Patent Publication Number: US-11023340-B2

Title: Layering a distributed storage system into storage groups and virtual chunk spaces for efficient data recovery

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     The present application is a continuation of U.S. patent application Ser. No. 16/210,718, filed Dec. 5, 2018, which is a continuation of U.S. patent application Ser. No. 15/890,913, filed Feb. 7, 2018, which is a division of U.S. patent application Ser. No. 14/696,001, filed Apr. 24, 2015 now U.S. Pat. No. 9,921,910 issued on Mar. 20, 2018, the disclosures of which are incorporated by reference herein in their entirety. 
    
    
     TECHNICAL FIELD 
     Several of the disclosed embodiments relate to distributed data storage services, and more particularly, to storing data in a distributed data storage system using virtual chunk services 
     BACKGROUND 
     In distributed data storage systems, various methods can be used to store data in a distributed manner, e.g., to improve data reliability, protection. Erasure coding is one such method of data protection in which a data object is broken into fragments, encoded with parity information and stored across a set of different storage nodes in the distributed data storage system. When a data object is erasure coded, the distributed data storage system has to typically store the storage information in its metadata. This metadata can include identities of the storage nodes that store each fragment of the encoded data object. When a storage node in the distributed data storage system fails, all the objects that were stored in that storage node have to be discovered and repaired, so that the reliability is not compromised. 
     For recovering the lost data, the distributed data storage system may have to go through the metadata of all the data objects to identify the data objects impacted by the failed node. Then alternate nodes are selected to move the fragments. After the fragments are moved, the metadata of each moved object should be updated to reflect the new set of storage nodes that the fragments of the objects are stored in. This approach can be resource intensive and can have the following performance bottlenecks: (a) metadata query for each object to find if it is impacted and (b) metadata update for each impacted object after repair due to node or volume loss. This can be a resource intensive process as the distributed data storage system can have a significantly large number of data objects, e.g., billions of data objects. Further, reading such significantly large number of data objects to identify a subset of them that are stored on the failed node, which can be a small the fraction of entire number of data objects is inefficient. In a system with billions of data objects, with each node storing millions of fragments, both these can cause serious performance issues for the recovery process. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating an environment in which the disclosed embodiments can be implemented. 
         FIG. 2A  is a block diagram illustrating a virtual chunk service (VCS) layout of a distributed storage of  FIG. 1 , consistent with various embodiments. 
         FIG. 2B  is an example describing various layers of the VCS layout. 
         FIG. 3  is a block diagram of a process for erasure coding a data object using a “2+1” erasure coding scheme, consistent with various embodiments. 
         FIG. 4  is a block diagram illustrating an arrangement of storage nodes of a distributed storage system at various sites, consistent with various embodiments. 
         FIG. 5  is a block diagram illustrating an example grouping scheme, consistent with various embodiments. 
         FIG. 6  is a block diagram illustrating an example of the VCS storage layout for storing data objects encoded using “2+1” erasure coding scheme, consistent with various embodiments. 
         FIG. 7  is a table of storage nodes and erasure coding groups showing data fragments of different objects stored at different storage nodes, consistent with various embodiments. 
         FIG. 8  is a flow diagram of a process for writing a data object to the distributed storage of  FIG. 1 , consistent with various embodiments. 
         FIG. 9  is a flow diagram of a process for reading data from the distributed storage of  FIG. 1 , consistent with various embodiments. 
         FIG. 10  is a flow diagram of a process for recovering lost data in the distributed storage of  FIG. 1 , consistent with various embodiments. 
         FIG. 11  is a flow diagram of a process for configuring a VCS storage layout of the distributed storage of  FIG. 1 , consistent with various embodiments. 
         FIG. 12  is a block diagram of a computer system as may be used to implement features of some embodiments of the disclosed technology. 
     
    
    
     DESCRIPTION 
     Technology is disclosed for virtual chunk service (VCS) based data storage in a distributed data storage system (“the technology”). The VCS based storage technique can improve efficiency in data storage and retrieval in the distributed data storage system (“distributed storage”) while also facilitating data protection mechanisms. For example, the VCS based storage technique can be used in conjunction with an erasure coding method, which is typically an encoding scheme used for providing data protection and/or reliability. The VCS based storage technique, when used with the erasure coding method, can improve the efficiency in data recovery, e.g., by minimizing the computing resources used for recovering the lost data. 
