This application is related by subject matter to U.S. patent application Ser. No. ______ (Attorney Docket No. NIMSP112) filed on the same day as the instant application and entitled “Content-Based Replication of Data in Scale Out System”, which is incorporated herein by reference.
1. Field of the Invention
The present embodiments relate to methods, systems, and programs for replicating data in a networked storage system.
2. Description of the Related Art
Network storage, also referred to as network storage systems or storage systems, is computer data storage connected to a computer network providing data access to heterogeneous clients. Typically network storage systems process a large amount of Input/Output (IO) requests, and high availability, speed, and reliability are desirable characteristics of network storage.
Sometimes data is copied from one system to another, such as when an organization upgrades to a new data storage device, when backing up data to a different location, or when backing up data for the purpose of disaster recovery. The data needs to be migrated or replicated to the new device from the old device.
However, when transferring large volumes of data, there could be some glitches during the transfer/replication process, and some of the data may be improperly transferred. It may be very expensive resource wise to retransfer all the data, because it may take a large amount of processor and network resources that may impact the ongoing operation of the data service. Also, when data is being replicated to a different storage system, there could be a previous snapshot of the data in both systems. If a change is detected between snapshots being replicated, it may be very expensive to transmit over the network large amounts of data if only a small portion of the data has changed. Further yet, if a common base snapshot is lost, resending all the data may be very expensive.
What is needed is a network storage device, software, and systems that provide verification of the correct transfer of large amounts of data from one system to another, as well as ways to correct errors found during the replication process.
It is in this context that embodiments arise.
The present embodiments relate to fixing problems when data is replicated from a first system to a second system. It should be appreciated that the present embodiments can be implemented in numerous ways, such as a method, an apparatus, a system, a device, or a computer program on a computer readable medium. Several embodiments are described below.
One aspect includes a method for replicating data across storage systems. The method includes an operation for transferring a snapshot of a volume from an upstream array to a downstream array, the volume being a single accessible storage area within the upstream array. The method further includes comparing an upstream snapshot checksum of the snapshot in the upstream array with a downstream snapshot checksum of the snapshot in the downstream array. When the upstream snapshot checksum is different from the downstream snapshot checksum, a plurality of chunks is defined in the snapshot. For each chunk in the snapshot, an upstream chunk checksum calculated by the upstream array is compared with a downstream chunk checksum calculated by the downstream array. Further, the method includes an operation for sending, from the upstream array to the downstream array, data of the chunk when the upstream chunk checksum is different from the downstream chunk checksum.
One general aspect includes a method for replicating data across storage systems. The method includes an operation for transferring a snapshot of a volume from an upstream array to a downstream array, the volume being a single accessible storage area within the upstream array. The method also includes an operation for comparing an upstream snapshot checksum of the snapshot in the upstream array with a downstream snapshot checksum of the snapshot in the downstream array. When the upstream snapshot checksum is different from the downstream snapshot checksum, a plurality of chunks is defined in the snapshot. For each chunk in the snapshot, an upstream chunk checksum calculated by the upstream array is compared with a downstream chunk checksum calculated by the downstream array. When the upstream chunk checksum is different from the downstream chunk checksum, a plurality of blocks is defined in the chunk. Further, for each block in the chunk an upstream block checksum calculated by the upstream array is compared with a downstream block checksum calculated by the downstream array. When the upstream block checksum is different from the downstream block checksum data of the block is sent from the upstream array to the downstream array.
One aspect includes a non-transitory computer-readable storage medium storing a computer program for replicating data across storage systems. The computer-readable storage medium includes program instructions for transferring a snapshot of a volume from an upstream array to a downstream array, the volume being a single accessible storage area within the upstream array, and program instructions for comparing an upstream snapshot checksum of the snapshot in the upstream array with a downstream snapshot checksum of the snapshot in the downstream array. When the upstream snapshot checksum is different from the downstream snapshot checksum, a plurality of chunks is defined in the snapshot. For each chunk in the snapshot, an upstream chunk checksum calculated by the upstream array is compared with a downstream chunk checksum calculated by the downstream array. The storage medium further includes program instructions for sending, from the upstream array to the downstream array, data of the chunk when the upstream chunk checksum is different from the downstream chunk checksum.
