JP2015158765A - storage system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To solve a problem in which the efficiency of eliminating redundant storage is lowered due to RAW backup.SOLUTION: A storage system 100 of the present invention includes: image analysis means 101 that analyzes RAW image data targeted for RAW backup; and backup means 102 that stores the RAW image data in a storage device while eliminating redundant storage eliminated so as to perform RAW backup. The image analysis means analyzes RAW image data and extracts data which can be classified into predetermined groups from the RAW image data. The backup means combines the extracted data into one piece of storage data for each of the classified groups and combines data which is not extracted into one piece of storage data; and stores each of the pieces of storage data obtained by the combination.

Description

  The present invention relates to a storage system, and more particularly to a storage system having a duplicate storage elimination function.

  In recent years, with the development and spread of computers, various types of information have been converted into digital data. As a device for storing such digital data, there are storage devices such as a magnetic tape and a magnetic disk. Since the data to be stored increases day by day and becomes enormous, a large-capacity storage system is required. In addition, reliability is required while reducing the cost of the storage device. In addition to this, it is necessary that data can be easily retrieved later. As a result, there is a demand for a storage system that can automatically increase storage capacity and performance, eliminate duplicate storage, reduce storage costs, and have high redundancy.

  In response to such a situation, in recent years, a content address storage system has been developed as shown in Patent Document 1. In this content address storage system, data is distributed and stored in a plurality of storage devices, and the storage location where the data is stored is specified by a unique content address specified according to the content of the data.

  As described above, since the content address is generated so as to be unique according to the content of the data, if it is duplicated data, the data of the same content can be acquired by referring to the data at the same storage position. . Therefore, it is not necessary to store the duplicate data separately, and duplicate recording can be eliminated and the data capacity can be reduced. That is, the content address storage system has a deduplication function in which new data is stored only when data of the same content is not stored.

  In addition, the storage system divides a chunk, which is block data of a predetermined capacity, into a plurality of fragment data, and further adds a fragment that becomes redundant data, and stores each of the plurality of fragment data in a plurality of storage devices. ing. Then, by designating the content address later, the fragment data stored in the storage location specified by the content address can be read, and the chunk before division can be restored from the plurality of fragment data.

  In this way, since the storage system adds fragment data that becomes redundant data, even if fragment data equal to or less than the number of fragments of the added redundant data is lost, the original chunk can be regenerated.

JP2013-182476

  In recent years, it is expected that a sufficiently high-speed device has a large capacity and is generally used even in a small I / O such as an SSD (Solid State Drive). Such devices reduce the need for defragmentation and increase the likelihood that a fragmented file system image will be backed up. However, it is difficult for such a RAW backup of a file system to increase the efficiency of deduplication using a deduplication storage system.

  For example, when a file system created on SAN (Storage Area Network) storage is RAW backed up to deduplication storage, if the file system is fragmented, the duplication rate will increase due to the update of some files. descend. This is because the files are not continuously arranged on the file system image, and even if files having the same data exist, they cannot be duplicated.

  Therefore, an object of the present invention is to solve the above-described problem that the efficiency of eliminating duplicate storage by performing RAW backup decreases.

A storage system according to an aspect of the present invention
Image analysis means for analyzing RAW image data to be subjected to RAW backup;
Backup means for performing RAW backup by storing the RAW image data in a storage device by eliminating duplicate storage;
With
The image analysis means analyzes the RAW image data and extracts data that can be classified into a predetermined group from the RAW image data.
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the data not extracted as one storage data. Store each stored data,
The configuration is as follows.

In addition, a program which is one embodiment of the present invention is
In the information processing device,
Image analysis means for analyzing RAW image data to be subjected to RAW backup;
Backup means for performing RAW backup by storing the RAW image data in a storage device by eliminating duplicate storage;
And realize
The image analysis means analyzes the RAW image data and extracts data that can be classified into a predetermined group from the RAW image data.
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the data not extracted as one storage data. Store each stored data,
Make it happen,
The configuration is as follows.

