Abstract:
A computer-executable method, computer program product, and system for managing metadata within a distributed data storage system, including a compute node in communication with a data storage array, the computer-executable method, computer program product, and system comprising receiving a data I/O from an application executing within the distributed data storage system, and creating a first storage system within the compute node, wherein the first storage system is enabled to manage metadata related to the data I/O, and processing the data I/O using the first storage system.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This Application claims priority from U.S. Provisional Patent Application Ser. Nos. 61/988,603 entitled “DISTRIBUTED DATA STORAGE MANAGEMENT” and 61/988,796 entitled “ZONE CONSISTENCY” filed on May 5, 2014 the content and teachings of which are hereby incorporated by reference in their entirety. 
     This Application is related to U.S. patent application Ser. No. 14/319,349 entitled “DISTRIBUTED DATA STORAGE MANAGEMENT”, Ser. No. 14/319,360 entitled “DISTRIBUTED METADATA MANAGMENT”, Ser. No. 14/319,378 entitled “DISTRIBUTED DATA STORAGE MANAGEMENT”, Ser. No. 14/319,383 entitled “DATA BACKUP MANAGEMENT ON DISTRIBUTED STORAGE SYSTEMS”, Ser. No. 14/319,113 entitled “ZONE CONSISTENCY”, and Ser. No. 14/319,117 entitled “ZONE CONSISTENCY” filed on even date herewith, the teachings of which applications are hereby incorporated herein by reference in their entirety. 
    
    
     A portion of the disclosure of this patent document may contain command formats and other computer language listings, all of which are subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever. 
     TECHNICAL FIELD 
     This invention relates to data storage. 
     BACKGROUND 
     Computer systems are constantly improving in terms of speed, reliability, and processing capability. As is known in the art, computer systems which process and store large amounts of data typically include a one or more processors in communication with a shared data storage system in which the data is stored. The data storage system may include one or more storage devices, usually of a fairly robust nature and useful for storage spanning various temporal requirements, e.g., disk drives. The one or more processors perform their respective operations using the storage system. Mass storage systems (MSS) typically include an array of a plurality of disks with on-board intelligent and communications electronics and software for making the data on the disks available. 
     Companies that sell data storage systems and the like are very concerned with providing customers with an efficient data storage solution that minimizes cost while meeting customer data storage needs. It would be beneficial for such companies to have a way for reducing the complexity of implementing data storage. 
     SUMMARY 
     A computer-executable method, computer program product, and system for managing metadata within a distributed data storage system, including a compute node in communication with a data storage array, the computer-executable method, computer program product, and system comprising receiving a data I/O from an application executing within the distributed data storage system, and creating a first storage system within the compute node, wherein the first storage system is enabled to manage metadata related to the data I/O, and processing the data I/O using the first storage system. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Objects, features, and advantages of embodiments disclosed herein may be better understood by referring to the following description in conjunction with the accompanying drawings. The drawings are not meant to limit the scope of the claims included herewith. For clarity, not every element may be labeled in every figure. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating embodiments, principles, and concepts. Thus, features and advantages of the present disclosure will become more apparent from the following detailed description of exemplary embodiments thereof taken in conjunction with the accompanying drawings in which: 
         FIG. 1  is a simplified illustration of a distributed data storage system, in accordance with an embodiment of the present disclosure; 
         FIG. 2  is a simplified illustration of a node within a cluster of a distributed data storage system, in accordance with an embodiment of the present disclosure; 
         FIG. 3  is a simplified illustration of a metadata in a distributed data storage system, in accordance with an embodiment of the present disclosure; 
         FIG. 4  is a simplified illustration of a scalable distributed data storage system, in accordance with an embodiment of the present disclosure; 
         FIG. 5  is a simplified illustration of management of data within a storage engine on a node of a distributed data storage system, in accordance with an embodiment of the present disclosure; 
         FIG. 6  is an alternate simplified illustration of metadata management within a storage engine of a node of a distributed data storage system, in accordance with an embodiment of the present disclosure; 
         FIG. 7  is a simplified flowchart of a method of managing metadata in the distributed data storage system of  FIG. 4 , in accordance with an embodiment of the present disclosure; 
         FIG. 8  is an example of an embodiment of an apparatus that may utilize the techniques described herein, in accordance with an embodiment of the present disclosure; and 
         FIG. 9  is an example of a method embodied on a computer readable storage medium that may utilize the techniques described herein, in accordance with an embodiment of the present disclosure. 
     
    
    
     Like reference symbols in the various drawings indicate like elements. 