     In the VCS based storage technique, a storage node (“node”), which is a computing device that facilitates storage of data in a persistent storage medium, contains a chunk service which is split into multiple VCSs and each of the VCSs can be assigned a unique ID in the distributed storage. A VCS is the smallest unit of a failure domain within a chunk service of the node. The unique ID of the VCS does not change during its lifetime. A set of VCSs from a set of nodes form a data storage group (“storage group”), which also can be assigned a unique ID in the distributed storage. When a data object is received for storage in the distributed storage, a storage group can be identified for the data object, the data object can be fragmented into multiple fragments and each fragment can be stored in a VCS of the identified storage group. For example, if a data object is stored using erasure coding method, the VCS based storage technique creates an erasure coding group (“ECG”) as a storage group and associates a set of VCSs from a set of nodes with the ECG. When a data object is received for storage, the data object is erasure coded into multiple fragments and each fragment is stored in a VCS of the selected ECG. 
     The VCS based storage technique maintains metadata of the data objects stored in the distributed storage, which can be used to access data and/or recover lost data efficiently. A metadata service can be used in the distributed storage to maintain the metadata. The metadata can include a mapping of the VCS to a storage node, which identifies a storage node a specified VCS belongs to or is hosted on. The metadata can also include a mapping of the ECG to the VCSs, which identifies a list of specified VCSs associated with an ECG. The metadata can also include a listing of the data objects stored in each of the VCSs. In some embodiments, the metadata service can also maintain a mapping of the ECGs to the data objects, which identifies an ECG in which a specified data object is stored, with which the VCSs having the data fragments of the data object can be derived. 
     When a data loss is experienced, e.g., due to a node failure, the data in the failed node can be recovered using the above metadata. For example, when a node fails, the VCSs on the node can be identified, e.g., using the VCS to storage node mapping, the affected ECGs can be identified, e.g., using the ECG to VCSs mapping, and then the data objects stored in the identified VCSs can be identified, e.g., using a listing of the data objects stored in each of the VCSs. The VCS based storage technique moves the group of VCSs from the failed node to an alternate node, reconstructs a data object stored in a VCS on the failed node using the remaining VCSs of the ECG to which the data object belongs, fragments the reconstructed data object into multiple fragments, and sends a fragment to the VCS that is moved to the alternate node. The VCS to storage node mapping is updated to indicate that the VCSs have been moved to the alternate node. 
     The data recovery process described above may not have to update the metadata of the impacted data objects as the fragments of those data objects are still stored in the same VCSs as before the failure; only the VCS storage node mapping may need to be updated as the VCSs are moved to the alternate node. Therefore, by eliminating the need to update the metadata of all the impacted data objects, the VCS based storage technique minimizes the computing resources consumed for updating the metadata, thereby improving the efficiency of a data recovery process. Further, since the data objects stored on the failed node can be identified using the VCS-storage node mapping and a VCS to data objects mapping, the process can eliminate the need to read the metadata of all the data objects to determine if a fragment of the data object is stored in the failed node, thereby saving the computing resources required for performing the read operation. 
     Although the document describes the VCS based storage technique in association with erasure coding method, it should be noted that the VCS based storage technique can be used with other data protection mechanisms, e.g., data replication. 
     Environment 
       FIG. 1  is a block diagram illustrating an environment  100  in which the disclosed embodiments can be implemented. The environment  100  includes a data management system  110  that provides data storage services, e.g., writing a data object to the distributed storage  150  and reading a data object from the distributed storage  150 . The distributed storage  150  can include multiple storage nodes, e.g., nodes “N 1 ”-“N 9 .” Each storage node can be associated with one or more persistent storage devices to store the data object. In some embodiments, the persistent storage device can include storage media such as hard disk drives, magnetic tapes, optical disks such as CD-ROM or DVD based storage, magneto-optical (MO) storage, flash based storage devices such as solid state drives (SSDs), or any other type of non-volatile storage devices suitable for storing large quantities of data. The nodes can be distributed geographically. For example, a set of nodes “N 1 ”-“N 3 ” can be in a first location  135 , “N 4 ”-“N 6 ” can be in a second location  130  and “N 7 ”-“N 9 ” can be in a third location  125 . Further, different locations can have different number of nodes. 