Other aspects will become apparent from the following detailed description, taken in conjunction with the accompanying drawings.
The embodiments may best be understood by reference to the following description taken in conjunction with the accompanying drawings.
The following embodiments describe methods, devices, systems, and computer programs for replicating data across storage systems. It will be apparent, that the present embodiments may be practiced without some or all of these specific details. In other instances, well-known process operations have not been described in detail in order not to unnecessarily obscure the present embodiments.
In some implementations, a Snapshot Delta Replication (SDR) method is used to replicate snapshots of data volumes in a network storage device. However, something could have gone wrong during the replication, and a check is made to determine if the replicated snapshot is correct. If the replication is not completely correct, the data would have to be resent, which may be very resource costly. In order to avoid having to replicate all the data again, a Content-Based Replication (CBR) method is used to minimize the amount of data needed to fix the replicated snapshot.
With the CBR method, volume checksums are made at the upstream system (system being replicated) and the downstream system (system where the replicated data is received). If the checksums do not match, the volume is divided into large pieces of data, referred to herein as chunks, (e.g., 16 MB although other values are also possible). Then checksums are performed for each chunk, at the upstream system and the downstream system. If corresponding pair of checksums for the same chunk do not match at the upstream and the downstream systems, then the upstream system sends the chunk of data to the downstream system.
In one embodiment, another level of iteration is used to further divide the chunks into smaller pieces and perform checksums on the smaller pieces. For example, checksums of the blocks within a chunk can be compared, and then the blocks that have mismatched checksums are transmitted over the network.
In another embodiment, an automated program determines when CBR is to be performed, based on system parameters (design by the system designers), or user configuration (e.g., once a week), or based on heuristics that determine when the risk of an incorrect replication is high (e.g., after installing a new release). For example, in one embodiment, CBR could be more efficient for replication seeding than SDR when a common base snapshot is not found between the upstream and the downstream volumes, however, the downstream volume may already have blocks of the volume due to an earlier SDR.
In one embodiment, a first system creates snapshots of a volume over time (e.g., S1, S2, S3, etc.). The volume replicates one or more of the snapshots to a second volume, for example to provide backup of the data in a different location or in a different storage array.
The storage array that holds the source data to be copied is referred to as the upstream storage array, or the upstream system, or the base storage array, and the storage array that receives a copy of the data is referred to as the downstream storage array or the downstream system. When SDR is in the process of replicating a snapshot to create a replicated snapshot in another storage array, to compute what blocks need to be transferred, SDR uses a base snapshot that is already present on the downstream as well as on the upstream. This common snapshot is also referred to as the common ancestor snapshot. After SDR is complete, the replicated snapshot is present on both the upstream and the downstream storage arrays.
In one embodiment, replication means copying all the data from the upstream volume to the downstream volume. In some embodiments, if the common ancestor snapshot of the volume has already been replicated, the replication of a later snapshot includes copying only the data that has changed, which is also referred to herein as the delta data or the difference between the two snapshots. It is noted that not all the snapshots in the upstream volume have to be replicated to the downstream volume.
For example, in the exemplary embodiment of
Replicating snapshot S1 requires copying all the data from S1 to S1′ because there are no previous snapshots that have been replicated. However, replicating snapshot S3 requires only copying the difference between S3 and S1 [S3-S1]. In one embodiment, this method for replicating snapshots from the upstream to the downstream volume by copying the difference between two snapshots in time is referred to herein as snapshot delta replication (SDR).
Sometimes, SDR is an efficient process, but other times SDR is very inefficient. For example, in one scenario, two blocks, B1 and B2 are written to the volume after snapshot S1 is taken but before snapshot S3 is taken. If SDR is performed for snapshot S3 using snapshot S1 as the common snapshot, only blocks B1 and B2 will be replicated (i.e., transmitted to the downstream system) and SDR is efficient in this case. However, if for some reason, snapshot S1 is not available in the downstream system, then SDR would be inefficient as the complete volume would have to be transmitted to the downstream system.