In addition, a backup method according to one aspect of the present invention includes:
Analyzing the raw image data subject to raw backup,
The RAW image data is stored in a storage device by eliminating duplicate storage, and RAW backup is performed.
During the analysis of the RAW image data, data that can be classified into a predetermined group is extracted from the RAW image data,
The data extracted by the analysis of the RAW image data at the time of the RAW backup is summarized as one storage data for each of the classified groups, and the data not extracted is summarized as one storage data. Store each stored data individually,
The configuration is as follows.

  By configuring as described above, the present invention can suppress a decrease in the efficiency of eliminating duplicate storage even during RAW backup of RAW image data.

1 is a block diagram illustrating an overall configuration of an information processing system including a deduplication storage apparatus according to the present invention. It is a functional block diagram which shows the structure of the SAN device disclosed in FIG. FIG. 2 is a functional block diagram illustrating a configuration of a deduplication storage device disclosed in FIG. 1. It is a figure which shows a mode when the data by the deduplication storage apparatus disclosed in FIG. 3 are memorize | stored. 3 is a flowchart illustrating an operation of the information processing system disclosed in FIG. 1. 3 is a flowchart illustrating an operation of the information processing system disclosed in FIG. 1. FIG. 4 is a diagram illustrating another configuration example of the deduplication storage device disclosed in FIG. 3. It is a figure which shows the mode at the time of the data writing by the deduplication storage apparatus disclosed in FIG. It is a figure which shows the mode at the time of the data writing by the deduplication storage apparatus disclosed in FIG. It is a figure which shows the other mode when storing the data by the deduplication storage apparatus disclosed in FIG. It is a figure which shows the structure of the storage system in attachment 1 of this invention.

<Embodiment 1>
A first embodiment of the present invention will be described with reference to FIGS. FIG. 1 is a block diagram showing the overall configuration of the information processing system. FIG. 2 is a functional block diagram showing the configuration of the SAN device, and FIG. 3 is a functional block diagram showing the configuration of the deduplication storage device. FIG. 4 is a diagram showing a state of processing when RAW image data is backed up by the deduplication storage apparatus. 5 to 6 are flowcharts showing the operation of the information processing system. FIG. 7 to FIG. 9 are diagrams showing a state at the time of data writing by the deduplication storage apparatus. FIG. 10 is a diagram illustrating another process when the RAW image data is RAW backed by the deduplication storage apparatus.

[Constitution]
As shown in FIG. 1, the information processing system includes a SAN (Storage Area Network) device 1, a deduplication storage device 2, and a business server device 3. These are connected by a communication path. The communication path is, for example, a network connected by Ethernet (registered trademark) or Fiber Channel. In this embodiment, the business server apparatus 3 uses a volume on the SAN apparatus 2 and the volume is backed up from the SAN apparatus 1 to the deduplication storage apparatus 2 for explanation.

  As shown in FIG. 2, the SAN device 1 includes a communication unit 10, a difference map acquisition unit 11, a pairing unit 12, a replicate unit 13, a separate unit 14, and a difference information storage unit 15. Each of these units is configured by a dedicated circuit, or is constructed by incorporating a program into an arithmetic device.

  Further, the SAN device 1 stores the difference map information 16 in a storage device that is equipped. In addition, the SAN device 1 includes a MV (Master Volume) 17 and a RV (Replica Volume) 18 that are volumes for storing data to be backed up in the storage device.

  The pairing unit 12, the replicate unit 13, and the separate unit 14 can be used from the communication path in the business server device 3 that updates or reads the data of the MV 17. Using the pairing unit 12, the MV 17 and the RV 18 can be paired. Thereafter, the replicate unit 13 can copy data from the MV 17 to the RV 18. Further, by using the separation unit 14, pairing between the MV 17 and the RV 18 can be canceled. The difference information storage unit 15 records, as difference map information 16, an update block due to data update generated in the MV 17 immediately after the separation by the pairing cancellation is performed. The deduplication storage apparatus 2 can acquire the difference map information 16 from the communication path using the difference map acquisition unit 11 of the SAN apparatus 1.

  The deduplication storage apparatus 2 includes a communication unit 20, a RAW backup unit 21, a RAW image restoration unit 22, a fragmentation determination unit 26, a RAW image analysis unit 27, an extraction block determination unit 28, and a file instantaneous copy unit 29. . Each of these units is configured by a dedicated circuit, or is constructed by incorporating a program into an arithmetic device.