     In some embodiments, the above described VCS based storage technique can be implemented using the data management system  110 . Further, the VCS based storage technique can be implemented in association with the erasure coding method of storing the data. In some embodiments, the erasure coding method involves transforming a set of “k” fragments  115  of a data object, e.g., data object  105 , into “n” erasure coded (“EC”) fragments  120  by adding “m” parity fragments, where “n=k+m” (thus referred to as “k+m” erasure coding scheme). Some examples of “k+m” erasure coding scheme include “2+1”, “6+3” and “8+2” erasure coding schemes. The data object  105  can be regenerated using a subset of the EC fragments  120 . The “n” number of data fragments is spread across different nodes in a site and/or across sites. After the EC fragments  120  are generated, the EC fragments  120  are distributed to separate storage nodes for storage. 
     The data management system  110  enables implementing the VCS based storage technique in association with the erasure coding method. The data management system  110  organizes the distributed storage  150  into multiple logical layers, e.g., an ECG, one or more VCSs that belong to a specified ECG, and stores the EC fragments in a set of nodes having a set of VCSs of the specified ECG. Such storage of the data object enables data to be written, read and recovered in an event of data loss efficiently. In some embodiments, after a data object is stored in the distributed storage  150 , the data management system generates various metadata. The metadata can include a mapping of the VCS to a storage node, which identifies a storage node a specified VCS belongs to or is hosted on. The metadata can also include a mapping of the ECG to the VCSs, which identifies a list of specified VCSs associated with an ECG. The metadata can also include a mapping of the VCS to data objects, which indicates the data objects (whose data fragments are) stored in a VCS. In some embodiments, the metadata service can also maintain a mapping of the ECGs to the data objects, which indicates the data objects stored in an ECG. 
       FIG. 2A  is a block diagram illustrating a VCS layout of a distributed storage of  FIG. 1 , consistent with various embodiments.  FIG. 2B  is an example describing various layers of the VCS layout  200 . A node can include or be considered as a chunk service, which can store a number of data chunks or fragments. The chunk service can be logically split into a specified number of virtual chunk spaces. Virtual chunk spaces are also referred to as virtual chunk services (VCSs). A VCS is the smallest unit of a failure domain within the chunk service and will have a unique identification (ID) which never changes during its lifetime. A set of VCSs spanning multiple storage nodes form an ECG. The size of a VCS can be determined in various ways, e.g., as a function of the erasure coding method used, number of storage nodes in the distributed storage  150 , typical size of data objects stored in the distributed storage  150 , etc. The number of VCSs in a storage node can also be determined in various ways, e.g., storage capacity of a storage node, storage capacity of the distributed storage  150 , number of storage nodes. 
     Referring to  FIG. 2A , the VCS layout  200  describes the layers in detail. The node  220  contains a chunk service  225 . In some embodiments, the node  220  can be similar to one of the storage nodes in the distributed storage  150  of  FIG. 1 . The chunk service  225  on the node  220  can contain a set of VCSs  215 . An ECG  205  can contain a set of VCSs, such as VCSs  215 , spanning multiple nodes. For example, a first ECG contains a VCS each from node “N 1 ,” “N 4 ” and “N 5 .” Different ECGs can be formed based on a grouping profile or scheme  210 . That is, the set of VCSs for a specified ECG can be selected from a specified set of nodes based on the grouping scheme  210 . Further, the number of VCSs in the ECG can also be selected based on the grouping scheme  210 . For example, the grouping scheme  210  can indicate that for a data object, e.g., data object  230 , that is erasure coded using a “2+1” erasure coding scheme, an ECG should have three VCSs, one each from one of the nodes from a first location  135 , a second location  130  and the third location  125 . For example, the ECG contains a VCS each from node “N 1 ,” “N 4 ” and “N 5 .” In another example, if the erasure coding scheme used to store the data object is  230 , is “6+3” erasure coding scheme, then the grouping scheme  210  can indicate that the ECG should have “9” VCSs, one from each of the nodes “N 1 ”-“N 9 .” 
