  110  pads the single row of the “k” rows when a combined size of the one or more independent data objects is less than a row size (e.g., a size of a desired encoded data slice). For instance, the data partitioning  110  pads the first row such that a size of the small data object  1  plus a size of a padding  1  equals the row size, pads the second row such that a size of the small data object  2  plus a size of a padding  2  equals the row size, etc. Another specific example of generating the concatenated object  406  where the one or more independent data objects are mapped to the single row is discussed in greater detail with reference to  FIG.  41 F . 
     Having produced the concatenated object  406 , the outbound DS processing module  80  performs the dispersed storage error coding function on the concatenated data object  406  to produce the set of encoded data slices that includes a set of data-based encoded data slices  1 - k    408  and a set of redundancy-based encoded data slices  410  (e.g., error coding slices). One or more independent data objects of the plurality of independent data objects is recoverable from a corresponding data-based encoded data slice of the set of encoded data slices or from a decode threshold number of encoded data slices, where the decode threshold number of encoded data slices includes one or more data-based encoded data slices of the set of data-based encoded data slices and one or more redundancy-based encoded data slices of the set of redundancy-based encoded data slices. 
     As a specific example, the DS error encoding  112  converts the concatenated data object  406  into a data matrix, generates a coded matrix based on the data matrix and an encoding matrix, generates the set of data-based encoded data slices  408  (e.g., data-based encoded data slices  1 - 3 ) from a first portion of the coded matrix that corresponds to a first portion of the encoding matrix, and generates the set of redundancy-based encoded data slices  410  (e.g., redundancy-based encoded data slices or error coding slices k+1 and n) from a second portion of the coded matrix that corresponds to a second portion of the encoding matrix. The generating of the encoded data slices is discussed in greater detail with reference to  FIGS.  41 B-E . 
     Having generated the set of encoded data slices, the DS error encoding  112  outputs, via the network  24 , the set of data-based encoded data slices to the first set of DST execution units (e.g., DST EX units  1 - k ) for storage and outputs, via the network  24  the set of redundancy-based encoded data slices to the second set of DST execution units (e.g., DST EX units k+1 through n) for storage. For example, the DS error encoding  112  sends, via the network  24 , encoded data slices  1 - 3  to DST execution units  1 - 3  for storage and sends, via the network  24 , error coded data slices  4  and  5  to DST execution units  4  and  5  for storage when k=3 and n=5. 
     Having output the set of encoded data slices, the outbound DS processing module  80  associates identifiers of the small data objects with corresponding identifiers (e.g., slice names, source name, DSN address) of each of the set of data-based encoded data slices. For example, the outbound DS processing module  80  updates one or more of a DSN directory and a dispersed hierarchical index to associate received identifiers of the small data objects with the identifiers of the corresponding set of data-based encoded data slices. 
       FIG.  41 B  is a diagram illustrating an example of encoding a concatenated object into a plurality of data blocks D 1 -Dn. The set of data blocks provides a representation of the concatenated object  406  for example, the concatenated object  406  is divided into n equal portions to form data blocks D 1 -Dn. As another example, the concatenated data object  406  is divided into as many portions as required when a fixed data portion size is utilized. 
       FIG.  41 C  is a diagram illustrating an example of matrix multiplication of an encoding matrix (E) and a data matrix (D) using a dispersed storage error coding function to produce a coded matrix (C). The encoding function may utilize a variety of encoding approaches to facilitate dispersed storage error encoding of data. The encoding function includes, but is not limited to, at least one of Reed Solomon encoding, an information dispersal algorithm, on-line codes, forward error correction, erasure codes, convolution encoding, Trellis encoding, Golay, Multidimensional parity, Hamming, Bose Ray Chauduri Hocquenghem (BCH), and/or Cauchy-Reed-Solomon. In an example of a Reed Solomon encoding function, the matrix multiplication is utilized to encode a data segment or concatenated object  406  to produce a set of encoded data blocks  412  as a representation of the data segment or concatenated object  406 . The Reed Solomon encoding function is associated with an error coding number (e.g., pillar width, number of slices per set) and a decode threshold number. As a specific example, the encoding matrix includes the error coding number of Y rows and the decode threshold number of X columns. Accordingly, the encoding matrix includes Y rows of X coefficients. The set of data blocks of the data segment or concatenated object  406  is arranged into the data matrix having X rows of Z number of data words (e.g., X*Z=number of data blocks). The data matrix is matrix multiplied by the encoding matrix to produce the coded matrix, which includes Y rows of Z number of encoded values (e.g., encoded data blocks  412 ). 
       FIG.  41 D  is a diagram illustrating another example of matrix multiplication of an encoding matrix (E) and a data matrix (D) using a dispersed storage error coding function to produce a coded matrix (C), where a set of encoded data slices are produced from the coded matrix. In an example of operation of using a Reed Solomon encoding function, the concatenated object  406  of  FIG.  41 B  is converted into data blocks (e.g., D 1 -D 12 ) of a portion of the data matrix (e.g., any number of bytes per block). Next, the encoding matrix is matrix multiplied by the data matrix to produce the coded matrix, where the coded matrix includes encoded data blocks  412 . As a specific example, the dispersed storage error encoding utilizes an error coding number of five and a decode threshold number of three. The encoding matrix (E) includes five rows of three coefficients (e.g., a-o). The data segment is divided into data blocks D 1 - 12 , which are arranged into the portion of the data matrix (D) having 3 rows of 4 data blocks when the number of data blocks is 12. The number of rows of the data matrix matches the number of columns of the encoding matrix (e.g., the decode threshold number). The number of columns of the data matrix increases as the number of data blocks of the data segment increases. The data matrix is matrix multiplied by the encoding matrix to produce the coded matrix, which includes 5 rows of 4 encoded data blocks (e.g., X 11 -X 14 , X 21 -X 24 , X 31 -X 34 , X 41 -X 44 , and X 51 -X 54 ). The number of rows of the coded matrix matches the number of rows of the encoding matrix (e.g., the error coding number). For instance, X 11 =aD 1 +bD 5 +cD 9 ; X 12 =aD 2 +bD 6 +cD 10 ; X 21 =dD 1 +eD 5 +fD 9 ; X 31 =gD 1 +hD 5 +iD 9 ; X 34 =gD 4 +hD 8 +iD 12 ; and X 54 =mD 4 +nD 8 +oD 12 . 
     One or more encoded data blocks  412  from each row of the coded matrix are selected to form a corresponding encoded data slice of the set of encoded data slices. Accordingly, an error coding number of encoded data slices are produced from the coded matrix. For example, coded values X 11 -X 14  are selected to produce an encoded data slice  1 , coded values X 21 -X 24  are selected to produce an encoded data slice  2 , coded values X 31 -X 34  are selected to produce an encoded data slice  3 , coded values X 41 -X 44  are selected to produce an encoded data slice  4 , and coded values X 51 -X 54  are selected to produce an encoded data slice  5 . The data matrix (e.g., the concatenated object  406 ) may be recovered (e.g., to produce a recovered data segment) when any decode threshold number of corruption-free error coded data slices are available of the set of error coded data slices. Alternatively, the recovered concatenated object may be produced when a decode threshold number of encoded data blocks for each column of the coded matrix are available. 
       FIG.  41 E  is a diagram illustrating another example of matrix multiplication of an encoding matrix (E) and a data matrix (D) using a dispersed storage error coding function to produce a coded matrix (C), where a decode threshold number of rows of the encoding matrix includes a unity matrix. Accordingly, matrix multiplying the encoding matrix with the data matrix produces the coded matrix where the encoded data blocks  412  include a set of encoded data slices. 
     The set of encoded data slices includes a set of data-based encoded data slices  1 - 3  and a set of redundancy-based encoded data slices  4 - 5  when the error coding number is five (e.g., n=5) and the decode threshold number is three (e.g., k=3). For example, matrix multiplying a first portion of the encoding matrix that includes the unity matrix by the data matrix produces a first portion of the coded matrix that includes the set of data-based encoded data slices  1 - 3  and matrix multiplying a second portion of the encoding matrix (e.g., remaining rows after the unity matrix) by the data matrix produces a second portion of the coded matrix that includes the set of redundancy-based encoded data slices  4 - 5 . For instance, coded matrix values X 11 -X 14  includes data blocks D 1 -D 4  forming data-based encoded data slice  1 , coded matrix values X 21 -X 24  includes data blocks D 5 -D 8  forming data-based encoded data slice  2 , and coded matrix values X 31 -X 34  includes data blocks D 9 -D 12  forming data-based encoded data slice  3 . As another instance, coded matrix values X 41 -X 44  forms redundancy-based encoded data slice  4 , and coded matrix values X 51 -X 54  forms redundancy-based encoded data slice  5 . 
       FIG.  41 F  is a diagram illustrating an example of mapping data objects to the concatenated object  406  where the independent data objects are mapped such that the “k” rows corresponds to a number of data-based encoded data slices (e.g., the decode threshold number) resulting from performing the dispersed storage error encoding function and where the one or more independent data objects is mapped to a single row of the “k” rows. As a specific example of generating the concatenated object  406  where the one or more independent data objects are mapped to the single row, the data partitioning  110  generates the concatenated object  406  to include small data objects  1  and  2  in a first row, small data object  3  in a second row, small data object  4  in a third row, through small data object k+1 in a “kth” row. Having mapped the one or more small data objects to each row, padding is added to each row of the “k” rows when a combined size of the one or more independent data objects is less than a row size (e.g., a size of a desired encoded data slice). For instance, the first row is padded such that a size of the small data object  1  and  2  plus a size of a padding  1  equals the row size, the second row is padded such that a size of the small data object  3  plus a size of a padding  2  equals the row size, etc. 
       FIG.  41 G  illustrates an example of retrieving the stored data to reproduce the data in accordance with the data concatenation approach where the inbound DS processing module  82  identifies an identifier of a stored encoded data slice corresponding to a small data object for retrieval. For example, the inbound DS processing module  82  accesses at least one of a DSN directory and a dispersed hierarchical index using an identifier of the small data object for retrieval to recover the identifier (e.g., slice name) of the corresponding stored encoded data slice. For instance, the inbound DS processing module  82  obtains a slice name corresponding to encoded data slice  2  that includes storage of small data object  2  for retrieval. 