  In addition, the deduplication storage device 2 stores the RAW image configuration information 25 in the storage device provided. Further, the deduplication storage device 2 includes an FG file system 23 and a BG file system 24 formed by a file management function and a storage device constructed by incorporating a program into the arithmetic device.

  First, the RAW backup unit 21 (backup means) uses the fragmentation determination unit 26 (distribution determination means) to fragment a predetermined unit of data in the RAW image data to be backed up based on a predetermined criterion. It is judged whether it is stored in a distributed manner. Also, the RAW backup unit 21 decomposes the RAW image data based on the determination by the fragmentation determination unit 26 and records it in the BG file system 24. At this time, the RAW backup unit 21 stores the stored data in the BG file system 24 by eliminating the redundant storage of the already stored data. Further, the RAW backup unit 21 records configuration information for returning the RAW image data stored in the BG file system 24 to the original file as the RAW image configuration information 25.

  The extraction block determination unit 26 (image analysis means, backup means) extracts data to be stored as a separate file from the block data divided from the RAW image data. For example, since a large file can obtain a large duplication rate and the capacity efficiency can be improved, it is determined that block data constituting such a file is extracted and recorded as a separate file. Specifically, block data constituting a file whose capacity exceeds a set threshold is extracted.

  The RAW image analysis unit 27 (image analysis unit) is used by the fragmentation determination unit 26 and the extraction block determination unit 28 in order to extract the block data described above. For example, when the RAW image data is a file system, the RAW image analysis unit 27 analyzes the size (capacity) of the file included in the RAW image data and the arrangement position of the blocks constituting the file. Information can be provided to the extraction block determination unit 26.

  The FG file system 23 (data output means) displays the original RAW image data based on the RAW image data recorded in the BG file system 24 and divided as described later and the RAW image configuration information 25. Is a transparent file system.

  The RAW image restore unit 22 (data output means) reads the RAW image data from the FG file system 23 to restore the RAW image data before being divided into the SAN device 1.

  The file instantaneous copy unit 29 is a function for creating a copy of a file only by copying metadata. Since it is implemented in the deduplication storage apparatus 2, deduplication is eliminated even if a copy is created, and thus the disk capacity is not actually consumed.

[Operation]
Next, the operation of the information processing system configured as described above will be described with reference to the explanatory diagram of FIG. 4, the flowcharts of FIGS. 5 to 6, and the explanatory diagrams of FIGS. 7 to 9. In the following description, it is assumed that the MV 17 is backed up from the business server device 3.

  First, pairing of the MV 17 and the RV 18 is performed from the business server device 3 (step S1). Then, replication is performed in order to copy the data of MV17 to RV18 (step S2). If backup with a static point is necessary (step S3: Yes), the business is stopped to create a static point (step S4), and then separation is performed (step S5). When the separation is performed, update information (update block) to the MV 17 is started to be recorded in the difference map information 16 by the difference information storage unit 15 (step S6).

  Thereafter, the RAW backup unit 21 of the deduplication storage device 2 uses the difference map acquisition unit 11 to acquire the difference map information 16 until immediately before the separation is performed (step S7). Using this acquired difference map information 16, the RAW backup unit 21 backs up the data of the RV 18 to the deduplication storage apparatus 2 (step S8).

  The RV 18 data backup process to the deduplication storage apparatus 2 in step S8 of FIG. 5 will be described in detail with reference to FIG. First, the RAW backup unit 21 uses the fragmentation determination unit 26 to determine whether the RAW image data is fragmented from the difference map information 16. That is, the fragmentation determination unit 26 analyzes the difference map information 16 that is difference information between Dynamic Data Replications or between snapshots, and estimates the degree of data dispersion, that is, the degree of fragmentation in the RAW image data.