In one embodiment, the detection that the snapshots are not exactly equal may be performed by doing checksums of the upstream and downstream volumes. If the checksums don't match, then there is a problem with the copied data. An obvious and expensive solution is to recopy all the data again until the checksums match. However, re-copying large amounts of data may cause distress in the data storage system and impact performance, which means that that transfer of large amounts of data should be avoided during normal operating hours. Therefore, resending the data is not a desirable solution.
In one embodiment, the volume is logically divided into large groups of data, referred to herein as chunks. In one embodiment, the size of a block is 4 KBytes, but other values are also possible, such as in the range from 256 bytes to 50 Kbytes or more.
A chunk (e.g., 16 MB) is usually much larger than a block, so the chunk includes a plurality of blocks. In one embodiment, the chunk is not addressable for accessing data from the volume and the chunk is only utilized for correcting the replication of snapshots, as described in more detail below. Other embodiments may include other sizes for chunks, such as in the range from 1 megabytes to 100 megabytes, or in the range from 100 megabytes to 1 or several gigabytes. In one embodiment, the size of the chunk is 100 times the size of the block, but other multipliers may also be possible, such as 50 to 5000. Therefore, the size of the chunk may be 50 to 5000 times bigger than the size of the block.
Another possible checksum is a Fletcher checksum. Further, several types of checksums may be utilized depending on the size of the data to be checksumed. For example, a Fletcher checksum may be utilized for snapshots, and an SHA-1 checksum may be utilized for chunks or blocks. In one embodiment, the checksum is negotiated between the upstream and the downstream storage arrays during the CBR initialization period.
Further, the checksums may be performed over compressed or uncompressed data. In one embodiment, the checksum of uncompressed data is utilized but this requires decompression which causes higher resource utilization. In another embodiment, the checksum is performed over compressed data, however, this option may stop working when compression of blocks starts differing between upstream and downstream (e.g., due to background strong recompression taking place in the downstream system). In yet another embodiment, uncompressed checksums are stored for certain data ranges, and a larger checksum is formed by combining the data from the uncompressed checksums. This way, there is no need to decompress the blocks to obtain the checksums of the chunks.
At start time, the upstream and the downstream arrays may exchange CBR-related information, such as checksum type, checksum size, and how much data is covered by each checksum (e.g., size of the chunk, how many blocks in each chunk).
The validation of the snapshots can be initiated in different ways. For example, an administrator may request a storage array to check for the validity of a snapshot in a downstream volume, or an automated validating process may be initiated by the storage array. For example, a validating process may be initiated periodically or maybe initiated after the data center updates the software of one or more storage arrays, or as additional hardware (e.g. another storage array) is added to the network data system.
In one embodiment, the upstream volume computes the checksum of S1, i.e., the checksum of the complete snapshot S1. The upstream volume then sends a request to the downstream volume to provide the checksum of the downstream snapshot S1′. In other embodiment, the downstream volume initiates the process for comparing the checksums. In general, some of the methods described herein include operations performed by the upstream volume (e.g., initiating the validation procedure, comparing checksums, etc.), but the same principles may be applied when the downstream volume perform these operations (e.g., initiating the validation of the replicated data) for validating replicated data.
The downstream volume then calculates S1′ checksum (or retrieves the checksum from memory if the checksum is already available) and sends the checksum to the upstream volume. The upstream volume compares the two checksums of S1 and S1′, and if the checksums match that snapshot is assumed to be correct (e.g., validated). However, if the checksums do not match, then the content-based replication CBR process is started.
A principle of CBR is to calculate the checksums of large amounts of data (e.g., for each chunk) instead of comparing the checksums for each of the individual blocks in the volume. In one embodiment, when a mismatch is found, the system administrator gets an alert (on the downstream array, or on the upstream array, or on both). The alert indicates that the replicated snapshot is compromised (and maybe older snapshots too). After executing CBR, the system administrator will get another alert that the mismatch has been fixed in the most recent replicated snapshot.
The upstream volume sends a request to the downstream volume to start the CBR process, and sends information related to the process, such as the checksum type to be performed, the chunk size, and a cursor used to indicate at what chunk to start the CBR process. The cursor is useful in case the CBR process is suspended for any reason, such as a system suffering downtime or a network-related problem (e.g., network disconnect). This way, when the upstream and the downstream volume are ready to continue with the suspended CBR process, the process does not have to be restarted from the beginning but from the place associated with the value of the cursor. In one embodiment, the cursor may be kept in the upstream volume, or in the downstream volume, or in both places. In one embodiment, the cursor is an identifier for a chunk in the volume, wherein all the chunks that preceded the identified chunk are considered to have been already validated.