     Having identified the identifier of the corresponding stored encoded data slice, the inbound DS processing module  82  initiates retrieval of the stored encoded data slice. For example, the inbound DS processing module  82  issues a read slice request to a DST execution unit corresponding to the identifier of the stored encoded data slice for retrieval and receives a read slice response that includes the stored encoded data slice when the stored encoded data slice is available. For instance, the DS error decoding  182  receives, via the network  24 , encoded data slice  2  from DST execution unit  2  when the encoded data slice  2  is available from the DST execution unit  2 . 
     Having received the corresponding stored encoded data slice that includes the small data object for retrieval, the inbound DS processing module  82  extracts the small data object from the received corresponding stored encoded data slice. For example, the data de-partitioning  184  extracts the small data object  2  from the received encoded data slice  2  to produce recovered small data object  2 . 
       FIG.  41 H  illustrates an example of retrieving the stored data to reproduce the data in accordance with the data concatenation approach where the inbound DS processing module  82  retrieves a decode threshold number of encoded data slices of the set of encoded data slices. For example, the inbound DS processing module  82  determines that the stored encoded data slice  2  is not available from the corresponding DST execution unit  2  by at least one of detecting that a response timeframe has expired since issuing the read slice request, receiving no read slice response, and receiving an unfavorable read slice response (e.g., but does not include the stored encoded data slice). Having determined that the stored encoded data slice is not available, the inbound DS processing module  82  issues a decode threshold number of read slice requests to other DST execution units of the DST execution unit set  402 , and receives at least a decode threshold number of favorable read slice responses that includes the decode threshold number of encoded data slices of the set of encoded data slices. For example, the DS error decoding  182  receives, via the network  24 , the decode threshold number of encoded data slices that includes one or more data slices  408  and one or more error coding slices  410 . 
     Having received the decode threshold number of encoded data slices, the DS error decoding  182  dispersed storage error decodes the received decode threshold number of encoded data slices to produce a recovered concatenated object  414 . The data de-partitioning  184  extracts the encoded data slice for retrieval from the recovered concatenated object to produce a recovered small data object. For example, the data de-partitioning  184  extracts the encoded data slice  2  for retrieval from the recovered concatenated object  414  and extracts the small data object  2  from the extracted encoded data slice  2 . 
       FIG.  41 I  is a flowchart illustrating an example of concatenating data objects for storage. In particular, a method is presented for use in conjunction with one or more functions and features described in conjunction with  FIGS.  1 - 39  and  41 A -H. The method begins at step  420  where a processing module of a computing device of one or more computing devices of a dispersed storage network (DSN) receives a message to concatenate a plurality of independent data objects, where the message is one of a user input message to group data objects having a common trait and a system message based on dispersed storage network conditions. 
     The method continues at step  422  where the processing module concatenates the plurality of independent data objects into a concatenated data object, where the concatenating is based a parameter of a dispersed storage error encoding function that indicates a number of data-based encoded data slices (e.g., a decode threshold number) resulting from performing the dispersed storage error encoding function. As a specific example, the processing module identifies data objects having the common trait and establishes the plurality of independent data objects from the data objects having the common trait. 
     As another specific example of the concatenating of the plurality of independent data objects, the processing module maps the plurality of independent data objects into “k” rows to produce the concatenated data object, wherein the “k” rows corresponds to a number of data-based encoded data slices resulting from performing the dispersed storage error encoding function and wherein the one or more independent data objects is mapped to a single row of the “k” rows. The processing module pads the single row of the “k” rows when a combined size of the one or more independent data objects is less than a row size. 
     As yet another specific example of the concatenating the plurality of independent data objects, the processing module maps the plurality of independent data objects into “k” rows to produce the concatenated data object, where the “k” rows corresponds to a number of data-based encoded data slices resulting from performing the dispersed storage error encoding function and where an independent data object of the plurality of independent data objects is mapped to more than one row of the “k” rows. 
     The method continues at step  424  where the processing module performs the dispersed storage error encoding function on the concatenated data object to produce a set of data-based encoded data slices and a set of redundancy-based encoded data slices, where one or more independent data objects of the plurality of independent data objects is recoverable from a corresponding data-based encoded data slice of the set of encoded data slices or from a decode threshold number of encoded data slices. The decode threshold number of encoded data slices includes one or more data-based encoded data slices of the set of data-based encoded data slices and one or more redundancy-based encoded data slices of the set of redundancy-based encoded data slices. As a specific example, the processing module converts the concatenated data object into a data matrix, generates a coded matrix based on the data matrix and an encoding matrix, generates the set of data-based encoded data slices from a first portion of the coded matrix that corresponds to a first portion of the encoding matrix, and generates the set of redundancy-based encoded data slices from a second portion of the coded matrix that corresponds to a second portion of the encoding matrix. 
     The method continues at step  426  where the processing module outputs the set of data-based encoded data slices to a first set of storage units for storage. The method continues at step  428  where the processing module outputs the set of redundancy-based encoded data slices to a second set of storage units for storage. 
     The method described above in conjunction with the processing module can alternatively be performed by other modules of the dispersed storage network or by other devices. In addition, at least one memory section of a computer readable storage medium that stores operational instructions can, when executed by one or more processing modules of one or more computing devices of the dispersed storage network (DSN), cause the one or more computing devices to perform any or all of the method steps described above. 
       FIGS.  42 A-C  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating an example of storing and retrieving data. The DSN includes dispersed storage and task (DST) execution unit sets  1 - 2 , the network  24  of  FIG.  1   , and the DST client module  34  of  FIG.  1   . Each DST execution unit set includes a set of DST execution units  1 - n . Each DST execution unit may be implemented utilizing the DST execution unit  36  of  FIG.  1   . The DST client module  34  includes the outbound dispersed storage (DS) processing module  80  and the inbound DS processing module  82  of  FIG.  3   . Each DST execution unit set may be associated with attributes of the corresponding set of DST execution units. Such attributes include one or more of storage capacity, storage latency, retrieval reliability, storage availability, and ingestion rate capability. Each DST execution unit set may be associated with value ranges of the attributes with respect to the other DST execution unit sets. For example, DST execution unit set  1  may be associated with lower than average storage capacity and higher than average ingestion rate capability while DST execution unit set  2  may be associated with higher than average storage capacity and average ingestion rate capability. 
       FIG.  42 A  illustrates initial steps of the example of the storing of the data to produce stored data. As a specific example, the outbound DS processing module  80  initiates receiving of the data  430  (e.g., a long transfer, a data stream) for storage and tracks a cumulative size of the received data  430  while the data has been received. While the cumulative size of the received data is less than a size threshold level, the outbound DS processing module  80  facilitates storage of a portion of the received data  430  in the DST execution unit set  1 . For example, the outbound DS processing module  80  partitions the portion of the received data to produce a data segment, dispersed storage error encodes the data segment to produce a set of encoded data slices (e.g., slices  1 - 1 ,  1 - 2 , through  1 - n  for a first set), generates a set of write slice requests  432  that includes the set of encoded data slices, and sends the set of write slice requests  432  to the set of DST execution units  1 - n  of the DST execution unit set  1 . The set of DST execution units  1 - n  stores the set of encoded data slices for each received set of encoded data slices of the portion of the data. 
       FIG.  42 B  illustrates further steps of the example of the storing of the data to produce the stored data. In the example, when the cumulative size of the received data is greater than the size threshold level, the outbound DS processing module  80  facilitate storage of remaining portions of the received data  430  in the DST execution unit set  1 . For example, for each remaining portion, the outbound DS processing module  80  partitions the remaining portion into data segments, and for each data segment, dispersed storage error encodes the data segment to produce another set of encoded data slices, issues another set of write slice requests  432  that includes the other set of encoded data slices to the set of DST execution units  1 - n  of the DST execution unit set  2 . The set of DST execution units  1 - n  of the DST execution unit set  2  stores the other set of encoded data slices etc. For instance, the set of DST execution units  1 - n  of the DST execution unit set  2  stores encoded data slices  3 - 1 ,  3 - 2 , through  3 - n  etc. 
     When the cumulative size of the received data is greater than a size threshold level, the outbound DS processing module  80  further facilitates migration of one or more sets of encoded data slices of the received data from the DST execution unit set  1  to the DST execution unit set  2 . For example, the outbound DS processing module  80  retrieves encoded data slices  1 - 1 ,  1 - 2 , through  1 - n  from the DST execution unit set  1  and stores the retrieved encoded data slices in the DST execution unit set  2  etc. When confirming that the migration has been completed, the outbound DS processing module  80  may facilitate deletion of the one or more sets of encoded data slices of the received data from the DST execution unit set  1 . For example, the outbound DS processing module  80  issues delete slice requests to the set of DST execution units  1 - n  of the DST execution unit set  1  to delete the one or more sets of encoded data slices of the received data. 
     Having migrated the encoded data slices to the DST execution unit set  2 , the outbound DS processing module  80  generates metadata of the data that includes an association of one or more of a storage location of the received data within the DST execution unit set  1 , identity of the received data, and identity of the sets of encoded data slices. Alternatively, when the cumulative size of all of the received data is not greater than the size threshold level, the outbound DS processing module  80  generates the metadata to indicate that storage of the data is associated with the DST execution unit set  1 . 
     Having generated the metadata, the outbound DS processing module  80  dispersed storage error encodes the metadata to produce a set of metadata slices (e.g., M- 1 , M 2 , through M-n). The outbound DS processing module  80  stores the set of metadata slices in the DST execution unit set  1 . For example, the outbound DS processing module  80  issues a set of write slice requests  432  to the set of DST execution units  1 - n  of the DST execution unit set  1 , where the set of write slice requests  432  includes the set of metadata slices. The set of DST execution units  1 - n  of the DST execution unit set  1  stores the set of metadata slices. 
     Having stored the set of metadata slices, the outbound DS processing module  80  associates a storage location (e.g., a source name, a DSN address, a set of slice names) of the metadata slices with the identity of the received data. For example, the outbound DS processing module  80  updates a DSN directory to associate the identity of the received data and the source name of the storage location of the set of metadata slices. As another example, the outbound DS processing module  80  updates an entry of an index node of a dispersed hierarchical index to associate the identity of the received data and the source name of the storage location of the set of metadata slices. 