  For example, as shown in step S11 and step S12 of FIG. 6, there are continuous update blocks having a size equal to or smaller than a predetermined value (step S11: Yes), and the end of the update block and the next update block If there are locations where the offset to the start position is less than or equal to the specified value (step S12: Yes), the difference from the previous generation data is considered large, and the data is fragmented in the RAW image data. (Step S13). Based on this result, as will be described below, it is determined whether it is necessary to perform processing for extracting a file from RAW image data.

  In the above description, the fragmentation determination unit 26 determines whether or not the data in the RAW image data is fragmented according to the capacity and arrangement status of a predetermined unit of data such as an update block in the difference map information 16. However, it may be determined whether it is fragmented according to other criteria.

  Subsequently, when it is determined that fragmentation has occurred, it is confirmed that a previous generation backup exists (step S15). If the previous generation backup exists (step S15: Yes), the difference on the SAN device 1 indicated that the previous generation backup image and the difference map information 16 acquired from the SAN device 1 are updated. RAW backup is performed using the data (step S17). At this time, RAW image data metadata from the previous generation backup image and differential data is analyzed, a large file whose capacity exceeds the threshold is extracted, and the extracted file and the unextracted data are deduplicated respectively. RAW backup is performed while

  Here, the above-described file extraction processing will be described with reference to FIG. “BK_A” in FIG. 4 indicates RAW image data of the entire volume of the SAN device 1. First, this RAW image data is divided into fixed-length block data, and offset information indicating a position on the RAW image data is assigned to each. As a result of analyzing the raw image data of “BK_A”, when a large file “f1” whose capacity exceeds the threshold is extracted, the offset information is stored in the raw image configuration information 25 as “f1 index”. deep. Here, it is assumed that “f1 (1)” to “f1 (6)” are extracted as block data constituting the file “f1”. The offset information of the block data that has not been extracted is also stored as “Rem index” in the RAW image configuration information 25.

  Then, as shown in FIG. 4, the BG file system 24 includes a file “f1” in which the extracted block data is combined into one, and the remaining data in which the block data that has not been extracted is combined into one. , Respectively. At this time, since the duplicate storage elimination process is performed and stored as will be described later, the duplicate elimination efficiency is increased particularly for the file “f1”. In the example of FIG. 4, only one file is extracted. However, when a plurality of files are extracted, block data is collected for each file and stored in the BG file system 24 for each file. .

  In the FG file system 23, the original RAW image data is displayed based on the offset information in the RAW image configuration information 25 and the data on the BG file system 24. For example, each block data on the BG file system 24 shown in FIG. 4 is restored to the position indicated by the offset information of the RAW image configuration information, and is displayed as the original RAW image data “BK_A”.

  Here, returning to step S15 in FIG. 6, if there is no previous generation backup (step S15: No), the differential backup based on the differential map information 16 cannot be performed, so the RAW image data is a full backup. . In this case, the RAW backup unit 21 analyzes the metadata part of the RAW image data of the SAN device 1 and extracts a large file whose capacity exceeds the threshold as described above, and extracts the extracted file and the data that has not been extracted. Are backed up by deduplication (step S18).

  Further, when both “No” in step S11 and step S12 in FIG. 6, it is considered that the difference from the previous generation data is not large, and it is determined that the data is not fragmented in the RAW image data. (Step S14). Subsequently, it is confirmed whether or not a previous generation backup exists (step S16). If the previous generation backup exists (step S16: Yes), the previous generation backup on the BG file system 24 is copied by the file instant copy unit 29. Furthermore, using the difference data on the SAN device 1 that is indicated to have been updated by the difference map information 16 acquired from the SAN device 1, the corresponding portion of the backup image after copying is overwritten with the updated data (step S19). ). As described above, when it is determined that the file is not fragmented and there is a previous generation backup, the backup is performed without extracting the file as described above.

  On the other hand, even if it is determined that it is not fragmented (step S14), if there is no previous generation backup (step S16: No), a full backup of the RAW image data is performed. Therefore, as described above, the metadata portion of the RAW image data of the SAN device 1 is analyzed, a large file whose capacity exceeds the threshold is extracted, and the extracted file and the data that has not been extracted are deduplicated respectively. To back up (step S18).

  Note that the RAW image restoration unit 22 can read the data of the BG file system 24 based on the information of the RAW image configuration information 25 and restore the data to the SAN device 1 as one RAW image data.