     DETAILED DESCRIPTION 
     Traditionally, distributed data storage systems are tasked with managing larger and larger data set, often referred to as big data. Generally, to manage big data, a distributed data storage system creates metadata to enable the distributed data storage system to manage, store, and/or access the big data efficiently. Conventionally, as big data grows, so does its associated metadata, which can become unwieldy to manage by itself. Typically, improving the ability to manage metadata within a distributed data storage system would be beneficial to the data storage system industry. 
     In many embodiments, the current disclosure may enable creation of a distributed data storage system that may be enabled to manage large amounts of metadata associated with big data. In various embodiments, the current disclosure may enable a distributed data storage system to create one or more dynamically created sub-systems to manage metadata within a distributed data storage system. In most embodiments, the current disclosure may enable a distributed data storage system to utilize a storage engine to manage one or more layers (or abstractions) of metadata associated with data. In other embodiments, the current disclosure may enable a distributed data storage system to dynamically add or remove layers and/or levels of abstraction to manage metadata as the amount of metadata changes over time. 
     In many embodiments, a distributed data storage system may include one or more zones and/or clusters. In various embodiments, a zone and/or cluster may include one or more compute nodes and one or more data storage arrays. In certain embodiments, a zone and/or cluster may be enabled to communicate with one or more zones and/or clusters in the distributed data storage systems. In most embodiments, a zone and/or cluster may be enabled to manage and/or store data chunk format. In various embodiments, chunk format may include file and object storage formats. In other embodiments, chunk format may be portions of data storage of a specified size (i.e. 64 MB/125 MB). In certain embodiments, a zone may be a cluster. In some embodiments, a cluster may be a zone. In certain embodiments, a zone may include one or more clusters. 
     In most embodiments, a cluster may include one or more compute nodes and one or more data storage arrays. In various embodiments, a compute node may include a storage engine for manage data services, metadata, Quality of Service, and/or communication between one or more of the nodes in the distributed data storage system. In certain embodiments, applications may communicate with a node&#39;s storage engine to facilitate use of data storage within the distributed data storage system. 
     In many embodiments, a storage engine may include one or more layers. In various embodiments, layers within a storage engine may include a transaction layer, index layer, chunk management layer, storage server management layer, partitions record layer, and/or a storage server (Chunk I/O) layer. In certain embodiments, a transaction layer may parse received object request from applications within a distributed data storage system. In most embodiments, a transaction layer may be enable to read and/or write object data to the distributed data storage system. In some embodiments, data written to a distributed data storage system may be in a chunk format which may be portions of data storage of a specified size (i.e. 64 mb/128 mb). In many embodiments, an index layer may be enabled to map file-name/data-range to data stored within the distributed data storage system. In various embodiments, an index layer may be enabled to manage secondary indices which may be used to manage data stored on the distributed data storage system. 
     In many embodiments, a chunk management layer may manage chunk information, such as, but not limited to, location and/or management of chunk metadata. In various embodiments, a chunk management layer may be enabled to execute per chunk operations. In certain embodiments, a storage server management layer may monitor the storage server and associated disks. In most embodiments, a storage server management layer may be enabled to detect hardware failures and notify other management services of failures within the distributed data storage system. In some embodiments, a partitions record layer may record an owner node of a partition of a distributed data storage system. In many embodiments, a partitions record layer may record metadata of partitions, which may be in a btree and journal format. 
     In most embodiments, a storage server layer may be enabled to direct I/O operations to one or more data storage arrays within the distributed data storage system. In various embodiments, a chunk manager service may select which storage server may be utilized for received I/O requests. In certain embodiments, a storage server manager service may be utilized to select disks to be utilized on storage servers selected by the chunk manager service. In most embodiments, once a chunk manager server and storage server manager service has initially processed an I/O request, a transaction layer may be enabled to access one or more storage servers based on the chunk manager service and/or storage server manager service directives. 
     Refer to the example embodiment of  FIG. 1 .  FIG. 1  is a simplified illustration of a distributed data storage system, in accordance with an embodiment of the present disclosure. As shown, distributed data storage system  100  includes cluster  120  which includes Node ( 105 A-C,  105  Generally), and Data Storage Arrays ( 115 A-B,  115  Generally). Node  105 A is in communication with data storage array  115 A and Data storage Array  115 B. Node  105 B is in communication with data storage array  115 A and  115 B. Node  105 C is in communication with data storage array  115 A and Data storage Array  115 B. In  FIG. 1 , storage engine  110  is executed on each node  105 . storage engine  110  enables Applications  107 A,  109 A,  107 B,  109 B,  107 C,  109 C to execute data I/O requests to and from distributed data storage system  100 . In various embodiments, a distributed data storage system may include one or more clusters which may be located in one or more locations. 