       FIG.  42 C  illustrates an example of the retrieving of the stored data. As a specific example, the inbound DS processing module  82  identifies the storage location of the metadata slices based on the identity of the data for retrieval. For example, the inbound DS processing module  82  accesses the DSN directory using the identity of the data for retrieval to recover the source name of the storage location of the metadata slices. Having identified the storage location, the inbound DS processing module  82  recovers the metadata using the storage location of the metadata slices. For example, the inbound DS processing module  82  issues a read threshold number of read slice requests to the set of DST execution units  1 - n  of the DST execution unit set  1  that corresponds to the storage location, where the read slice requests includes slice names of the metadata slices, receives read slice responses  434  from the DST execution unit set  1 , and dispersed storage error decodes a decode threshold number of extracted metadata slices from the received read slice responses to reproduce the metadata. 
     Having recovered the metadata, the inbound DS processing module  82  identifies a storage location of the data for retrieval from the reproduced metadata. For example, the inbound DS processing module  82  extracts a DSN address from the reproduced metadata and determines an identifier of a corresponding DST execution unit set (e.g., set  2 ). Having identified the storage location of the data, the inbound DS processing module  82  retrieves one or more sets of encoded data slices using the storage location. For example, the inbound DS processing module  82  issues a set of read slice requests to the DST execution unit set  2 , where the set of read slice requests includes one or more sets of slice names corresponding to the one or more sets of encoded data slices and receives read slice responses from the set of DST execution units  1 - n  of the DST execution unit set  2 . Having received the read slice responses  434 , the inbound DS processing module  82  disperse storage error decodes a decode threshold number of encoded data slices of each of one or more sets of encoded data slices to produce a plurality of recovered data segments and aggregates the plurality of recovered data segments to produce the recovered data  436 . 
       FIG.  42 D  is a flowchart illustrating another example of accessing data. The accessing of the data includes storing of the data and retrieving of the data. As a specific example of the storing of the data, the method begins or continues at step  438  where a processing module (e.g., of a distributed storage and task (DST) client module) receives data and while a cumulative size of the data being received is less than a size threshold level, the processing module stores a portion of the received data in a first set of storage units. For example, the processing module partitions a portion of the received data to produce a data segment, dispersed storage error encodes the data segment to produce a set of encoded data slices, and issues a set of write slice requests to the first set of storage units, where the set of write slice request includes the set of encoded data slices. 
     When a cumulative size of the data being received is greater than the size threshold level, the method continues at step  440  where the processing module stores remaining portions of the received data in a second set of storage units. For example, the processing module partitions the remaining portions of the received data to produce data segments, and for each additional data segment, dispersed storage error encodes the additional data segment to produce an additional set of encoded data slices, and issues an additional set of write slice requests to the second set of storage units, where the additional set of write slice requests includes the additional set of encoded data slices. 
     When the cumulative size of the data being received is greater than the size threshold level, the method continues at step  442  where the processing module facilitates migration of one or more portions of the received data from the first set of storage units to the second set of storage units. For example, for each set of encoded data slices stored in the first set of storage units, the processing module retrieves each of the sets of encoded data slices and stores each of the sets of encoded data slices of the second set of storage units. The method continues at step  444  where the processing module generates metadata of the data that includes an association of a storage location of the portions of the received data in the second set of storage units and the identity of the data. 
     The method continues at step  446  where the processing module dispersed storage error encodes the metadata to produce a set of metadata slices. The method continues at step  448  where the processing module stores the set of metadata slices in the first set of storage units. The method continues at step  450  where the processing module associates the identity of the data with a storage location of the metadata slices. For example, the processing module updates at least one of a dispersed storage network (DSN) directory and a dispersed hierarchical index. 
     As a specific example of the retrieving of the data, the method continues or begins at step  452  where the processing module identifies the storage location of the set of metadata slices based on identity of data for retrieval. For example, the processing module accesses at least one of the DSN directory in the dispersed hierarchical index using the identity of the data to recover the storage location. The method continues at step  454  where the processing module recovers the metadata from the first set of storage units using the storage location. For example, the processing module issues a set of read slice requests to the first set of storage units using the storage location, receives metadata slices, and dispersed storage error decodes a decode threshold number of metadata slices to reproduce the metadata. 
     The method continues at step  456  where the processing module identifies a storage location for the data for retrieval from the recovered metadata. For example, the processing module extracts a DSN address from the recovered metadata and identifies the storage location for the data based on the DSN address (e.g., performs a DSN address to storage location lookup to identify the second set of storage units). 
     The method continues at step  458  where the processing module retrieves at least a decode threshold number of encoded data slices of each set of encoded data slices of a plurality of sets of encoded data slices corresponding to the portions of the data from the second set of storage units using the storage location for the data. For example, the processing module generates one or more sets of read slice requests using the storage location for the data, sends the one or more sets of read slice requests to the second set of storage units, receives read slice responses, and extracts a decode threshold number of encoded data slices from each set of received encoded data slices. 
     For each set of encoded data slices, the method continues at step  460  where the processing module decodes the at least the decode threshold number of encoded data slices to reproduce the data for retrieval. For example, the processing module disperse storage error decodes a decode threshold number of encoded data slices of the at least the decode threshold number of encoded data slices for each set of encoded data slices to reproduce a corresponding data segment and aggregates each of the corresponding reproduced data segments to reproduce the data for retrieval. 
       FIG.  43 A  is a schematic block diagram of an embodiment of a storage service access system that includes the user device  12  of  FIG.  1   , the distributed storage and task (DST) processing unit  16  of  FIG.  1   , one or more authentication servers  462 , and at least one storage service  464 . The storage service  464  includes one or more of a dispersed storage network (DSN), a Web services provider (e.g., Amazon Web Services (AWS)), and a distributed storage and task network (DSTN). 
     The storage service access system functions to authenticate access to the storage service  464 . In an example of operation, the user device  12  (e.g., a requesting entity with regards to the requesting access to the storage service, alternatively a storage service provider on behalf of the user device  12 ) issues a generate key request  466  to the DST processing unit  16 . The generate key request  466  includes one or more of a user name associated with a user, and a password associated with the username and user. The DST processing unit  16  identifies one of the authentication servers  462  based on the generate key request  466  (e.g., based on the username and a mapping of usernames to authentication servers). 
     The DST processing unit  16  issues an authentication request  468  to the identified authentication server, where the authentication request  468  includes the generate key request  466  (e.g., the username and the password). The authentication server  462  authenticates the authentication request  468  by comparing the authentication request  468  to authentication records and account status information. When the authentication server  462  determines that the authentication request  468  is favorably authenticated, the authentication server  462  issues an authentication response  470  to the DST processing unit  16 . The authentication response  470  includes one or more of the authentication request  468  and an account identifier (ID) associated with the username and/or user. 
     The DST processing unit  16  determines whether the generate key request  466  is authenticated based on the authentication response  470 . For example, the DST processing unit  16  indicates that the generate key request  466  is authenticated when the authentication response  470  includes the account ID. Having authenticated the generate key request, the DST processing unit  16  generates a storage key and a storage key ID. The storage key includes a secret key to be associated with the account ID and may be utilized to access the storage service. For example, the DST processing unit  16  generates a random AWS key as the storage key. As another example, the DST processing unit  16  generates another storage service key as the storage key such that the storage key is compatible with the storage service  464 . The DST processing unit  16  may generate another random number to produce the storage key ID. 
     Having generated the storage key and the storage key ID, the DST processing unit  16  generates an index entry of an index (e.g., of a dispersed hierarchical index, of a local index) to include one or more of the storage key, the storage key ID, the account ID, an identifier of the identified authentication server (e.g., authentication server ID), where an index key to locate the entry of the index may be based on one or more of the storage key ID, the authentication server ID, the account ID, and a storage key value. Having generated the index entry of the index, the DST processing unit  16  updates the index to include the generated index entry. For example, the DST processing unit  16  accesses a DSN memory using the index key to search the dispersed hierarchical index for an index node, retrieves the index node, updates the index node to include the index entry, and stores the updated index node in the DSN memory to update the dispersed hierarchical index. 
     Having updated the index, the DST processing unit  16  issues a generate key response  472  to the user device  12 , where the generate key response  472  includes the storage key ID and may include the storage key. Having received the generate key response  472 , the user device  12  issues an access validation request  474  to the DST processing unit  16 , where the access validation request  474  includes the storage key ID and a signature request. The DST processing unit  16  accesses the index using the storage key ID to recover the index entry and extract one or more of the storage key, the account ID, and the authentication server ID. The DST processing unit  16  may issue another authentication request  468  to an authentication server  462  associated with the authentication server ID and receive another authentication response  470 . 
     When the other authentication response  470  is favorable (e.g., the user/account ID is still authenticated), the DST processing unit  16  validates the signature request using the storage key. For example, the DST processing unit  16  signs the signature request using the storage key. Having validated the signature request, the DST processing unit  16  issues an access validation response  476  to the user device  12 . Having received the access validation response  476 , the user device  12  issues a storage service access request  478  to the storage service  464 , where the storage service access request includes the validated signature request. The storage service  464  processes the storage service access request  478  and issues a storage service access response  478  to the user device. Alternatively, or in addition to, the storage service may issue a generate key request as a query  480  to the DST processing unit  16  and receive the generate key response on behalf of the user device  12  as a query response  482 . 
       FIG.  43 B  is a flowchart illustrating an example of authentication access to a storage service. The method begins or continues to establish authentication at step  484  where a processing module (e.g., of a distributed storage and task (DST) client module) receives a generate key request from a requesting entity (e.g., a storage service on behalf of a user device, the user device) for an accessing entity (e.g., the user device). The method continues at step  486  where the processing module issues an authentication request to a corresponding authentication module based on the generate key request. For example, the processing module identifies the authentication module based on the generate key request, generates the authentication request to include a username and password of the generate key request, sends the authentication request to the identified authentication module, and receives an authentication response. 