  Here, an example of data writing processing in which the duplicate storage is eliminated by the above-described duplicate elimination storage apparatus 2 will be described with reference to FIGS. For example, as shown in FIG. 7, the deduplication storage device 2 is a server computer that includes a plurality of access nodes 5 that are server computers that control storage and reproduction operations in the storage device 2 itself, and a storage device that stores data. A plurality of storage nodes 6. Note that the number of access nodes 5 and the number of storage nodes 6 are not limited to those shown in FIG. 7, and more nodes 5 and 6 may be connected. Alternatively, the deduplication storage device 2 may be configured by a single computer.

  In addition, the deduplication storage device 2 divides and redundantly stores the data, distributes and stores the data in a plurality of storage devices, and stores the data according to a unique content address set according to the content of the stored data. This is a content address storage system for specifying a storage location.

  The writing process by the deduplication storage apparatus 2 is started by first receiving a file A that is stored data as indicated by an arrow Y1 in FIGS. The file A is, for example, the file “f1” that is a summary of the extracted block data and the data that is a summary of the block data that has not been extracted, as disclosed in FIG.

  Subsequently, the deduplication storage apparatus 2 divides the file A into chunks D that are blocks of a predetermined capacity (for example, 64 KB), as indicated by an arrow Y2 in FIGS. Then, based on the data content of the divided chunk D, a unique hash value H representing the data content is calculated (arrow Y3 in FIG. 9). For example, the hash value H is calculated from the data content of the chunk D using a preset hash function.

  Subsequently, using the hash value H of the chunk D of the file A, it is checked whether or not the chunk D is already stored. At this time, the chunk D that has already been stored is registered in an MFI (Main Fragment Index) file in which the hash value H and the content address CA representing the storage position are stored in association with each other. Therefore, when the hash value H of the chunk D calculated before storage is present in the MFI file, it can be determined that the chunk D having the same content has already been stored. In this case, the content address CA associated with the hash value H in the MFI that matches the hash value H of the chunk D before storage is acquired from the MFI file. Then, this content address CA is returned as the content address CA of the chunk D requested to be written.

  Then, the already stored data referred to by the returned content address CA is used as the chunk D requested to be written. That is, it is assumed that the chunk D requested to be written is stored by designating an area referred to by the returned content address CA as a storage destination of the chunk D requested to be written. As described above, when it is determined that the chunks D related to the write request are duplicated, the writing is completed without actually writing the data itself.

  On the other hand, when it is determined that the chunk D related to the write request is not duplicated and has not been stored yet, the chunk D is written as follows. First, the chunk D is compressed and divided into a plurality of fragment data of a predetermined capacity as indicated by an arrow Y5 in FIG. For example, as shown by reference numerals D1 to D9 in FIG. 8, the chunk D is divided into nine fragment data (divided data F1). Further, even if some of the divided fragment data is missing, redundant data is generated so that the original chunk D can be restored and added to the divided fragment data F1. For example, three pieces of fragment data (redundant data F2) are added as indicated by reference numerals D10 to D12 in FIG. As a result, a data set composed of 12 fragment data composed of 9 divided data F1 and 3 redundant data F2 is generated.

  Subsequently, each fragment data constituting the data set generated as described above is distributed and stored in a plurality of storage devices. At this time, each piece of fragment data is stored in a data storage area called a component (reference numerals 01 to 12) arranged in each storage device (see arrow Y6 in FIG. 9).

  Subsequently, a content address CA representing the storage position of the fragment data D1 to D12 stored as described above, that is, the storage position of the chunk D restored by the fragment data D1 to D12 is generated and managed. Specifically, a part (short hash) of the hash value H calculated based on the contents of the stored chunk D (for example, the top 8B (bytes) of the hash value H) and information indicating the logical storage position, In combination, a content address CA is generated. Then, the content address CA is returned to the file system service (arrow Y7 in FIG. 9), and the identification information such as the file name of the data to be stored is associated with the content address CA and managed by the MFI file described above. (Arrow Y8 in FIG. 9).