     The data object can split into a number of slices or stripes  235 , each stripe having a specified number of data fragments that is determined based on the erasure coding scheme. For example, in a “2+1” erasure coding, the stripe width is three, which means each stripe of the data object has “3” fragments  240 , out of which “2” fragments are data fragments  250  and “1” fragment is a parity fragment  245 . After the data object is erasure coded, the EC fragments of the data object  230  are stored in separate VCSs of the ECG group to which the data object is assigned, e.g., based on the grouping scheme  210 . 
       FIG. 3  is a block diagram of a process for erasure coding a data object using a “2+1” erasure coding scheme  300 , consistent with various embodiments. In some embodiments, the data object  305  can be similar to the data object  105  of  FIG. 1 . The data object  305  can include “6” bytes of data. The data object  305  can be erasure coded using “2+1” erasure coding scheme. In some embodiments, “2+1” means “2” data and “1” parity fragments in a stripe. Using a 1 Byte fragment size, the data object  305  can be split into “3” stripes and “9” EC fragments  310  as illustrated. In the “2+1” scheme, 2 bytes/fragments are considered at a time and a third byte/fragment is added as parity to generate a stripe. 
     The EC fragments  310  can then be stored in VCSs of an ECG that can span multiple nodes, which can be situated in different geographical locations. In some embodiments, the EC fragments  310  can be similar to the EC fragments  120  of  FIG. 1 .  FIG. 4  is a block diagram illustrating arrangement  400  of nodes at various sites, consistent with various embodiments. In the arrangement  400 , “6” nodes are located at various sites. For example, storage nodes “SN 1 ” and “SN 2 ” are located at site A, storage nodes “SN 3 ” and “SN 4 ” are located at site B, and storage nodes “SN 5 ” and “SN 6 ” are located at site C. 
     A data management system, e.g., the data management system  110  of  FIG. 1 , can generate various ECGs that spread across various storage nodes in the arrangement  400 , e.g., based on a grouping scheme.  FIG. 5  is a block diagram  500  illustrating an example grouping scheme  505 , consistent with various embodiments. In some embodiments, the grouping scheme  505  can select the sites and the number of storage nodes based on the erasure coding scheme used. The data management system  110  can define a number of grouping schemes. For example, the data management system  110  can define a grouping scheme  505  that forms a storage pool by selecting a storage node from each of the sites A, B and C and to store data objects that are erasure coded using “2+1” erasure coding scheme. The data management system  110  can generate various ECGs per grouping scheme  505 . 
     Note that the “2+1” erasure coding scheme  300  is described for illustration purposes. The data object  305  can be erasure coded using other “k+m” erasure coding schemes. 
       FIG. 6  is a block diagram illustrating an example  600  of the VCS storage layout for storing data objects encoded using “2+1” erasure coding scheme, consistent with various embodiments. In the example  600 , for the grouping scheme  505 , the data management system  110  has generated a number of ECGs  610 , e.g., “ECG  1 ” and “ECG  2 .” Further, “ECG  1 ” is allocated “3” VCSs  620  required for a “2+1” erasure coding scheme, e.g., “VCS  1 ,” “VCS  2 ,” and “VCS  3 ” from storage nodes  625  “SN 1 ”, “SN 3 ” and “SN 5 ,” respectively. Note that the VCSs  620  for “ECG  1 ” are from storage nodes  625  at different sites, per the grouping scheme  505 . Similarly, “ECG  2 ” is allocated “3” VCSs, e.g., “VCS  4 ,” “VCS  5 ,” and “VCS  6 ” from storage nodes “SN 1 ”, “SN 3 ” and “SN 5 ,” respectively. The storage nodes  625  can be similar to one or more of the storage nodes in the arrangement  400  of  FIG. 4 . 