For each chunk, the upstream and the downstream systems calculate the respective checksums Ci and Ci′. Then the downstream array sends Ci′ checksum to the upstream array, and the upstream array compares checksums Ci and Ci′. If the checksums match, the process continues with the next chunk, until all the chunks are validated. However, if the checksums Ci and Ci′ do not match, the upstream storage array sends the data for chunk Ci to the downstream array. When the last chunk has been validated, the upstream storage array sends a CBR complete notification to the downstream array.
In some embodiments, the upstream array and the downstream array coordinate the validation process by checksumming and comparing a plurality of chunks simultaneously (e.g., in parallel), that is, the arrays do not have to wait till a chunk validation is completed to perform the validation of the next chunk and several chunk validation processes may be performed in parallel.
It is noted that SDR and CBR may coexist in the same storage array, or even in the same volume, because at different times and under different circumstances one method may be preferred over others.
In one embodiment, a per-volume state is maintained, in both the upstream and the downstream array, for managing and tracking content based replication of each volume. The downstream volume's state is consulted during the replication protocol phase that occurs prior to the SDR data transfer phase. If the upstream or the downstream volume state indicates the need for content based replication to occur, the upstream and/or the downstream array coordinate with the storage control system to initiate CBR.
Once the data transfer phase has completed, the upstream array sends an indication to the downstream array during the snapshot replication phase as to whether or not content based replication was carried out. This allows the downstream array to update the volume state, which includes clearing a flag that indicates a content based replication is needed, and updating a state to indicate the snapshot ID at which content based replication occurred. Also, the downstream array will issue an alert if the volume record indicates that errors took place (which need to be fixed at this point).
If the checksum for a chunk fails, then checksums for the sub-chunks are calculated and compared and the data for the sub-chunks that fail the validation is sent from the upstream array to the downstream array, instead of having to send the whole chunk. In one embodiment, the size of the chunk is between 5 times and 1000 times the size of the sub-chunk, but other value multipliers are also possible.
The operations described in
The upstream and the downstream volumes then calculate the checksum for a block Bj and the downstream volume sends the checksum of Bj′. The upstream volume compares the checksums of Bj and Bj′, and if there is a mismatch the data for block Bj is sent to the downstream array. In one embodiment, once all the blocks in the chunk are validated, identification is sent to the downstream array that the validation of that chunk has been completed. In one embodiment, the checksums for the chunk are rechecked to validate that the chunk is now correctly replicated. In one embodiment, the downstream array compares the checksums and notifies the upstream array which blocks to re-send.
In CBR, the upstream and downstream arrays compute checksums and if the checksums don't match, the upstream array sends data to fix the mismatch. The two states of verification and fixing can be done sequentially or it can be parallelized, for example if checksum of chunk 0 . . . 16 MB of bin1 does not match, the system will start fixing 0 . . . 16 MB while performing checksum on the next chunk 16 MB . . . 32 MB.
In one embodiment, the performance of the write path is driven by the flushing of NVRAM 108 to disk 110. With regards to the read path, the initiator 106 sends a read request to storage array 102. The requested data may be found in any of the different levels of storage mediums of the storage array 102. First, a check is made to see if the data is found in RAM (not shown), which is a shadow memory of NVRAM 108, and if the data is found in RAM then the data is read from RAM and sent back to the initiator 106. In one embodiment, the shadow RAM memory (e.g., DRAM) keeps a copy of the data in the NVRAM and the read operations are served from the shadow RAM memory. When data is written to the NVRAM, the data is also written to the shadow RAM so the read operations can be served from the shadow RAM leaving the NVRAM free for processing write operations.
If the data is not found in the shadow RAM then a check is made to determine if the data is in cache, and if so (i.e., cache hit), the data is read from the flash cache 112 and sent to the initiator 106. If the data is not found in the NVRAM 108 nor in the flash cache 112, then the data is read from the hard drives 110 and sent to the initiator 106. In addition, if the data being served from hard disk 110 is cache worthy, then the data is also cached in the SSD cache 112.