  As described above, in the information processing system according to the present embodiment, a file is extracted from RAW image data, and the file and other parts are backed up separately, thereby improving the duplicate storage exclusion rate. it can. In other words, even if the RAW backup of the RAW image data in which the data is fragmented is performed, the extracted file is stored separately, so that the duplication rate of the file is increased and the backup can be performed with a high deduplication rate.

  As described above, since a high deduplication rate can be obtained by RAW backup, there is no need to perform defragmentation processing of the file system. Also, the user need not be aware of the degree of fragmentation. Here, even if defragmentation is performed in a certain backup generation, it can overlap with the backup of the past generation.

  In addition, even if backups from different storage devices contain files similar to the file system image, there is an increased possibility that these RAW backups will be duplicated in the deduplication storage. Improvements can be made. For this reason, it is possible to obtain the same deduplication rate as the backup of each file using the backup server. In other words, since a high deduplication rate can be obtained without requiring a separate backup server or backup software, the cost can be reduced.

  In the above description, the standard that the capacity exceeds the threshold is adopted as the standard for the file extracted from the RAW image data. However, the file may be extracted based on another standard. Further, the data to be extracted is not limited to a file, and data that can be classified into a predetermined group according to other criteria may be extracted. For example, the data may be classified according to the update time, that is, the updated generation, data of a certain generation may be extracted, and the data may be combined and backed up. A specific example will be described with reference to FIG.

  First, in the deduplication storage apparatus 2, an updated generation is stored as RAW image data for each block that is a predetermined unit of data. When the backup generation increases, blocks that have not been updated over a long period (set period) are extracted, and these extracted blocks are combined into one data. Also, unextracted blocks are combined into one data. FIG. 10 shows an example in which the third generation blocks are extracted and combined into one data, and the other generation blocks are combined into one data. Each of these collected data is deduplicated and backed up.

  Here, it is considered that the generation blocks that have not been updated are unlikely to be updated in the future. Therefore, by storing blocks of such generations together as one data, the possibility of duplication between backup generations increases, and the deduplication rate can be improved. In the above description, data of a generation that has not been updated for a long time is extracted. However, data of a predetermined generation may be extracted based on other criteria.

  In the above, the RAW image data is divided into block data and data satisfying a certain standard is extracted. However, the above-described file or a certain generation of data can be obtained by another analysis method without dividing the block image into block data. Data that can be classified into such groups may be extracted.

<Appendix>
Part or all of the above-described embodiment can be described as in the following supplementary notes. The outline of the configuration of the storage system (see FIG. 11), program, and backup method in the present invention will be described below. However, the present invention is not limited to the following configuration.

(Appendix 1)
Image analysis means 101 for analyzing RAW image data to be subjected to RAW backup;
Backup means 102 for storing the RAW image data in the storage device 110 by eliminating duplicate storage and performing RAW backup;
With
The image analysis unit 101 analyzes the raw image data and extracts data that can be classified into a predetermined group from the raw image data.
The backup unit 102 summarizes the data extracted by the image analysis unit as one storage data for each of the classified groups, and combines the data not extracted as one storage data. Store each stored data individually,
Storage system 100.

(Appendix 2)
The storage system according to attachment 1, wherein
The image analysis means divides the RAW image data into block data of a predetermined capacity, classifies and extracts the block data into the groups,
The backup means summarizes the block data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the block data not extracted as one storage data. Store each stored data individually,
Storage system.

(Appendix 3)
The storage system according to appendix 1 or 2,
The image analysis means extracts data that can be classified from the RAW image data into files that satisfy a predetermined criterion set as the group,
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified files, and summarizes the data not extracted as one storage data. Memorize memorized data,
Storage system.

(Appendix 4)
The storage system according to appendix 5,
The image analysis means extracts data that can be classified into the files whose capacity set as the group exceeds a threshold value from the RAW image data.
Storage system.

(Appendix 5)
The storage system according to appendix 1 or 2,
The image analysis means extracts data that can be classified from the RAW image data into a data group in which the update time of the data set as the group satisfies a predetermined criterion,
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified data groups, and summarizes the data not extracted as one storage data. Store each stored data,
Storage system.