     The method continues at step  488  where the processing module determines whether the authentication is favorable based on the received authentication response from the authentication module. For example, the processing module indicates that the authentication is favorable when the received authentication response indicates that the requesting entity and/or the accessing entity are authenticated. When the authentication is favorable, the method continues at step  490  where the processing module generates a storage key for the accessing entity. For example, the processing module generates a secret key as the storage key and an identifier (ID) of the storage key (e.g., storage key ID). 
     The method continues at step  492  where the processing module generates an index entry to include access information. The access information includes one or more of an account ID of the accessing entity, the storage key ID, the storage key, an identifier of the authentication module, and at least one indexing key (e.g., the processing module may generate the indexing key based on one or more of the storage key ID, the authentication module ID, the account ID, and the storage key). The method continues at step  494  where the processing module updates one or more dispersed hierarchical indexes to include the index entry based on one or more indexing keys. For example, the processing module searches a first dispersed hierarchical index using a selected indexing key, adds the index entry to an identified index node, and stores the updated index node in the dispersed hierarchical index (e.g., encodes the updated index node to produce a set of index slices and facilitate storage of the set of index slices in a dispersed storage network (DSN) memory). The method continues at step  496  where the processing module issues a generate key response to the requesting entity, where the generate key response includes one or more of the storage key ID and the storage key. 
     The method continues where the processing module begins to facilitate access to the storage service at step  498  when the processing module receives an access validation request from the accessing entity. The access validation request includes one or more of the storage key ID and a signature request. The method continues at step  500  where the processing module accesses a corresponding dispersed hierarchical index based on the access validation request to recover the index entry. For example, the processing module searches the dispersed hierarchical index using the storage key ID of the request as an indexing key and extracts one or more of the storage key, the account ID, and the authentication module ID from an identified index entry of the index. Alternatively, the processing module accesses a list of index entries using the account ID to recover the index entry. 
     The method continues at step  502  where the processing module issues an authentication request to the corresponding authentication module based on the recovered index entry. For example, the processing module identifies data from an authentication module from the index entry, generates the authentication request to include the account ID, sends the authentication request to the identified a convocation module, and receives an authentication response. 
     The method continues at step  504  where the processing module determines whether the authentication is favorable based on the received authentication response from the authentication module. When the authentication is favorable, the method continues at step  506  where the processing module issues a favorable access validation response to the accessing entity. For example, the processing module validates the signature request from the accessing entity to produce a validated signature, generates the favorable access validation response to include the validated signature request, and sends the favorable access validation response to the accessing entity. 
     The method continues at step  508  where the accessing entity accesses the storage service using the favorable access validation response. For example, the accessing entity generates an access request that includes the validated signature, sends the access request to the storage service, and receives an access response from the storage service. 
       FIGS.  44 A-B  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating another example of storing data, where the DSN includes the distributed storage and task (DST) client module  34  of  FIG.  1   , the network  24  of  FIG.  1   , and a DST execution unit set  510 . The DST client module  34  includes the outbound dispersed storage (DS) processing module  80  and the inbound DS processing module  82  of  FIG.  3   . The DST execution unit set  510  includes a set of DST execution units  36  of  FIG.  1   , where one or more DST execution units are deployed at one or more sites. Each DST execution unit provides at least one storage slot of N storage slots. A storage slot includes at least one virtual storage location associated with physical memory of the DST execution unit. For example, the DST execution unit set  510  includes DST execution units  1 - 14  when 30 storage slots are provided and a varying number of storage slots are associated with each DST execution unit. The DSN functions to store data to the set of DST execution unit set  510  and to retrieve the data from the DST execution unit set  510 . 
       FIG.  44 A  illustrates initial steps of an example of operation of the storing of the data to the DST execution unit set  510 , where the outbound DS processing module  80  receives a write data object request  512  from a requesting entity. The write data object request  512  includes one or more of a data object for storage in the DSN, a data identifier (ID) of the data, an ID of the requesting entity, and a desired performance level indicator. Having received the write data object request  512 , the outbound DS processing module  80  obtains dispersal parameters. The dispersal parameters includes one or more of a number of storage slots N, an information dispersal algorithm (IDA) width number, a write threshold number, a read threshold number, and a decode threshold number. The obtaining includes at least one of retrieving a portion of system registry information, utilizing a predetermination, determining based on the desired performance level indicator, and accessing a list based on the requesting entity ID. 
     Having obtained the dispersal parameters, the outbound DS processing module  80  selects a set of primary storage slots of N storage slots associated with the DST execution unit set, where the set of storage slots includes at least a decode threshold number of storage slots and at most an IDA width number of storage slots. The selecting may be based on one or more of DST execution unit availability information, a DST execution unit performance level, site availability information, system topology information, a system loading level, a system loading goal level, a data storage availability goal, a data retrieval reliability goal, and a site selection scheme. As a specific example, the outbound DS processing module  80  selects the IDA width number of storage slots out of the N storage slots. As such, the outbound DS processing module  80  selects one permutation out of a number of permutations expressed by a formula: number of permutations of the selecting of the IDA width number of storage slots=N choose IDA width. For instance, the number of permutations of selecting the IDA width number of storage slots=30 choose 15=155 million permutations, when N=30 and the IDA width=15. 
     Storage of data within the DST execution unit set can tolerate a number of storage slot failures and/or unavailability without affecting data storage availability and data retrieval reliability in accordance with a formula: number of storage slot failures tolerated=N-IDA width=30−15=15. As such, the storage of data within the DST execution unit set can tolerate 15 storage slot failures. 
     The outbound DS processing module  80  may select the IDA width number of storage slots in accordance with the site selection scheme to improve the data retrieval reliability. For example, the outbound DS processing module  80  selects storage slots at each site of the one or more sites such that at least a decode threshold number of encoded data slices are available from available storage slots at a minimum desired number of sites. As a specific example, the outbound DS processing module  80  selects storage slots associated with available and better-than-average performing DST execution units such that the decode threshold number of encoded data slices are available from any two operational sites when one of three total sites is unavailable. For instance, the outbound DS processing module  80  selects 5 storage slots at each of the 3 sites when the IDA width is 15 and the decode threshold is 10. 
     Having selected the set of primary storage slots, the outbound DS processing module  80  encodes the data object using a dispersed storage error encoding function and in accordance with the dispersal parameters to produce a plurality of sets of encoded data slices. For example, the outbound DS processing module  80  encodes a first data segment of a plurality of data segments of the data object to produce a first set of encoded data slices, where the first set of encoded data slices includes the IDA width number of slices and the first data segment may be recovered when at least any decode threshold number of encoded data slices of the set of encoded data slices is retrievable. 
     Having encoded the data object, the outbound DS processing module  80 , identifies DST execution units associated with the selected set of primary storage slots. The identifying may be based on one or more of a table lookup (e.g., a storage slot to DST execution unit mapping), initiating a query, and receiving a query response. For example, the outbound DS processing module  80  identifies DST execution units  1 ,  2 ,  3 ,  5 ,  6 ,  8 ,  10 ,  12 , and  13  based on accessing the storage slot to DST execution unit mapping. 
     Having identified the DST execution units associated with the selected set of primary storage slots, the outbound DS processing module  80  identifies an underperforming DST execution unit (e.g., poor performance, failing, failed) of the identified DST execution units associated with the selected set of primary storage slots. The identifying may be based on one or more of receiving an error message, performing a test, interpreting test results, and monitoring performance information associated with the identified DST execution units. For example, the outbound DS processing module  80  identifies DST execution unit  13  as the underperforming DST execution unit based on receiving an error message from DST execution unit  13 , where the error message is interpreted to indicate underperformance. 
     Having identified underperforming DST execution unit, the outbound DS processing module  80  identifies one or more primary storage slots associated with the underperforming DST execution unit. For example, the processing module accesses the storage slot to DST execution unit mapping to identify the one or more primary storage slots associated with the underperforming DST execution unit. For instance, the outbound DS processing module  80  identifies primary storage slot  29  associated with DST execution unit  13  by accessing the storage slot to DST execution unit mapping. 
     For each of the one or more identified primary storage slots associated with the underperforming DST execution unit, the outbound DS processing module  80  replicates an associated encoded data slice of each of the plurality sets of encoded data slices to produce replicated encoded data slices. For example, the outbound DS processing module  80  identifies encoded data slice  15  associated with primary storage slot  29  and replicates encoded data slice  15  of each of the sets of encoded data slices to produce replicated encoded data slices  15 . 
     Having produced the replicated encoded data slices, the outbound DS processing module  80  generates one or more sets of write slice requests  514 , where the one or more sets of write slice requests  514  includes the plurality of sets of encoded data slices and the replicated encoded data slices. Having generated the one or more sets of write slice requests  514 , the outbound DS processing module  80 , for each replicated slice, selects an alternate storage slot associated with another DST execution unit, where the other DST execution unit is not underperforming. The selecting may be based on one or more of the slice to storage slot mapping, performance levels of the DST execution units, a DST execution unit performance threshold level, a performance goal, a network loading level, and a network loading level goal. For example, the outbound DS processing module  80  selects storage slot  30  associated with DST execution unit  14  for storage of the replicated encoded data slices  15  when performance levels of the DST execution unit  14  is greater than the DST execution unit performance threshold level (e.g., not underperforming). 
     Having selected the alternate storage slot, the outbound DS processing module  80  sends, via the network  24 , the one or more sets of write slice requests  514  to the identified DST execution units and to the other DST execution unit. As an example of the sending the one or more sets of write slice requests to the identified DST execution units, the outbound DS processing module  80  sends, via the network  24 , write slice requests  514  to store encoded data slices  1 - 2  in storage slots  1 - 2  of DST execution unit  1 , encoded data slices  3 - 4  in storage slots  4 - 5  of DST execution unit  2 , encoded data slice  5  in storage slot  7  of DST execution unit  3 , encoded data slice  6  in storage slot  13  of DST execution unit  5 , encoded data slices  7 - 9  in storage slots  14 - 16  of DST execution unit  6 , encoded data slice  10  in storage slot  19  of DST execution unit  8 , encoded data slices  11 - 12  in storage slots  23 - 24  of DST execution unit  10 , encoded data slices  13 - 14  in storage slots  27 - 28  of DST execution unit  12 , and encoded data slice  15  in storage slot  29  of underperforming DST execution unit  13 . As an example of the sending of the one or more sets of write slice requests  514  to the other DST execution unit, the outbound DS processing module  80  sends, via the network  24 , at least one write slice request  514  to store replicated encoded data slices  15  in storage slot  30  of DST execution unit  14 . 