As shown, a volume can be configured to span multiple storage arrays of a storage pool. In this configuration, arrays in a volume are members of a storage pool. In one example, if an array is added to a group and the array if not specified to a particular pool, the array will be made a member of a default storage pool. For instance, in
The difference between groups and storage pools is that groups aggregate arrays for management while storage pools aggregate arrays for capacity and performance. As noted above, some operations on storage pools may include creating and deleting storage pools, adding and removing arrays to or from storage pools, merging storage pools, and the like. In one example, a command line may be provided to access a particular pool, which allows management of multiple storage arrays via the command line (CLI) interface. In one embodiment, a scale-out set up can be created by either performing a group merge or adding an array. A group merge is meant to merge two arrays that are already set up and have objects and data stored thereon. The merge process ensures that there are no duplicate objects and the merge adheres to other rules around replication, online volumes, etc. Multi-array groups can also be created by adding an underutilized array to another existing array.
In one embodiment, storage pools are rebalanced when storage objects such as arrays, pools and volumes are added, removed or merged. Rebalancing is a non-disruptive low-impact process that allows application IO to continue uninterrupted even to the data sets during migration. Pool rebalancing gives highest priority to active data IO and performs the rebalancing process with a lower priority.
As noted, a group may be associated with several arrays, and at least one array is designated as the group leader (GL). The group leader has the configuration files and data that it maintains to manage the group of arrays. In one embodiment, a backup group leader (BGL) may be identified as one of the members of the storage arrays. Thus, the GL is the storage array manager, while the other arrays of the group are member arrays. In some cases, the GL may be migrated to another member array in case of a failure or possible failure at the array operating as the GL. As the configuration files are replicated at the BGL, the BGL is the one that takes the role as a new GL and another member array is designated as the BGL. In one embodiment, volumes are striped across a particular pool of arrays. As noted, group configuration data (configuration files and data managed by a GL) is stored in a common location and is replicated to the BGL.
In one embodiment, only a single management IP (Internet Protocol) address is used to access the group. Benefits of a centrally managed group include single volume collections across the group, snapshot and replication schedules spanning the group, added level of security by creating pools, shared access control lists (ACLs), high availability, and general array administration that operates at the group level and CLI command access to the specific group.
In one implementation, the storage scale-out architecture allows management of a storage cluster that spreads volumes and their IO requests between multiple arrays. A host cannot assume that a volume can be accessed through specific paths to one specific array or another. Instead of advertising all of the iSCSI interfaces on the array, the disclosed storage scale-out clusters advertise one IP address (e.g., iSCSI discovery). Volume IO requests are redirected to the appropriate array by leveraging deep integration with the host operating system platforms (e.g., Microsoft, VMware, etc.), or using iSCSI redirection.
In addition, the active controller 1120 further includes CPU 1108, general-purpose RAM 1112 (e.g., used by the programs executing in CPU 1108), input/output module 1110 for communicating with external devices (e.g., USB port, terminal port, connectors, plugs, links, etc.), one or more network interface cards (NICs) 1114 for exchanging data packages through network 1156, one or more power supplies 1116, a temperature sensor (not shown), and a storage connect module 1122 for sending and receiving data to and from the HDD 110 and SSD 112. In one embodiment, standby controller 1124 includes the same components as active controller 1120.
Active controller 1120 is configured to execute one or more computer programs stored in RAM 1112. One of the computer programs is the storage operating system (OS) used to perform operating system functions for the active controller device. In some implementations, one or more expansion shelves 1130 may be coupled to storage array 102 to increase HDD 1132 capacity, or SSD 1134 capacity, or both.
Active controller 1120 and standby controller 1124 have their own NVRAMs, but they share HDDs 110 and SSDs 112. The standby controller 1124 receives copies of what gets stored in the NVRAM 1118 of the active controller 1120 and stores the copies in its own NVRAM. If the active controller 1120 fails, standby controller 1124 takes over the management of the storage array 102. When servers, also referred to herein as hosts, connect to the storage array 102, read/write requests (e.g., IO requests) are sent over network 1156, and the storage array 102 stores the sent data or sends back the requested data to host 104.