(Appendix 6)
The storage system according to appendix 5,
The image analysis means extracts data that can be classified into the data group having the same update time of the data set as the group from the RAW image data.
Storage system.

(Appendix 7)
The storage system according to any one of appendices 1 to 6,
The backup means stores position information in the RAW image data of each data collected in each storage data,
Data output means for outputting as one RAW image data based on each stored data and the position information stored,
Storage system.

(Appendix 8)
The storage system according to any one of appendices 1 to 7,
A distribution determination unit configured to determine a distribution status of data in the RAW image data according to a capacity and arrangement status of data in a predetermined unit in the RAW image data;
The image analysis unit and the backup unit are configured to operate according to the determination result by the dispersion determination unit.
Storage system.

  According to the above invention, first, the image analysis means analyzes the RAW image data and extracts data that can be classified into groups from the RAW image data. For example, data constituting a file whose capacity is equal to or greater than a threshold is extracted, or generation data that can be determined not to be updated for a while is extracted. At this time, the RAW image data may be divided into block data of a predetermined capacity and classified into groups such as files and generations that satisfy a predetermined standard. Then, the backup means collects the data extracted by the image analysis means and the data not extracted as stored data. For example, the extracted data is collected for each classified file or generation, and stored as storage data. Then, the storage data extracted and collected and the storage data collected without being extracted are stored in the storage device while performing redundant storage elimination, and RAW backup is performed. As described above, even in the case of RAW backup, since a large-capacity file, generation data that has not been updated, and the like are stored together, the efficiency of eliminating duplicate storage can be improved.

(Appendix 9)
In the information processing device,
Image analysis means for analyzing RAW image data to be subjected to RAW backup;
Backup means for performing RAW backup by storing the RAW image data in a storage device by eliminating duplicate storage;
And realize
The image analysis means analyzes the RAW image data and extracts data that can be classified into a predetermined group from the RAW image data.
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the data not extracted as one storage data. Store each stored data,
A program to make things happen.

(Appendix 9.1)
The program according to appendix 9, wherein
The image analysis means divides the RAW image data into block data of a predetermined capacity, classifies and extracts the block data into the groups,
The backup means summarizes the block data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the block data not extracted as one storage data. Store each stored data individually,
program.

(Appendix 9.2)
A program according to appendix 9 or 9.1, wherein
The image analysis means extracts data that can be classified from the RAW image data into files that satisfy a predetermined criterion set as the group,
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified files, and summarizes the data not extracted as one storage data. Memorize memorized data,
program.

(Appendix 9.3)
A program according to appendix 9 or 9.1, wherein
The image analysis means extracts data that can be classified from the RAW image data into a data group in which the update time of the data set as the group satisfies a predetermined criterion,
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified data groups, and summarizes the data not extracted as one storage data. Store each stored data,
program.

(Appendix 10)
Analyzing the raw image data subject to raw backup,
The RAW image data is stored in a storage device by eliminating duplicate storage, and RAW backup is performed.
During the analysis of the RAW image data, data that can be classified into a predetermined group is extracted from the RAW image data,
The data extracted by the analysis of the RAW image data at the time of the RAW backup is summarized as one storage data for each of the classified groups, and the data not extracted is summarized as one storage data. Store each stored data individually,
Backup method.

(Appendix 10.1)
The backup method according to appendix 10, wherein
When analyzing the RAW image data, the RAW image data is divided into block data of a predetermined capacity, and the block data is classified into the group and extracted.
At the time of the RAW backup, the block data extracted by the analysis of the RAW image data is grouped as one storage data for each of the classified groups, and the block data not extracted is grouped as one storage data. , Memorize each of these storage data,
Backup method.

(Appendix 10.2)
The backup method according to appendix 10 or 10.1,
During the analysis of the RAW image data, data that can be classified into files that satisfy the predetermined criteria set as the group is extracted from the RAW image data,
The data extracted by the analysis of the RAW image data at the time of the RAW backup is summarized as one storage data for each of the classified files, and the data not extracted is summarized as one storage data. Memorize each stored data,
Backup method.