     After the VCS storage layout is determined, the data management system  110  can generate various mappings, e.g., as metadata. The metadata can include a mapping of the VCS to a storage node, which identifies a storage node a specified VCS belongs to. For example, referring to the VCS storage layout of example  600 , the VCS-&gt;node mapping for storage node “SN  1 ” can include “SN  1 -&gt;VCS  1 , VCS  4  . . . ” or “VCS  1 -&gt;SN  1 ” “VCS  4 -&gt;SN  1 ” etc. The metadata can also include a mapping of the ECG to the VCSs, which identifies a list of specified VCSs associated with an ECG. For example, referring to example  600 , the ECG-&gt;VCS mapping for “ECG  1 ” can include “ECG  1 -&gt;VCS  1 , VCS  2 , VCS  3 .” 
     The data management system  110  assigns a data object to a particular ECG, and stores all stripes of the data object in the same ECG. However, each fragment is stored in a separate VCS of the ECG. For example, referring to the data object  305  of  FIG. 3 , if the data object  305  is assigned to “ECG  1 ,” then each fragment of a stripe is stored in a separate VCS—data fragment “a” in “VCS  1 ,” data fragment “b” in “VCS  2 ,” and data fragment “!” in “VCS  3 .” All other stripes of the data object  305  can be stored in “ECG  1 ” similarly. 
     The data management system  110  can also generate metadata for the data storage object, which indicates the list of objects or fragments of the object in a specified VCS. For example, if data objects “Obj  1 ,” “Obj  2 ,” “Obj  3 ,” and “Obj  4 ” are stored in the VCSs of “ECG  1 ,” then a VCS-&gt;Obj mapping can include “VCS  1 -&gt;Obj  1 , Obj  2 , Obj  3 , Obj  4 ”. In some embodiments, the metadata service can also maintain a mapping of the data objects to the ECGs, which identifies an ECG in which a specified data object is stored. Continuing with the above example of storing data objects “Obj  1 ”-“Obj  4 ” in “ECG  1 ,” an ECG-&gt;Obj mapping can include “ECG  1 -&gt;Obj  1 , Obj  2 , Obj  3 , Obj  4 ”. 
       FIG. 7  is a table  700  of storage nodes and ECGs showing data fragments of different objects stored at different storage nodes, consistent with various embodiments. In the table  700 , various ECGs are assigned VCSs from various storage nodes. For example, “EC Group  1 ” is allocated “3” VCSs, e.g., from storage nodes “SN 1 ”, “SN 3 ” and “SN 5 ,” respectively. Similarly, “EC Group  2 ” is allocated “3” VCSs, e.g., from storage nodes “SN 1 ”, “SN 3 ” and “SN 6 ” respectively. 
       FIG. 8  is a flow diagram of a process  800  for writing a data object to the distributed storage of  FIG. 1 , consistent with various embodiments. In some embodiments, the process  800  can be implemented in the environment  100  of  FIG. 1  and using the data management system  110 . At step  1 , a content management service (CMS) module  805  associated with the data management system  110  initiates a write operation for a data object, e.g., data object  305 . In some embodiments, the CMS module  805  directs placement of objects into the distributed data storage system. In some embodiments, the CMS module  805  can include information regarding the grouping scheme to be applied to the data object. In some embodiments, the grouping scheme may be determined by the CMS module  805  based on a type of application issuing the write request, a type of the data object, etc. In some embodiments, the grouping scheme can be defined by a user, e.g., an administrator of the data management system  110 , and stored in the form of a data protection policy. At step  2 , an EC module  810  associated with the data management system  110  obtains, e.g., from an EC group manager  815 , an ECG that satisfies the provided grouping scheme, e.g., “ECG 1 ”. In some embodiments, the EC group manager  815  generates the ECGs, e.g., ECGs  610 , based on the grouping scheme. At step  3 , the EC module  810  retrieves the data object, e.g., from a replication storage service, from one or more sources where the data object is stored, e.g., the data object  305  to be erasure coded. 