     Having sent the one or more sets of write slice requests  514 , the outbound DS processing module  80  receives, via the network  24 , write slice responses  516  from at least some DST execution units of the DST execution unit set. Each write slice response  516  includes a write operation status indicator. The write operation status indicator includes a favorable indication when a corresponding write slice request was successfully executed. The write operation status indicator includes an unfavorable indication when the corresponding write slice request was not successfully executed (e.g., due to an error). The example of operation continues as is discussed in greater detail with reference to  FIG.  44 B . 
       FIG.  44 B  illustrates further steps of the example of operation of the storing of the data to the DST execution unit set, where the outbound DS processing module  80 , for each replicated encoded data slice, selects one storage slot of the storage slot associated with the encoded data slice and the alternate storage slot associated with the replicated encoded data slice based on one or more of the received write slice responses, a performance level, a performance level goal, and a predetermination. For example, the outbound DS processing module  80  selects the alternate storage slot when receiving a favorable write slice response from DST execution unit  14  with regards to the storage of the replicated encoded data slice  15  in storage slot  30  of the DST execution unit  14  and not receiving a write slice response from DST execution unit  13  with regards to the storage of the encoded data slice  15  in storage slot  29  within a storage time frame. As another example, the outbound DS processing module  80  selects the storage slot when receiving a favorable write slice response from DST execution unit  13 . 
     Having selected the one storage slot, the outbound DS processing module  80  issues a commit request  518 , via the network  24 , to a DST execution unit associated with the selected one storage slot. For example, the outbound DS processing module  80  generates and sends, via the network  24 , the commit request  518  to DST execution unit  14  when the one selected storage slot is storage slot  30  associated with DST execution unit  14 , where the commit request  518  indicates to commit redundant encoded data slice  15 . 
     Having sent the commit request  518 , the outbound DS processing module  80  issues, for a remaining storage slot of the storage slot associated with the encoded data slice and the alternate storage slot associated with the replicated encoded data slice, a rollback request  520 . For example, the outbound DS processing module  80  generates and sends, via the network  24 , the rollback request to DST execution unit  13  where the rollback request  520  indicates to rollback storage of the encoded data slice  15 . 
     Having issued the rollback request  520 , the outbound DS processing module  80 , for each other encoded data slice of each set of encoded data slices (e.g., non-replicated slices), issues, via the network  24 , a commit request  518  to an associated DST execution unit in accordance with one or more of a corresponding received write slice response and the slice to storage slot mapping. As a specific example, the outbound DS processing module  80  generates and sends, via the network  24 , commit requests  518  to commit storage of encoded data slices  1 - 2  in storage slots  1 - 2  of DST execution unit  1 , encoded data slices  3 - 4  in storage slots  4 - 5  of DST execution unit  2 , encoded data slice  5  in storage slot  7  of DST execution unit  3 , encoded data slice  6  in storage slot  13  of DST execution unit  5 , encoded data slices  7 - 9  in storage slots  14 - 16  of DST execution unit  6 , encoded data slice  10  in storage slot  19  of DST execution unit  8 , encoded data slices  11 - 12  in storage slots  23 - 24  of DST execution unit  10 , and encoded data slices  13 - 14  in storage slots  27 - 28  of DST execution unit  12 . 
       FIG.  44 C  is a flowchart illustrating an example of storing data. The method begins or continues at step  522  where a processing module (e.g., of a distributed storage and task (DST) client module) selects a set of primary storage slots from N storage slots associated with a set of storage units. The method continues at step  524  where the processing module encodes data for storage in accordance with dispersal parameters to produce a plurality of sets of encoded data slices. The method continues at step  526  where the processing module identifies an underperforming storage unit associated with a primary storage slot of the selected set of primary storage slots. For example, the processing module obtains historical storage unit performance information and identifies a most underperforming storage unit of the set of storage units. 
     The method continues at step  528  where the processing module replicates each encoded data slice associated with the primary storage slot of the underperforming storage unit to produce replicated encoded data slices. For each replicated encoded data slice, the method continues at step  530  where the processing module selects an alternate storage slot associated with another storage unit of the set of storage units. For example, the processing module interprets the historical performance storage unit performance information to identify a favorably performing storage unit that is different than the identified underperforming storage unit. 
     The method continues at step  532  of the processing module generates one or more sets of write slice requests, where the one or more sets of write slice requests includes the plurality of sets of encoded data slices and the replicated encoded data slices. The generating includes generating one or more sets of slice names and replicating at least some of the slice names that are associated with the replicated encoded data slices. The method continues at step  534  where the processing module sends the one or more sets of write slice requests to the set of storage units and to the other storage unit. For example, the processing module sends the one or more sets of write slice requests to storage units associated with the primary set of storage units and at least one write slice request to the other storage unit. The method continues at step  536  where the processing module receives write slice responses from at least some of the storage units. 
     For each replicated encoded data slice, the method continues at step  538  where the processing module selects one storage slot of the primary storage slot and the alternate storage slot based on the received write slice responses. For example, the processing module selects the storage slot when receiving a corresponding favorable write slice response for the storage slot. As another example, the processing module selects the alternate storage slot when receiving a corresponding favorable write slice response for the alternate storage slot and not receiving a favorable write slice response corresponding to the storage slot within a response timeframe. 
     The method continues at step  540  where the processing module issues a commit request to a storage unit associated with the selected one storage slot. For example, the processing module issues the commit request to include a transaction number associated with a corresponding write slice request, identifies the storage unit associated with the selected one storage slot, and outputs the commit requests to the identified storage unit. The method continues at step  542  where the processing module issues a rollback request to an un-selected storage unit associated with a remaining storage slot of the storage slot of the primary storage slots and the alternate storage slot. The issuing includes generating the rollback request to include the transaction number. For each other encoded data slice of each set of encoded data slices, the method continues at step  544  where the processing module issues a commit request to an associated storage unit in accordance with a corresponding received write slice response. 
       FIGS.  45 A-B  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating an example of rebuilding stored data. The DSN includes a distributed storage and task (DST) execution unit set  546 , the network  24  of  FIG.  1   , and the DST client module  34  of  FIG.  1   . The DST execution unit set  546  includes a set of DST execution units  1 - 8 . Each DST execution unit may be implemented utilizing the DST execution unit  36  of  FIG.  1   . The DST client module  34  includes the inbound dispersed storage (DS) processing module  82  of  FIG.  3   , and the outbound DS processing module  80  of  FIG.  3   . The DSN functions to store data as stored data, retrieve stored data to reproduce the data, and to rebuild stored data. The rebuilding the stored data includes rebuilding the stored data while retrieving the stored data. 
       FIG.  45 A  illustrates initial steps of an example of the rebuilding of the stored data while retrieving the stored data. As a specific example, the inbound DS processing module  82  receives a read data request  548  to retrieve the stored data, where the data is dispersed error encoded to produce a plurality of sets of encoded data slices that are stored in a set of storage resources (e.g., the set of DST execution units  1 - 8 ). Each set of encoded data slices includes an information dispersal algorithm (IDA) width number of encoded data slices. For example, the IDA width is 8 when producing eight encoded data slices for each set of encoded data slice. The data can be recovered when at least a decode threshold number of encoded data slices for each set of encoded data slices is available. For example, the data may be recovered when 5-8 encoded data slices for each set of encoded data slices are available and the decode threshold number is 5. 
     Having received the read data request  548 , the inbound DS processing module  82  generates a read threshold number of read slice requests  550  for a read threshold number of encoded data slices of each set of encoded data slices. The read threshold number is greater than or equal to the decode threshold number and less than or equal to the IDA width number. For example, the inbound DS processing module  82  generates 6 read slice requests corresponding to encoded data slices  1 - 1 ,  1 - 2 ,  1 - 3 ,  1 - 4 ,  1 - 5 , and  1 - 6  when the read threshold number is 6. Having generated the read threshold number of read slice requests  550 , the inbound DS processing module  82  generates a list slice request  552  for each remaining encoded data slice of a set of encoded data slices. For example, the inbound DS processing module  82  generates a list slice request  552  for encoded data slice  1 - 7  and another list slice request  552  for encoded data slice  1 - 8 . 
     Having generated the read slice requests  550  and the list slice requests  552 , the inbound DS processing module  82  sends the read threshold number of read slice requests  550  and the remaining list slice requests  552  to the set of DST execution units  1 - 8  corresponding to the set of storage resources (e.g., including in accordance with a mapping of storage resources to DST execution units). For example, the inbound DS processing module  82  sends read slice requests  1 - 6  to DST execution units  1 - 6  and sends the list slice requests  7 - 8  to DST execution units  7 - 8 . 
     Having sent the requests, the inbound DS processing module  82  receives read slice responses  554  and list slice responses  556  from at least some of the DST execution units. For example, the inbound DS processing module  82  receives read slice responses  1 - 6  from DST execution units  1 - 7  and list slice responses  7 - 8  from DST execution units  7 - 8 . For each set of encoded data slices, the inbound DS processing module  82  dispersed storage error decodes a decode threshold number of encoded data slices of received encoded data slices from the read slice responses  554  to reproduce a data segment of a plurality of data segments. The inbound DS processing module  82  aggregates the plurality of data segments to produce recovered data  549 . 
     For each set of encoded data slices, the inbound DS processing module  82  determines whether a slice error has occurred based on the received read slice responses  554  and received list slice responses  556 . A slice error includes at least one of a missing slice and a corrupted slice. For example, the inbound DS processing module  82  indicates that encoded data slice  1 - 4  is associated with a slice error when the read slice response  4  indicates that the encoded data slice  1 - 4  is corrupted or missing. As another example, the inbound DS processing module  82  indicates that encoded data slice  1 - 8  is associated with another slice error when the inbound DS processing module  82  interprets the list slice response  8  and detects that encoded data slice  1 - 8  is missing. When the slice error has occurred, the inbound DS processing module  82  identifies a corresponding reproduced data segment  558  of the plurality of reproduced data segments. 