     Refer to the example embodiment of  FIG. 2 .  FIG. 2  is a simplified illustration of a node within a cluster of a distributed data storage system, in accordance with an embodiment of the present disclosure. As shown, Node  200  executes storage engine  205 . Storage engine  205  includes multiple layers for management of node  200  within a distributed data storage system. Storage engine  205  includes transaction layer  210 , index layer  215 , chunk management layer  220 , storage server management layer  225 , partitions record layer  230 , and storage server layer  235 . One or more layers within storage engine  205  on node  200  are enabled to communicate with other nodes in a cluster of distributed data storage systems. In various embodiments, one or more layers within a storage engine on a node may be enabled to communicate with other nodes in one or more other clusters of a distributed data storage system. 
     Refer to the example embodiment of  FIG. 3 .  FIG. 3  is a simplified illustration of a metadata in a distributed data storage system, in accordance with an embodiment of the present disclosure. As shown, Node  305  is part of distributed data storage system  300 . Node  305  manages partition  310  and includes storage engine  307 . Partition  310  includes metadata  312  which is stored using Btree  315  and journal  320 . Metadata  312  is stored on chunks ( 325 A-C,  325  Generally). Chunks  325  are stored throughout distributed data storage system  300 . In most embodiments, chunks of data may include data stored in file, object, and or other data storage formats. In various embodiments, a chunk may mean a specified amount of data storage within a distributed data storage system. In this embodiment, storage engine  307  manages placement and/or stores the location of partition  310 . 
     Refer to the example embodiment of  FIG. 4 .  FIG. 4  is a simplified illustration of a scalable distributed data storage system, in accordance with an embodiment of the present disclosure. As shown, Node  405  includes storage engine  410  and is in communication with data storage array  450 A and data storage array  450 B. Storage engine  410  is enabled to manage multiple levels of data and/or metadata within storage engine  410 . In this embodiment, storage engine includes storage systems ( 440 A-N,  440  Generally). Storage system  440 A includes chunk management  425 A, storage server management  430 A, and partitions record  435 A. Storage system  440 B includes Chunk management  425 B, storage server management  430 B, and partitions record  435 B. Storage system  440 N includes chunk management  425 N, storage server management  430 N, and Partitions record  435 N. In most embodiments, a storage engine may be enabled to create one or more storage systems to manage metadata managed by a storage engine. In some embodiments, metadata created from managing data may be so difficult, that the metadata created may be managed by a secondary instantiation of a storage system to manage the metadata. In various embodiments, a secondary instantiation of a storage system may create secondary metadata to manage the first level of metadata created. In Most embodiments, where distributed data storage system may operate on big data sets, a distributed data storage system may need to create multiple instantiations of a storage system to reduce created metadata to a manageable amount of data. 
     In this embodiment, storage system  440 A is in communication with storage server Layer  440  and storage system  440 B. Storage system  440 B is in communication with storage system  440 A, storage server layer  440 , and is enabled to connect to storage system  440 N. Storage system  440 N is in communication with Storage system  440 B and storage server layer  440 . In various embodiments, a storage engine may include multiple storage systems which may be enabled to manage portions of the data managed within a given node. In this embodiment, storage system  440 A is enabled to store data on data storage array  450 A and/or data storage array  450 B. Storage system  440 A is enabled to manage a portion of the data storage system  440 A manages using storage system  440 B. Storage system  440 B is enabled to store data on data storage array  450 A and data storage array  450 B. Storage system  440 B is enabled to manage a portion of the data stored by storage system  440 B using storage system  440 N. In many embodiments, one or more storage systems may be use to portion data storage within a distributed data storage system into smaller manageable portions. 
     Refer to the example embodiment of  FIG. 5 .  FIG. 5  is a simplified illustration of management of data within a storage engine on a node of a distributed data storage system, in accordance with an embodiment of the present disclosure. In this embodiment, distributed data storage system  500  includes node  502 , which includes storage engine  504 . Storage engine  504  is enabled to manage data  505  and associated metadata. As shown, storage engine  504  created metadata  510 , which includes object data  515  and listing data  520  and/or information relating to the portion of data storage within distributed data storage system  500  that data  505  is stored. Storage engine  504  has determined that metadata  510  exceeds a threshold size of metadata to be managed and creates metadata  550  to manage metadata  510 . Metadata  550  includes partitions records data  535 , chunk manager data  540 , and storage server manager data  545 , and other data related to storage of metadata  510 . 