     At step  4 , the EC module  810  erasure codes the data object, e., based on a erasure coding scheme to generate the EC fragments, e.g., EC fragments  310 , and transmits the EC fragments to the VCSs of the selected ECG. The chunk service on the storage nodes that are part of the selected ECG receives the VCSs and stores at them at the persistent storage medium associated with the storage nodes. At step  5 , upon successful writing of the EC fragments to the VCSs, the EC module  810  can send a success message to the CMS module  805 . In some embodiments, the EC module  810  also provides the IDs of the VCSs where the data object fragments are stored to the CMS module  805 , e.g., as part of the success message. At step  6 , the CMS module  805  provides the VCSs and/or the ECG information of the data object to a metadata service, e.g., a distributed data service (DDS) module  820 , to update the metadata, e.g., in a metadata store. The metadata can include the IDs of the VCSs and/or the ECG where the data object fragments are stored. In some embodiments, the CMS module  805  can update the metadata of the data object in the metadata store without using the DDS module  820 . 
       FIG. 9  is a flow diagram of a process  900  for reading data from the distributed storage of  FIG. 1 , consistent with various embodiments. In some embodiments, the process  900  may be implemented in environment  100  of  FIG. 1 . At step  1 , the EC module  810  receives a read request from a requesting entity for retrieving a data object. In some embodiments, the read request includes the object ID of the data object and/or the ECG ID of the ECG to which the data object is assigned. In some embodiments, the requesting entity can be a client computer (“client”) which sends the read and/or write request using one or more protocols, e.g., hyper-text transfer protocol (HTTP). 
     At step  2 , the EC module  810  obtains the IDs of the VCSs in which the data object is stored, e.g., from the EC group manager  815 . In some embodiments, the EC group manager  815  uses the DDS module  820  to obtain the VCSs storing the data object. The DDS module  820  can identify the VCSs in which the data object is stored by searching the ECG&gt;VCS mapping and/or the VCS-&gt;object mapping metadata using the object ID and any ECG ID provided in the request. 
     After identifying the VCSs, at step  3 , the EC module  810  obtains all or a subset of the data fragments of the data object from the identified VCSs. At step  4 , the EC module  810  decodes the data fragments, e.g., based on the erasure coding scheme used to encode the data object, to reconstruct the data object, and returns the reconstructed data object to the requesting entity. 
     Note that the data management system  110  can include additional modules or lesser number of modules than illustrated in  FIGS. 8 and 9 . For example, the additional modules can perform other functionalities than described above. In another example, the functionalities of one or more of the above modules can be split into two or more additional modules. Further, functionalities of two or more modules can be combined into one module. 
       FIG. 10  is a flow diagram of a process  1000  for recovering lost data in the distributed storage of  FIG. 1 , consistent with various embodiments. In some embodiments, the process  1000  may be implemented in environment  100  of  FIG. 1 . The data in the distributed storage  150  can be lost due to various reasons, e.g., failure of a storage node, failure of a portion of the storage node, failure of a site. For the sake of convenience, the data recovery process  1000  is described with respect to data loss due to a failure of a storage node in the distributed storage  150 . However, the process  1000  can be implemented for other types of data losses as well. The process  1000  begins at block  1005 , and at block  1010 , the EC module  810  identifies a storage node that has failed in the distributed storage  150  (“failed storage node”). 
     At block  1015 , the EC module  810  identifies the VCSs that are associated with the failed storage node using the metadata. For example, the EC module  810  requests the DDS module  820  to obtain the IDs of the VCSs associated with failed storage node, and the DDS module  820  uses the metadata, e.g., VCS to storage node mapping described above, to obtain the VCS IDs. 
     At block  1020 , the EC module  810  identifies the ECGs that are affected due to storage node failure. In some embodiments, the EC module  810  requests the DDS module  820  to obtain the IDs of the ECG associated with the storage node. The DDS module  820  can use the IDs of the VCSs identified in the block  1015  to identify the affected ECGs, e.g., based on the ECG to VCS mapping metadata. 
     At block  1025 , the EC module  810  reassigns the VCSs of the affected ECGs to an alternate node(s). In some embodiments, reassigning the VCSs to the alternate node can include reassigning the VCSs on the failed storage node to the alternate node such that this reassignment continues to satisfy the data protection requirements of the ECG. These reassigned VCSs can start off empty until data fragments that belonged to them before the storage node failure are regenerated, e.g., as described in block  1035 . 