       FIG.  45 B  illustrates further steps of the example of the rebuilding of the stored data while retrieving the stored data. As a specific example, when the slice error(s) has occurred, the outbound DS processing module  80  dispersed storage error encodes the identified reproduced data segment associated with the slice error(s) to reproduce a corresponding set of encoded data slices. For each slice error, the outbound DS processing module  80  generates a write slice request  560  that includes a corresponding reproduced encoded data slice of the reproduced set of encoded data slices. Having generated the write slice request  560 , the outbound DS processing module  80  selects a storage resource for storing the corresponding reproduced encoded data slice. The selecting may be based on one or more of DST execution unit availability, DST execution unit performance, network performance, a predetermination, and a DST execution unit solicitation as a store storage unit. For example, the outbound DS processing module  80  selects DST execution unit  4  for storage of reproduced encoded data slice  1 - 4  and selects DST execution unit  8  for storage of reproduced encoded data slice  1 - 8  when DST execution units  4  and  8  are associated with favorable performance levels. 
     Having selected the storage resource, the outbound DS processing module  80  sends the write slice request  560  to a DST execution unit corresponding to the selected storage resource. For example, the outbound DS processing module  80  sends a write slice request  4  to DST execution unit  4  for storage of reproduced encoded data slice  1 - 4  within the DST execution unit  4  and sends a write slice request  8  to DST execution unit  8  for storage of reproduced encoded data slice  1 - 8  within the DST execution unit  8 . Alternatively, the outbound DS processing module  80  sends write slice request  8  to DST execution unit  7  when DST execution unit  8  is associated with unfavorable performance levels, DST execution unit  7  is associated with favorable performance levels, and DST execution unit  7  as indicated availability as a foster storage unit. 
       FIG.  45 C  is a flowchart illustrating an example of rebuilding stored data. The method begins or continues at step  562  where a processing module (e.g., of a distributed storage and task (DST) client module) receives a read data request for data stored in a dispersed storage network (DSN) as a plurality of sets of encoded data slices. For each set of encoded data slices, the method continues at step  564  of the processing module retrieves at least a decode threshold number of encoded data slices from the DSN. For example, the processing module issues a read threshold number of read slice requests to a read threshold number of storage units of a set of storage units of the DSN and receives at least a decode threshold number of favorable read slice responses from the read threshold number of storage units. 
     For each at least a decode threshold number of encoded data slices, the method continues at step  566  where the processing module determines whether the remaining encoded data slices of the set of encoded data slices are favorably stored in the DSN. For example, the processing module issues list slice requests to storage units associated with the remaining encoded data slices, receives list slice responses, and indicates that the remaining encoded data slices are favorably stored when a sufficient number of encoded data slices are listed by the list slice responses. 
     For each set of encoded data slices, the method continues at step  568  where the processing module decodes a decode threshold number of encoded data slices of the at least a decode threshold number of encoded data slices to reproduce a corresponding data segment. For example, the processing module selects the decode threshold number of encoded data slices and dispersed storage error decodes the decode threshold number of encoded data slices to produce the reproduce corresponding data segment. Alternatively, or in addition to, the processing module aggregates a plurality of reproduced data segments to reproduce the data for outputting to a requesting entity. 
     For each set of encoded data slices, the method continues at step  570  where the processing module determines whether a storage error has occurred. For example, the processing module interprets read slice responses and list slice responses to identify a missing and/or corrupted encoded data slices of one or more storage errors. When the storage error has occurred, the method continues at step  572  where the processing module dispersed storage error encodes a corresponding reproduced data segment to produce a reproduced set of encoded data slices. 
     For each storage error, the method continues at step  574  where the processing module generates a write slice request that includes a corresponding reproduced encoded data slice. For each write slice request, the method continues at step  576  where the processing module selects a storage resource for storing the corresponding reproduced encoded data slice. The selecting may be based on one or more of storage resource performance, storage resource availability, and a predetermination. For example, the processing module selects a same storage resource associated with the storage error when a storage unit associated with the storage error has favorable storage performance. As another example, the processing module selects a foster storage resource for temporary storage of the encoded data slice when the storage resource associated with the storage error has an unfavorable attribute and the foster storage resource has favorable performance. The method continues at step  578  where the processing module sends the write slice requests to the selected storage resource of the DSN. 
       FIGS.  46 A-B  are schematic block diagrams of another embodiment of a dispersed storage network (DSN) illustrating another example of storing data. The DSN includes the DST execution unit set  510  of  FIG.  44 A , the network  24  of  FIG.  1   , and the DST client module  34  of  FIG.  1   . The DST client module  34  includes the outbound dispersed storage (DS) processing module  80  of  FIG.  3    and the inbound DS processing module  82  of  FIG.  3   . The DSN functions to store data to the set of DST execution unit set and to retrieve the data from the DST execution unit set. 
       FIG.  46 A  illustrates initial steps of an example of operation of the storing of the data to the DST execution unit set, where the outbound DS processing module  80  receives a write data object request  512  from a requesting entity. The write data object request  512  includes one or more of a data object for storage in the DSN, a data identifier (ID) of the data, an ID of the requesting entity, and a desired performance level indicator. Having received the write data object request  512 , the outbound DS processing module  80  obtains dispersal parameters. The dispersal parameters includes one or more of a number of storage slots N, an information dispersal algorithm (IDA) width number, a write threshold number, a read threshold number, and a decode threshold number. The obtaining includes at least one of retrieving a portion of system registry information, utilizing a predetermination, determining based on the desired performance level indicator, and accessing a list based on the requesting entity ID. 
     Having obtained the dispersal parameters, the outbound DS processing module  80  selects a set of primary storage slots of N storage slots associated with the DST execution unit set, where the set of storage slots includes at least a decode threshold number of storage slots and at most an IDA width number of storage slots. The selecting may be based on one or more of DST execution unit availability information, a DST execution unit performance level, site availability information, system topology information, a system loading level, a system loading goal level, a data storage availability goal, a data retrieval reliability goal, and a site selection scheme. As a specific example, the outbound DS processing module  80  selects the IDA width number of storage slots out of the N storage slots. As such, the outbound DS processing module  80  selects one permutation out of a number of permutations expressed by a formula: number of permutations of the selecting of the IDA width number of storage slots=N choose IDA width. For instance, the number of permutations of selecting the IDA width number of storage slots=30 choose 15=155 million permutations, when N=30 and the IDA width=15. 
     Storage of data within the DST execution unit set can tolerate a number of storage slot failures and/or unavailability without affecting data storage availability and data retrieval reliability in accordance with a formula: number of storage slot failures tolerated=N-IDA width=30−15=15. As such, the storage of data within the DST execution unit set can tolerate 15 storage slot failures. 
     The outbound DS processing module  80  may select the IDA width number of storage slots in accordance with the site selection scheme to improve the data retrieval reliability. For example, the outbound DS processing module  80  selects storage slots at each site of the one or more sites such that at least a decode threshold number of encoded data slices are available from available storage slots at a minimum desired number of sites. As a specific example, the outbound DS processing module  80  selects storage slots associated with available and better-than-average performing DST execution units such that the decode threshold number of encoded data slices are available from any two operational sites when one of three total sites is unavailable. For instance, the outbound DS processing module  80  selects 5 storage slots at each of the 3 sites when the IDA width is 15 and the decode threshold is 10. 
     Having selected the set of primary storage slots, the outbound DS processing module  80  encodes the data object using a dispersed storage error encoding function and in accordance with the dispersal parameters to produce a plurality of sets of encoded data slices. For example, the outbound DS processing module  80  encodes a first data segment of a plurality of data segments of the data object to produce a first set of encoded data slices, where the first set of encoded data slices includes the IDA width number of slices and the first data segment may be recovered when at least any decode threshold number of encoded data slices of the set of encoded data slices is retrievable. 
     Having encoded the data object, the outbound DS processing module  80 , identifies DST execution units associated with the selected set of primary storage slots. The identifying may be based on one or more of a table lookup (e.g., a storage slot to DST execution unit mapping), initiating a query, and receiving a query response. For example, the outbound DS processing module  80  identifies DST execution units  1 ,  2 ,  3 ,  5 ,  6 ,  8 ,  10 ,  12 , and  13  based on accessing the storage slot to DST execution unit mapping. 
     Having identified the DST execution units associated with the selected set of primary storage slots, the outbound DS processing module  80  generates one or more sets of write slice requests  514 , where the one or more sets of write slice requests  514  includes the plurality of sets of encoded data slices. Having generated the one or more sets of write slice requests  514 , the outbound DS processing module  80  sends, via the network  24 , the one or more sets of write slice requests  514  to the identified DST execution units. For example, the outbound DS processing module  80  sends, via the network  24 , write slice requests  514  to store encoded data slices  1 - 2  in storage slots  1 - 2  of DST execution unit  1 , encoded data slices  3 - 4  in storage slots  4 - 5  of DST execution unit  2 , encoded data slice  5  in storage slot  7  of DST execution unit  3 , encoded data slice  6  in storage slot  13  of DST execution unit  5 , encoded data slices  7 - 9  in storage slots  14 - 16  of DST execution unit  6 , encoded data slice  10  in storage slot  19  of DST execution unit  8 , encoded data slices  11 - 12  in storage slots  23 - 24  of DST execution unit  10 , encoded data slices  13 - 14  in storage slots  27 - 28  of DST execution unit  12 , and encoded data slice  15  in storage slot  29  of DST execution unit  13 . 
     Having sent the one or more sets of write slice requests  514 , the outbound DS processing module  80  receives, via the network  24 , write slice responses  516  from at least some DST execution units of the DST execution unit set. Each read slice response  516  includes a write operation status indicator. The write operation status indicator includes a favorable indication when a corresponding write slice request was successfully executed. The write operation status indicator includes an unfavorable indication when the corresponding write slice request was not successfully executed (e.g., due to an error). 
     Having received the write slice responses  516 , the outbound DS processing module  80  identifies one or more write failures based on the received write slice responses  516 . For example, the outbound DS processing module  80  identifies write failures associated with storage of encoded data slices  13 - 14  in storage slots  27 - 28  of DST execution unit  12  when a corresponding write slice response has not been received from DST execution unit  12  within a response timeframe (e.g., DST execution unit  12  is unavailable). The example of operation continues as is discussed in greater detail with reference to  FIG.  46 B . 