     Refer to the example embodiment of  FIG. 6 .  FIG. 6  is an alternate simplified illustration of metadata management within a storage engine of a node of a distributed data storage system, in accordance with an embodiment of the present disclosure. As shown, distributed data storage system  600  includes node  602 . Node  602  includes storage engine  604 . In this embodiment, storage engine  604  receives data  605  and creates metadata  610 , which includes object table  615  and listing table  620 . Storage engine determines that the size of metadata  610  exceeds a threshold size and creates metadata  650  to manage metadata  610 . Metadata  650  includes partitions records data  635 , chunk manager data  640 , and storage server manager data  645 . Storage engine  604  again determines that Metadata  650  exceeds a threshold size and creates metadata  675  to manage metadata  650 . Metadata  675  includes partitions records data  660 , chunk manager data  665 , and storage server manager data  670 . In many embodiments, a user and/or administrator may direct a storage engine to create one or more levels within the storage engine to manage metadata. In various embodiments, a user and/or administrator may direct a storage engine to create a level of metadata management for metadata exceeding a specified size and/or other data storage characteristic trait. 
     Refer to the example embodiments of  FIGS. 4 and 7 .  FIG. 7  is a simplified flowchart of a method of managing metadata in the distributed data storage system of  FIG. 4 , in accordance with an embodiment of the present disclosure. In  FIG. 4 , distributed data storage system  400  includes node  405 , data storage array  450 A and data storage array  450 B. Node  405  includes storage engine  410 . Storage engine includes object system  420 , storage systems ( 440 A-N,  440  Generally), and storage server Layer  440 . Object system  420  receives data I/Os from applications operating using node  405  (Step  700 ). Object system  420  utilizes transaction layer  415  to direct the received I/O to storage system  440 A, which creates metadata for received data I/O (Step  710 ) using chunk management  425 A, storage management  430 A, and partitions record  435 A. Storage system  440 A stores received I/Os and associated metadata on either data storage array  450 A or data storage array  450 B using storage server layer  440 . Storage engine  410  analyzes created metadata to determine whether created metadata exceeds a specified threshold for further management (Step  720 ). Upon a positive determination, storage engine  410  creates storage system  440 B which is enabled to manage metadata created by storage system  440 A. Storage system  440 B utilizes chunk management  425 B, storage server management  430 B, and partitions record  435 B to create metadata on metadata created by storage system  440 A (Step  730 ). Storage system  440 B stores metadata created at storage system  440 B on either data storage array  450 A or data storage array  450 B using storage server layer  440 . Upon a negative determination, storage engine  410  maintains the current allocation of storage systems  440 . In many embodiments, if the amount of metadata managed by a storage engine is reduced, a storage engine may remove one or more dynamically created storage systems. 
     The methods and apparatus of this invention may take the form, at least partially, of program code (i.e., instructions) embodied in tangible non-transitory media, such as floppy diskettes, CD-ROMs, hard drives, random access or read only-memory, or any other machine-readable storage medium. 
       FIG. 8  is a block diagram illustrating an apparatus, such as a computer  810  in a network  800 , which may utilize the techniques described herein according to an example embodiment of the present invention. The computer  810  may include one or more I/O ports  802 , a processor  803 , and memory  804 , all of which may be connected by an interconnect  825 , such as a bus. Processor  803  may include program logic  805 . The I/O port  802  may provide connectivity to memory media  883 , I/O devices  885 , and drives  887 , such as magnetic or optical drives. When the program code is loaded into memory  804  and executed by the computer  810 , the machine becomes an apparatus for practicing the invention. When implemented on one or more general-purpose processors  803 , the program code combines with such a processor to provide a unique apparatus that operates analogously to specific logic circuits. As such, a general purpose digital machine can be transformed into a special purpose digital machine. 
       FIG. 9  is a block diagram illustrating a method embodied on a computer readable storage medium  960  that may utilize the techniques described herein according to an example embodiment of the present invention.  FIG. 9  shows Program Logic  955  embodied on a computer-readable medium  960  as shown, and wherein the Logic is encoded in computer-executable code configured for carrying out the methods of this invention and thereby forming a Computer Program Product  900 . Program Logic  955  may be the same logic  805  on memory  804  loaded on processor  803  in  FIG. 8 . The program logic may be embodied in software modules, as modules, as hardware modules, or on virtual machines. 
     The logic for carrying out the method may be embodied as part of the aforementioned system, which is useful for carrying out a method described with reference to embodiments shown in, for example,  FIGS. 1-9 . For purposes of illustrating the present invention, the invention is described as embodied in a specific configuration and using special logical arrangements, but one skilled in the art will appreciate that the device is not limited to the specific configuration but rather only by the claims included with this specification. 
     Although the foregoing invention has been described in some detail for purposes of clarity of understanding, it will be apparent that certain changes and modifications may be practiced within the scope of the appended claims. Accordingly, the present implementations are to be considered as illustrative and not restrictive, and the invention is not to be limited to the details given herein, but may be modified within the scope and equivalents of the appended claims.