     At block  1030 , the EC module  810  identifies the objects whose fragments are stored in the VCSs (and/or ECGs) of the failed storage node, e.g., using the VCS-&gt;object mapping metadata and/or ECG-&gt;object mapping metadata. Recall, e.g., from  FIG. 8 , that when the data object is stored in the distributed storage  150 , the object metadata is updated to indicate the VCSs in which the fragments of the data object are stored. 
     After identifying the data objects whose fragments are stored in the affected VCSs, at block  1035 , the EC module  810  executes a data recovery process. The data recovery process can include executing erasure coding algorithm on the data object fragments stored in the VCSs to reconstruct the data objects and then to regenerate the data fragments by erasure coding the reconstructed data objects. 
     At block  1040 , the EC module  810  stores the data fragments of the data objects in the respective VCSs in the alternate node. 
     At block  1045 , the DDS module  820  can update the VCSs to storage node mapping to indicate that the VCSs have been moved to the alternate node, and the process  1000  returns. In some embodiments, the EC module  810  can send a success message to the CMS module  805  along with one or more of object ID, VCS ID and storage node ID. The CMS module  805  can then instruct the DDS module  820  to update the VCSs to storage node mapping accordingly. 
     Referring back to blocks  1035  and  1040 , in some embodiments, the data management system  110  can reconstruct all the data objects stored in the affected ECGs by one ECG at a time and one stripe of a data object at a time. The reconstructed stripes can be erasure encoded to regenerate data fragments belonging to the VCSs that were reassigned in block  1025  after the storage node failure. In some embodiments, the blocks  1035  and  1040  are executed serially for each stripe of every ECG to be repaired. 
     The data recovery process described above may not have to update the metadata of the impacted data objects as the fragments of those data objects are still stored in the same VCSs as before the failure; only the VCS storage node mapping may need to be updated as the VCSs are moved to the alternate node. Therefore, by eliminating the need to update the metadata of all the impacted data objects, the VCS based storage technique minimizes the computing resources consumed for updating the metadata, thereby improving the efficiency of a data recovery process. Further, since the data objects stored on the failed node can be identified using the VCS-&gt;storage node mapping and VCS-&gt;data objects mapping, the process can eliminate the need to read the metadata of all the data objects to determine if a fragment of the data object is stored in the failed node, thereby saving the computing resources required for performing the read operation. 
       FIG. 11  is a flow diagram of a process  1100  for configuring a VCS storage layout of the distributed storage of  FIG. 1 , consistent with various embodiments. In some embodiments, the process  1100  may be implemented in environment  100  of  FIG. 1 . The process  1100  begins at block  1105 , and at block  1110 , the EC group manager  815  receives a storage grouping scheme, e.g., grouping scheme  505 , for configuring the distributed storage  150 . In some embodiments, the grouping scheme  505  can include information regarding storage nodes, e.g., the storage sites to be selected for a storage group, the number of storage nodes to be selected and the number of storage nodes to be selected from a storage site. In some embodiments, the grouping scheme define the selection of the storage sites and/or nodes based on an erasure coding scheme to be used. For example, the grouping scheme  505  indicates that for a “2+1” erasure coding scheme, a storage pool is to be created by selecting a node from each of the sites A, B and C, which means that an object erasure coded using “2+1” erasure coding scheme is to be stored at the selected nodes in sites A, B and C. The data management system  110  can facilitate defining a number of grouping schemes. 
     At block  1115 , the EC group manager  815  generates a storage group, e.g., “ECG  1 ” based on the storage grouping scheme, and assigns a unique ID to the storage group. 
     At block  1120 , the EC group manager  815  identifies a set of the nodes in the distributed storage  150  that satisfy the grouping scheme. 
     At block  1125 , the EC group manager  815  associates a VCS from each of the identified nodes with the storage group. 
     At block  1130 , the DDS module  820  generates various metadata indicating the associations between the VCS, storage group and the nodes, and the process  1100  returns. For example, the DDS module  820  generates an ECG-&gt;VCS mapping metadata that indicates the VCSs associated with a particular storage group. In some embodiments, the DDS module  820  generates a VCS-&gt;node mapping metadata when a storage node is deployed into the distributed storage  150  and the chunk service splits the storage node into VCSs. 