       FIG.  46 B  illustrates further steps of the example of operation of the storing of the data to the DST execution unit set, where the outbound DS processing module  80 , for each write failure, generates a foster encoded data slice. For example, the outbound DS processing module  80  generates a foster encoded data slice  13  for encoded data slice  13  and a foster encoded data slice  14  for encoded data slice  14 . Having generated the foster encoded data slices, the outbound DS processing module  80  obtains capacity information for the DST execution unit set. For example, the outbound DS processing module  80  issues capacity information requests  580  to the DST execution unit set and receives capacity information responses  582 . The capacity information may include one or more of total capacity, capacity utilized, available capacity, and capacity utilization growth rate. 
     For each foster encoded data slice, the outbound DS processing module  80  selects a storage slot based on the obtained capacity information for the DST execution unit set. The selecting includes selecting how many foster encoded data slices to store in each storage slot in accordance with a selection scheme. The selection scheme includes rank ordering starting with most available capacity, selecting at least one storage unit for all slices, and selecting a different storage unit for each foster encoded data slice. For example, the outbound DS processing module  80  selects storage slot  25  of DST execution unit  11  for storage of foster encoded data slice  14  and selects storage slot  30  of DST execution unit  14  for storage of foster encoded data slice  13  when DST execution unit  14  has a most available storage space of storage units supporting secondary slots followed by DST execution unit  11  etc. 
     For each foster encoded data slice, the outbound DS processing module  80  issues a write slice request  514  to a DST execution units that corresponds to the selected storage slots for the foster encoded data slice. The write slice request  514  includes the foster encoded data slice. For example, the outbound DS processing module  80  issues a write slice request  514  to DST execution unit  11  that includes foster encoded data slice  14  and issues another write slice request to DST execution unit  14  that includes foster encoded data slice  13 . 
       FIG.  46 C  is a flowchart illustrating another example of storing data, which include similar steps to  FIG.  44 C . The method begins or continues with steps  524  and  522  of  FIG.  44 C  where a processing module (e.g., of a distributed storage and task (DST) client module) encodes data for storage in accordance with dispersal parameters to produce a plurality of sets of encoded data slices and selects a set of primary storage slots from N storage slots associated with a set of storage units. 
     The method continues at step  584  where the processing module identifies storage units of the set of storage units associated with the selected set of primary storage slots. For example, the processing module performs a lookup based on the selected primary storage slots to identify the storage units. The method continues at step  586  where the processing module generates one or more sets of write slice requests to include the plurality of sets of encoded data slices. The method continues at step  588  where the processing module sends the one or more sets of write slice requests to the identified storage units. The method continues with step  536  of  FIG.  44 C  where the processing module receives write slice responses. 
     The method continues at step  590  where the processing module determines whether one or more write failures have occurred based on the received write slice responses. When the one or more write failures have occurred, for each write failure, the method continues at step  592  where the processing module generates a foster encoded data slice. For example, the processing module indicates a write failure when not receiving a write slice response within a response timeframe. The method continues at step  594  where the processing module obtains capacity information for at least some storage units of the set of storage units. 
     For each foster encoded data slice, the method continues at step  596  where the processing module selects a storage slot based on the capacity information. For example, the processing module selects the storage slot based on the capacity information in accordance with a by rank ordering selection scheme. For each foster encoded data slice, the method continues at step  598  where the processing module issues a write slice request to a storage unit that corresponds to the selected storage slots for the foster encoded data slice. For example, the processing module generates the write slice requests to include the foster encoded data slice and sends the write slice request to the storage unit. 
       FIG.  47 A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) that includes at least two distributed storage and task (DST) client modules  1 - 2 , the network  24  of  FIG.  1   , and a DST execution unit set  600 . Each DST client module may be implemented using the DST client module  34  of  FIG.  1   . Each DST client module includes the outbound DS processing module  80  of  FIG.  3   . The DSN functions to resolve write conflicts while storing data in the DST execution unit set. 
     In an example of operation of the resolving of the write conflicts, DST execution unit  1  dispersed storage error encodes data A- 1  to produce a plurality of sets of encoded data slices  1  (e.g., each set includes encoded data slices  1 ,  2 ,  3 , through n), generates a set of write slice requests range  1  that includes the plurality of sets of encoded data slices  1 , and sends, via the network  24 , the set of write slice requests range  1  to the set of DST execution units  1 - n . The range  1  includes a range of slice names associated with the plurality of sets of encoded data slices from data A- 1 . For example, the DST client module  1  sends, via the network  24 , range  1  encoded data slices  1  to DST execution unit  1 , range  1  encoded data slices  2  to DST execution unit  2 , etc. 
     Substantially simultaneously, DST execution unit  2  dispersed storage error encodes data A- 2  to produce a plurality of sets of encoded data slices  2  (e.g., each set includes encoded data slices  1 ,  2 ,  3 , through n), generates a set of write slice requests range  2  that includes the plurality of sets of encoded data slices  2 , and sends, via the network  24 , the set of write slice requests range  2  to the set of DST execution units  1 - n . The range  2  includes another range of slice names associated with the plurality of sets of encoded data slices from data A- 2 . For example, the DST client module  2  sends, via the network  24 , range  2  encoded data slices  2  to DST execution unit  1 , range  2  encoded data slices  2  to DST execution unit  2 , etc. 
     Each DST execution unit of the DST execution unit set  600  receives a corresponding write slice request from one of the DST client module  1  and the DST client module  2 , where the write slice request includes a plurality of encoded data slices for storage in the DST execution unit and a corresponding plurality of slice names of the plurality of encoded data slices. Having received the write slice request, the DST execution unit interprets the plurality of slice names to produce a slice name range (e.g., a high and low slice name produces the range). Having produced the slice name range, the DST execution unit determines whether a write lock conflict exists based on the slice name range. For example, the processing module indicates the write lock conflict when the slice name range conflicts with a previously and still active locked slice name range of the DST execution unit. 
     When the write lock conflict does not exist, the DST execution unit indicates that the slice name ranges now locked, initiates local storage of the received plurality of encoded data slices, issues a favorable write slice response to the corresponding one of the DST client modules  1  and  2 , and indicates that the slice name range is not locked when completing the local storage of the plurality of encoded data slices (e.g., completing after receiving a corresponding commit transaction request). 
     When the write lock conflict does exist, the DST execution unit issues an unfavorable write slice response to the corresponding one of the DST client modules  1  and  2 . The unfavorable write slice response indicates that the write lock conflict exists. 
       FIG.  47 B  is a flowchart illustrating an example of resolving write conflicts. The method begins or continues at step  602  where a processing module (e.g., of a distributed storage and task (DST) execution unit, of a storage unit) receives a write slice request from a requesting entity, where the write slice request includes a plurality of encoded data slices and the corresponding plurality of slice names. The method continues at step  604  where the processing module interprets the plurality of slice names to produce a slice name range. The interpreting includes identifying a lowest slice name and a high slice name of the corresponding plurality of slice names to produce the slice name range. 
     The method continues at step  606  where the processing module determines whether a write lock conflict exists based on the slice name range. For example, the processing module indicates that the write lock conflict exists when the slice name range conflicts with a lock slice name range. For instance, the slice name range overlaps with a retrieved locked slice name range of a currently active write lock. When the write conflict exists, the method continues at step  608  where the processing module issues an unfavorable write slice response to the requesting entity. For example, the processing module generates the unfavorable write slice response to indicate that the write lock conflict exists, and sends the write slice response to the requesting entity. When the write lock conflict does not exist, the method branches to step  610 . 
     The method continues at step  610  where the processing module indicates that the slice name range is locked when the write conflict does not exist. For example, the processing module updates a lock slice name list to include the slice name range. The method continues at step  612  where the processing module initiates local storage of the plurality of encoded data slices. For example, the processing module stores the plurality of encoded data slices in the memory of the storage unit. 
     The method continues at step  614  where the processing module issues a favorable write slice response to the requesting entity. For example, the processing module generates the favorable write slice response to indicate a favorable write slice operation and sends the favorable write slice response to the requesting entity. The issuing may further include receiving at least one of a rollback transaction request and a commit transaction request followed by at least one of a finalize transaction request or an undo transaction request. 
     The method continues at step  616  where the processing module indicates that the slice name range is not locked when completing the local storage of the plurality of encoded data slice. For example, the processing module receives the finalize transaction request and updates the locked slice name list to indicate that the slice name range is not locked. 
       FIG.  48 A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) that includes the distribute storage and task (DST) client module  34  of  FIG.  1   , the network  24  of  FIG.  1   , and the DST execution unit set  600  of  FIG.  47 A . The DST execution unit set includes a set of DST execution units  1 - n . The DST client module  34  includes the outbound dispersed storage (DS) processing module  80  of  FIG.  3    and the inbound DS processing module  82  of  FIG.  3   . The outbound DS processing module  80  includes a selection module  618 , a compression module  620 , and the DS error encoding  112  of  FIG.  4   . The inbound DS processing module  80  includes the DS error decoding  182  of  FIG.  13   , a de-compression module  622 , and a de-selection module  624 . The DSN functions to store and retrieve a plurality of correlated data. 
     In an example of operation of the storing the plurality of correlated data, the outbound DS processing module  80  receives a plurality of sorted data entries  626 , where the sorted data entries share a common affiliation. The common affiliation includes at least one of belonging to a common index node of a dispersed hierarchical index, being sorted with similar sorting factor outcomes, sharing a common data type, sharing a common data source, sharing a common data owner, belonging to a common storage vault, etc. The receiving of the plurality of sorted data entries may include searching the dispersed hierarchical index and recovering the common index node that includes the sorted data entries. 
     Having obtained the plurality of sorted data entries  626 , the outbound DS processing module  80  obtains a data access goal level associated with the plurality of sorted data entries. The obtaining includes at least one of performing a lookup, determining based on historical performance, and receiving. Such data access goal levels include a data access latency goal, a data access bandwidth goal, and a data access transfer rate goal. 