Host 104 is a computing device including a CPU 1150, memory (RAM) 1146, permanent storage (HDD) 1142, a NIC card 1152, and an IO module 1154. The host 104 includes one or more applications 1136 executing on CPU 1150, a host operating system 1138, and a computer program storage array manager 1140 that provides an interface for accessing storage array 102 to applications 1136. Storage array manager 1140 includes an initiator 1144 and a storage OS interface program 1148. When an IO operation is requested by one of the applications 1136, the initiator 1144 establishes a connection with storage array 102 in one of the supported formats (e.g., iSCSI, Fibre Channel, or any other protocol). The storage OS interface 1148 provides console capabilities for managing the storage array 102 by communicating with the active controller 1120 and the storage OS 1106 executing therein.
To process the IO requests, resources from the storage array 102 are required. Some of these resources may be a bottleneck in the processing of storage requests because the resources are over utilized, or are slow, or for any other reason. In general, the CPU and the hard drives of the storage array 102 can become over utilized and become performance bottlenecks. For example, the CPU may become very busy because the CPU is utilized for processing storage IO requests while also performing background tasks, such as garbage collection, snapshots, replication, alert reporting, etc. In one example, if there are many cache hits (i.e., the SSD contains the requested data during IO requests), the SSD cache, which is a fast responding system, may press the CPU for cycles, thus causing potential bottlenecks for other requested IOs or for processing background operations.
The hard disks may also become a bottleneck because the inherent access speed to data is slow when compared to accessing data from memory (e.g., NVRAM) or SSD. Embodiments presented herein are described with reference to CPU and HDD bottlenecks, but the same principles may be applied to other resources, such as a system with insufficient amount of NVRAM.
As used herein, SSDs functioning as flash cache, should be understood to operate the SSD as a cache for block level data access, providing service to read operations instead of only reading from HDDs 110. Thus, if data is present in SSDs 112, reading will occur from the SSDs instead of requiring a read to the HDDs 110, which is a slower operation. As mentioned above, the storage operating system 1106 is configured with an algorithm that allows for intelligent writing of certain data to the SSDs 112(e.g., cache-worthy data), and all data is written directly to the HDDs 110 from NVRAM 1118.
The algorithm, in one embodiment, is configured to select cache-worthy data for writing to the SSDs 112, in a manner that provides in increased likelihood that a read operation will access data from SSDs 112. In some embodiments, the algorithm is referred to as a cache accelerated sequential layout (CASL) architecture, which intelligently leverages unique properties of flash and disk to provide high performance and optimal use of capacity. In one embodiment, CASL caches “hot” active data onto SSD in real time—without the need to set complex policies. This way, the storage array can instantly respond to read requests—as much as ten times faster than traditional bolt-on or tiered approaches to flash caching.
For purposes of discussion and understanding, reference is made to CASL as being an algorithm processed by the storage OS. However, it should be understood that optimizations, modifications, additions, and subtractions to versions of CASL may take place from time to time. As such, reference to CASL should be understood to represent exemplary functionality, and the functionality may change from time to time, and may be modified to include or exclude features referenced herein or incorporated by reference herein. Still further, it should be understood that the embodiments described herein are just examples, and many more examples and/or implementations may be defined by combining elements and/or omitting elements described with reference to the claimed features.
In some implementations, SSDs 112 may be referred to as flash, or flash cache, or flash-based memory cache, or flash drives, storage flash, or simply cache. Consistent with the use of these terms, in the context of storage array 102, the various implementations of SSD 112 provide block level caching to storage, as opposed to instruction level caching. As mentioned above, one functionality enabled by algorithms of the storage OS 1106 is to provide storage of cache-worthy block level data to the SSDs, so that subsequent read operations are optimized (i.e., reads that are likely to hit the flash cache will be stored to SSDs 12, as a form of storage caching, to accelerate the performance of the storage array 102).