       FIG. 12  is a block diagram of a computer system as may be used to implement features of some embodiments of the disclosed technology. The computing system  1200  may be used to implement any of the entities, components or services depicted in the examples of the foregoing figures (and any other components described in this specification). The computing system  1200  may include one or more central processing units (“processors”)  1205 , memory  1210 , input/output devices  1225  (e.g., keyboard and pointing devices, display devices), storage devices  1220  (e.g., disk drives), and network adapters  1230  (e.g., network interfaces) that are connected to an interconnect  1215 . The interconnect  1215  is illustrated as an abstraction that represents any one or more separate physical buses, point to point connections, or both connected by appropriate bridges, adapters, or controllers. The interconnect  1215 , therefore, may include, for example, a system bus, a Peripheral Component Interconnect (PCI) bus or PCI-Express bus, a HyperTransport or industry standard architecture (ISA) bus, a small computer system interface (SCSI) bus, a universal serial bus (USB), IIC (I2C) bus, or an Institute of Electrical and Electronics Engineers (IEEE) standard 1394 bus, also called “Firewire”. 
     The memory  1210  and storage devices  1220  are computer-readable storage media that may store instructions that implement at least portions of the described technology. In addition, the data structures and message structures may be stored or transmitted via a data transmission medium, such as a signal on a communications link. Various communications links may be used, such as the Internet, a local area network, a wide area network, or a point-to-point dial-up connection. Thus, computer readable media can include computer-readable storage media (e.g., “non transitory” media) and computer-readable transmission media. 
     The instructions stored in memory  1210  can be implemented as software and/or firmware to program the processor(s)  1205  to carry out actions described above. In some embodiments, such software or firmware may be initially provided to the computing system  1200  by downloading it from a remote system through the computing system  1200  (e.g., via network adapter  1230 ). 
     The technology introduced herein can be implemented by, for example, programmable circuitry (e.g., one or more microprocessors) programmed with software and/or firmware, or entirely in special-purpose hardwired (non-programmable) circuitry, or in a combination of such forms. Special-purpose hardwired circuitry may be in the form of, for example, one or more ASICs, PLDs, FPGAs, etc. 
     REMARKS 
     The above description and drawings are illustrative and are not to be construed as limiting. Numerous specific details are described to provide a thorough understanding of the disclosure. However, in some instances, well-known details are not described in order to avoid obscuring the description. Further, various modifications may be made without deviating from the scope of the embodiments. Accordingly, the embodiments are not limited except as by the appended claims. 
     Reference in this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the disclosure. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Moreover, various features are described which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but not for other embodiments. 
     The terms used in this specification generally have their ordinary meanings in the art, within the context of the disclosure, and in the specific context where each term is used. Some terms that are used to describe the disclosure are discussed below, or elsewhere in the specification, to provide additional guidance to the practitioner regarding the description of the disclosure. For convenience, some terms may be highlighted, for example using italics and/or quotation marks. The use of highlighting has no influence on the scope and meaning of a term; the scope and meaning of a term is the same, in the same context, whether or not it is highlighted. It will be appreciated that the same thing can be said in more than one way. One will recognize that “memory” is one form of a “storage” and that the terms may on occasion be used interchangeably. 
     Consequently, alternative language and synonyms may be used for any one or more of the terms discussed herein, nor is any special significance to be placed upon whether or not a term is elaborated or discussed herein. Synonyms for some terms are provided. A recital of one or more synonyms does not exclude the use of other synonyms. The use of examples anywhere in this specification including examples of any term discussed herein is illustrative only, and is not intended to further limit the scope and meaning of the disclosure or of any exemplified term. Likewise, the disclosure is not limited to various embodiments given in this specification. 
     Those skilled in the art will appreciate that the logic illustrated in each of the flow diagrams discussed above, may be altered in various ways. For example, the order of the logic may be rearranged, substeps may be performed in parallel, illustrated logic may be omitted; other logic may be included, etc. 
     Without intent to further limit the scope of the disclosure, examples of instruments, apparatus, methods and their related results according to the embodiments of the present disclosure are given below. Note that titles or subtitles may be used in the examples for convenience of a reader, which in no way should limit the scope of the disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. In the case of conflict, the present document, including definitions will control.