     Having obtained the data access goal level, the outbound DS processing module  80  obtains a DSN performance information. The DSN performance information includes one or more of access latency, bandwidth, transfer rates, resource availability levels, local memory capacity, available processing capacity levels, and available storage levels. The obtaining includes at least one of performing a lookup, accessing a historical record, initiating a query, receiving a query response, initiating a test, and interpreting a test result. 
     Having obtained the DSN performance information, the outbound DS processing module  80  selects compression parameters based on one or more of the data access goal level and the DSN performance information. For example, the outbound DS processing module  80  performs an iterative function to estimate data access performance based on a given set of compression parameters and the DSN performance information, compares the estimated data access performance to the data access goal level and adjusts the compression parameters such that the estimated performance is substantially the same as the data access goal level. The compression parameters include one or more of a compression algorithm identifier, a compression level, an allocated memory level, a desired size of compressed data, and a size of the data object for compression. Data access latency includes a number of access cycles multiplied by a sum of an individual access latency and the individual compression related latency. 
     Having selected the compression parameters, the selection module selects sorted data entries to produce a data object  628  based on the selected compression parameters. For example, a data object A includes a plurality of index keys  1 ,  2 ,  3 ,  4 , etc., and corresponding content  1 ,  2 ,  3 ,  4 , etc. Having produced the data object  628 , the compression module compresses the data object  628  to produce a compressed data object  630  in accordance with the selected compression parameters. For example, the compression module compresses a data object A using the selected compression parameters to produce a compressed data object A. 
     Having produced the compressed data object  630 , the DS error encoding  112  dispersed storage error encodes the compressed data object to produce one or more sets of encoded data slices. The outbound DS processing module  80  issues, via the network  24 , write slice requests  634  to the set of DST execution units  1 - n , where the write slice requests  634  includes encoded data slices  1 - n  of each set of encoded data slices. The outbound DS processing module  80  receives write slice responses  636  from the DST execution unit set indicating whether the one or more sets of encoded data slices have been successfully stored. 
     In an example of operation of the retrieving of the plurality of correlated data, the inbound DS processing module  82  issues read slice requests  638  to the set of DST execution units  1 - n  and receives read slice responses  640  from at least some of the set of DST execution units  1 - n , where the read slice responses  640  includes encoded data slices of the one or more sets of encoded data slices. Having received the read slice responses, the DS error decoding  182 , for each set of encoded data slices, decodes a decode threshold number of received encoded data slices to reproduce the compressed data object  630 . The de-compression module  622  decompresses the compressed data object  630  to reproduce the data object  628 . The de-selection module  624  selects one or more entries of the reproduced data object to provide recovered sorted data entries  632 . 
       FIG.  48 B  is a flowchart illustrating an example of storing a plurality of correlated data. The method begins or continues at step  642  where a processing module (e.g., of a distributed storage and task (DST) client module) obtains a plurality of sorted data entries. For example, the processing module searches a dispersed hierarchical index of a dispersed storage network (DSN) to recover an index node that includes a compressed data object that includes plurality of sorted data entries and decompresses the compressed data object to produce the sorted data entries. The method continues at step  644  where the processing module obtains a data access performance goal level associated with the plurality of sorted data entries. For example, the processing module accesses system registry information and interprets historical performance information to produce the data access performance goal level. 
     The method continues at step  646  where the processing module obtains DSN performance information. The obtaining includes one or more of accessing historical DSN performance information, initiating a performance test, and interpreting a performance test result. The method continues at step  648  where the processing module selects compression parameters based on the data access performance goal level and the DSN performance information. For example, the processing module performs an iterative function that includes estimating a performance based on a set of compression parameters and adjusting the compression parameters to provide estimated performance that is substantially the same as the data access performance level. 
     The method continues at step  650  where the processing module selects sorted data entries of the plurality of sorted data entries based on the selected compression parameters to produce a data object. The selecting includes one or more of utilizing a number of entries from the compression parameters, selecting all entries from a previous recovery operation of an index node, selecting a first sorted subset, selecting a last sorted subset, and selecting a middle sorted subset. The processing module may initiate generating of another data object to store remaining sorted data entries. 
     The method continues at step  652  where the processing module compresses the data object to produce a compressed data object using the selected compression parameters. For example, the processing module applies a compression algorithm of the compression parameters to the data object to produce the compressed data object. the method continues at step  654  where the processing module disperse storage error encodes the compressed data object to produce one or more sets of encoded data slices for storage in a set of storage units. For example, the processing module encodes the compressed data object to produce one or more sets of encoded data slices, issues one or more sets of write slice requests that includes the one or more sets of encoded data slices to the set of storage units. When the other data object is generated, the processing module may encode the other data object to produce more sets of encoded data slices for storage in the set of storage units. 
     As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. Such an industry-accepted tolerance ranges from less than one percent to fifty percent and corresponds to, but is not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, and/or thermal noise. Such relativity between items ranges from a difference of a few percent to magnitude differences. As may also be used herein, the term(s) “operably coupled to”, “coupled to”, and/or “coupling” includes direct coupling between items and/or indirect coupling between items via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, and/or a module) where, for indirect coupling, the intervening item does not modify the information of a signal but may adjust its current level, voltage level, and/or power level. As may further be used herein, inferred coupling (i.e., where one element is coupled to another element by inference) includes direct and indirect coupling between two items in the same manner as “coupled to”. As may even further be used herein, the term “operable to” or “operably coupled to” indicates that an item includes one or more of power connections, input(s), output(s), etc., to perform, when activated, one or more its corresponding functions and may further include inferred coupling to one or more other items. As may still further be used herein, the term “associated with”, includes direct and/or indirect coupling of separate items and/or one item being embedded within another item. As may be used herein, the term “compares favorably”, indicates that a comparison between two or more items, signals, etc., provides a desired relationship. For example, when the desired relationship is that signal  1  has a greater magnitude than signal  2 , a favorable comparison may be achieved when the magnitude of signal  1  is greater than that of signal  2  or when the magnitude of signal  2  is less than that of signal  1 . 
     As may also be used herein, the terms “processing module”, “processing circuit”, and/or “processing unit” may be a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. The processing module, module, processing circuit, and/or processing unit may be, or further include, memory and/or an integrated memory element, which may be a single memory device, a plurality of memory devices, and/or embedded circuitry of another processing module, module, processing circuit, and/or processing unit. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. Note that if the processing module, module, processing circuit, and/or processing unit includes more than one processing device, the processing devices may be centrally located (e.g., directly coupled together via a wired and/or wireless bus structure) or may be distributedly located (e.g., cloud computing via indirect coupling via a local area network and/or a wide area network). Further note that if the processing module, module, processing circuit, and/or processing unit implements one or more of its functions via a state machine, analog circuitry, digital circuitry, and/or logic circuitry, the memory and/or memory element storing the corresponding operational instructions may be embedded within, or external to, the circuitry comprising the state machine, analog circuitry, digital circuitry, and/or logic circuitry. Still further note that, the memory element may store, and the processing module, module, processing circuit, and/or processing unit executes, hard coded and/or operational instructions corresponding to at least some of the steps and/or functions illustrated in one or more of the Figures. Such a memory device or memory element can be included in an article of manufacture. 
     The present invention has been described above with the aid of method steps illustrating the performance of specified functions and relationships thereof. The boundaries and sequence of these functional building blocks and method steps have been arbitrarily defined herein for convenience of description. Alternate boundaries and sequences can be defined so long as the specified functions and relationships are appropriately performed. Any such alternate boundaries or sequences are thus within the scope and spirit of the claimed invention. Further, the boundaries of these functional building blocks have been arbitrarily defined for convenience of description. Alternate boundaries could be defined as long as the certain significant functions are appropriately performed. Similarly, flow diagram blocks may also have been arbitrarily defined herein to illustrate certain significant functionality. To the extent used, the flow diagram block boundaries and sequence could have been defined otherwise and still perform the certain significant functionality. Such alternate definitions of both functional building blocks and flow diagram blocks and sequences are thus within the scope and spirit of the claimed invention. One of average skill in the art will also recognize that the functional building blocks, and other illustrative blocks, modules and components herein, can be implemented as illustrated or by discrete components, application specific integrated circuits, processors executing appropriate software and the like or any combination thereof. 
     The present invention may have also been described, at least in part, in terms of one or more embodiments. An embodiment of the present invention is used herein to illustrate the present invention, an aspect thereof, a feature thereof, a concept thereof, and/or an example thereof. A physical embodiment of an apparatus, an article of manufacture, a machine, and/or of a process that embodies the present invention may include one or more of the aspects, features, concepts, examples, etc., described with reference to one or more of the embodiments discussed herein. Further, from figure to figure, the embodiments may incorporate the same or similarly named functions, steps, modules, etc., that may use the same or different reference numbers and, as such, the functions, steps, modules, etc., may be the same or similar functions, steps, modules, etc., or different ones. 
     While the transistors in the above described figure(s) is/are shown as field effect transistors (FETs), as one of ordinary skill in the art will appreciate, the transistors may be implemented using any type of transistor structure including, but not limited to, bipolar, metal oxide semiconductor field effect transistors (MOSFET), N-well transistors, P-well transistors, enhancement mode, depletion mode, and zero voltage threshold (VT) transistors. 
     Unless specifically stated to the contra, signals to, from, and/or between elements in a figure of any of the figures presented herein may be analog or digital, continuous time or discrete time, and single-ended or differential. For instance, if a signal path is shown as a single-ended path, it also represents a differential signal path. Similarly, if a signal path is shown as a differential path, it also represents a single-ended signal path. While one or more particular architectures are described herein, other architectures can likewise be implemented that use one or more data buses not expressly shown, direct connectivity between elements, and/or indirect coupling between other elements as recognized by one of average skill in the art. 
     The term “module” is used in the description of the various embodiments of the present invention. A module includes a processing module, a functional block, hardware, and/or software stored on memory for performing one or more functions as may be described herein. Note that, if the module is implemented via hardware, the hardware may operate independently and/or in conjunction software and/or firmware. As used herein, a module may contain one or more sub-modules, each of which may be one or more modules. 
     While particular combinations of various functions and features of the present invention have been expressly described herein, other combinations of these features and functions are likewise possible. The present invention is not limited by the particular examples disclosed herein and expressly incorporates these other combinations.