(Appendix 10.3)
The backup method according to appendix 10 or 10.1,
During the analysis of the RAW image data, data that can be classified into a data group in which the update time of the data set as the group satisfies a predetermined standard is extracted from the RAW image data,
In the RAW backup, the data extracted by the analysis of the RAW image data is summarized as one storage data for each of the classified data groups, and the data not extracted is summarized as one storage data, Store each of these stored data,
Backup method.

  Note that the above-described program is stored in a storage device or recorded on a computer-readable recording medium. For example, the recording medium is a portable medium such as a flexible disk, an optical disk, a magneto-optical disk, and a semiconductor memory.

  Although the present invention has been described with reference to the above-described embodiment and the like, the present invention is not limited to the above-described embodiment. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

DESCRIPTION OF SYMBOLS 1 SAN apparatus 10 Communication part 11 Difference map acquisition part 12 Pairing part 13 Replicate part 14 Separate part 15 Difference information storage part 16 Difference map information 17 MV
18 RV
2 Deduplication storage device 20 Communication unit 21 RAW backup unit 22 RAW image restore unit 23 FG file system 24 BG file system 25 RAW image configuration information 26 Fragmentation determination unit 27 RAW image analysis unit 28 Extraction block determination unit 29 File instantaneous copy unit 3 Business server device 100 Storage system 101 Image analysis means 102 Backup means 110 Storage device

Claims (10)

Image analysis means for analyzing RAW image data to be subjected to RAW backup;
Backup means for performing RAW backup by storing the RAW image data in a storage device by eliminating duplicate storage;
With
The image analysis means analyzes the RAW image data and extracts data that can be classified into a predetermined group from the RAW image data.
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the data not extracted as one storage data. Store each stored data,
Storage system. The storage system according to claim 1,
The image analysis means divides the RAW image data into block data of a predetermined capacity, classifies and extracts the block data into the groups,
The backup means summarizes the block data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the block data not extracted as one storage data. Store each stored data individually,
Storage system. The storage system according to claim 1 or 2,
The image analysis means extracts data that can be classified from the RAW image data into files that satisfy a predetermined criterion set as the group,
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified files, and summarizes the data not extracted as one storage data. Memorize memorized data,
Storage system. The storage system according to claim 5,
The image analysis means extracts data that can be classified into the files whose capacity set as the group exceeds a threshold value from the RAW image data.
Storage system. The storage system according to claim 1 or 2,
The image analysis means extracts data that can be classified from the RAW image data into a data group in which the update time of the data set as the group satisfies a predetermined criterion,
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified data groups, and summarizes the data not extracted as one storage data. Store each stored data,
Storage system. The storage system according to claim 5,
The image analysis means extracts data that can be classified into the data group having the same update time of the data set as the group from the RAW image data.
Storage system. The storage system according to any one of claims 1 to 6,
The backup means stores position information in the RAW image data of each data collected in each storage data,
Data output means for outputting as one RAW image data based on each stored data and the position information stored,
Storage system. The storage system according to any one of claims 1 to 7,
A distribution determination unit configured to determine a distribution status of data in the RAW image data according to a capacity and arrangement status of data in a predetermined unit in the RAW image data;
The image analysis unit and the backup unit are configured to operate according to the determination result by the dispersion determination unit.
Storage system. In the information processing device,
Image analysis means for analyzing RAW image data to be subjected to RAW backup;
Backup means for performing RAW backup by storing the RAW image data in a storage device by eliminating duplicate storage;
And realize
The image analysis means analyzes the RAW image data and extracts data that can be classified into a predetermined group from the RAW image data.
The backup means summarizes the data extracted by the image analysis means as one storage data for each of the classified groups, and summarizes the data not extracted as one storage data. Store each stored data,
A program to make things happen. Analyzing the raw image data subject to raw backup,
The RAW image data is stored in a storage device by eliminating duplicate storage, and RAW backup is performed.
During the analysis of the RAW image data, data that can be classified into a predetermined group is extracted from the RAW image data,
The data extracted by the analysis of the RAW image data at the time of the RAW backup is summarized as one storage data for each of the classified groups, and the data not extracted is summarized as one storage data. Store each stored data individually,
Backup method.

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