In one embodiment, it should be understood that the “block level processing” of SSDs 112, serving as storage cache, is different than “instruction level processing,” which is a common function in microprocessor environments. In one example, microprocessor environments utilize main memory, and various levels of cache memory (e.g., L1, L2, etc.). Instruction level caching, is differentiated further, because instruction level caching is block-agnostic, meaning that instruction level caching is not aware of what type of application is producing or requesting the data processed by the microprocessor. Generally speaking, the microprocessor is required to treat all instruction level caching equally, without discriminating or differentiating processing of different types of applications.
In the various implementations described herein, the storage caching facilitated by SSDs 112 is implemented by algorithms exercised by the storage OS 1106, which can differentiate between the types of blocks being processed for each type of application or applications. That is, block data being written to storage 1130 can be associated with block data specific applications. For instance, one application may be a mail system application, while another application may be a financial database application, and yet another may be for a website-hosting application. Each application can have different storage accessing patterns and/or requirements. In accordance with several embodiments described herein, block data (e.g., associated with the specific applications) can be treated differently when processed by the algorithms executed by the storage OS 1106, for efficient use of flash cache 112.
In operation 806, a check is made to determine if usc is equal to dsc. If usc is equal to dsc, the method flows to operation 818, and if usc is not equal to dsc, the method flows to operation 808. In operation 808, a plurality of chunks is defined in the snapshot.
From operation 808, the method flows to operation 810 where a comparison is made of an upstream chunk checksum (ucc) calculated by the upstream array with a downstream chunk checksum (dsc) calculated by the downstream array.
In operation 812, a check is made to determine if ucc is equal to dsc. If ucc is equal to dsc, the method flows to operation 814 where the chunk is considered validated. If ucc is not equal to dsc, the method flows to operation 816 where data of the is sent chunk from the upstream array to the downstream array. Operations 810, 812, and 814 or 816 are repeated for all the chunks defined in operation 808. When all the chunks have been validated, the snapshot is considered validated in operation 818.
The snapshot operations described herein solve the problem of having to re-send all the data of a volume from one storage system to another storage system when a problem occurs while replicating data. The data of the original snapshot is kept in permanent storage of the upstream array, and the replicated data is kept in permanent storage in the downstream array. Instead of having to resend all the data of the volume, the volume is divided into logical groups of data, referred to as chunks, and then each chunk is validated. When all the chunks have been validated, the replicated version of the volume is considered validated. The operations described herein refer to the exchange of information between two separate storage devices, which exchange data and transfer parameters to validate the replicated data. By re-transmitting data only chunks that have been improperly replicated, savings in time and resources are attained because the data of the chunks that have been correctly replicated does not have to be re-transmitted.
One or more embodiments can also be fabricated as computer readable code on a non-transitory computer readable storage medium. The non-transitory computer readable storage medium is any non-transitory data storage device that can store data, which can be thereafter be read by a computer system. Examples of the non-transitory computer readable storage medium include hard drives, network attached storage (NAS), read-only memory, random-access memory, CD-ROMs, CD-Rs, CD-RWs, magnetic tapes and other optical and non-optical data storage devices. The non-transitory computer readable storage medium can include computer readable storage medium distributed over a network-coupled computer system so that the computer readable code is stored and executed in a distributed fashion.
Although the method operations were described in a specific order, it should be understood that other housekeeping operations may be performed in between operations, or operations may be adjusted so that they occur at slightly different times, or may be distributed in a system which allows the occurrence of the processing operations at various intervals associated with the processing, as long as the processing of the overlay operations are performed in the desired way.
Although the foregoing embodiments have been described in some detail for purposes of clarity of understanding, it will be apparent that certain changes and modifications can be practiced within the scope of the appended claims. Accordingly, the present embodiments are to be considered as illustrative and not restrictive, and the embodiments are not to be limited to the details given herein, but may be modified within the scope and equivalents of the described embodiments.
This application claims priority from U.S. Provisional Patent Application No. 62/084,395, filed Nov. 25, 2014, entitled “Content-Based Replication of Data Between Storage Units,” and from U.S. Provisional Patent Application No. 62/084,403, filed Nov. 25, 2014, entitled “Content-Based Replication of Data in Scale Out System.” These provisional applications are herein incorporated by reference.
Number | Date | Country | |
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62084395 | Nov 2014 | US | |
62084403 | Nov 2014 | US |