JP2009282563A - Data storage system, program, method, and monitoring device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To reduce resources necessary for the operation of stored data. <P>SOLUTION: This data storage system for acquiring and storing storage object data in each of a plurality of different times is provided with: a means for storing the whole data of reference storage target data as storage object data acquired at an arbitrary time; a means for storing the whole data of the previous storage target data as storage target data acquired at a time prior to the reference storage target data; a means for generating difference data between the whole data of the reference storage object data and the whole data of the previous storage object data; and a difference data storage means for storing the generated difference data. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a data storage system, a program and method, and a monitoring device, and can be applied to a system that collects and stores data at a plurality of times, for example.

  The conventional data backup in a database or the like, or the version management function in the data backup, can obtain a full backup of data periodically or arbitrarily and can perform differential backup of data up to the present. Further, in order to delete a past version of data, a deletion target is detected from difference information and full backup data up to that version, and the deletion target full backup data and difference information are deleted (Non-Patent Document 1). reference).

Further, in a conventional so-called version management system (for example, CVS (Current Versions System), Subversion, etc.), the oldest data is held as full data, and only the changed difference information is managed when the version is changed thereafter. (See Non-Patent Document 2).
Published by Yoshinobu Matsuno, “MySQL that can be used in the field”, published by Shosuisha in March 2006 By Karl Fogel, Rika Takeuchi, Debangle Translation, “CVS Version Control System”, published in May 2000 by Ohmsha

  However, in the database described in Non-Patent Document 1, differential backup between data versions was possible. When extracting past information, a method of extracting by sequentially applying differential backup from fully backed up data However, it was also difficult to delete data before any version. In addition, when a full backup of a conventional database is regularly performed, as the number of versions to be managed increases, the magnetic disk of the system that performs version management is pressed. In addition, the processing performance required to retrieve and delete past versions of data cannot be processed at high speed.

  Also, in the CVS described in Non-Patent Document 2, when data with a past version is taken out, all the data of the past version specified by applying differential information to the oldest full data one by one is restored. Then, since it is a process of extracting desired data, it cannot be processed at high speed. In addition, it is impossible to delete data before any version.

  For this reason, a large amount of network information (for example, about 5 minutes) is obtained in a short period (for example, about 5 minutes) by network monitoring by MIB (Management Information Base) data acquisition by SNMP (Simple Network Management Protocol) or alive monitoring by Ping. In a monitoring device that collects about 10,000 cases and keeps the state of the past network, the conventional database backup method uses the load status of the nodes existing on the network for an arbitrary time. Searching the connection status and deleting any past version data is time consuming and inefficient, and compresses the magnetic disk with a large amount of backup data. Needed. In addition, it is impossible to delete arbitrary past version data in CVS.

  Therefore, a data storage system, program and method, and monitoring device that can reduce resources required for operating stored data are desired.

  The data storage system according to the first aspect of the present invention is (1) a data storage system that acquires and stores storage target data at a plurality of different times, and (2) a reference that is storage target data acquired at an arbitrary time. Reference whole data storage means for saving the whole data of the storage target data, and (3) front whole data holding the whole data of the forward storage target data which is the storage target data acquired at a time before the reference storage target data. (4) difference data generation means for generating difference data between the whole data stored in the reference whole data storage means and the whole data held in the front whole data holding means; And a difference data storage unit for storing the difference data generated by the difference data generation unit.

  The data storage program according to the second aspect of the present invention provides (1) a computer mounted in a data storage system that acquires and stores data to be stored at a plurality of different times, and (2) stores acquired at an arbitrary time. Reference entire data storage means for storing the entire data of the reference storage target data that is the target data; and (3) the entire data of the forward storage target data that is the storage target data acquired at a time before the reference storage target data. Forward whole data holding means for holding, (4) difference data generation for generating difference data between the whole data saved by the reference whole data saving means and the whole data held by the front whole data holding means And (5) functioning as difference data storage means for storing difference data generated by the difference data generation means.

  The data storage method of the third aspect of the present invention is (1) a data storage method in a data storage system that acquires and stores data to be stored at a plurality of different times, and (2) reference whole data storage means, A data holding unit, a difference data generation unit, and a difference data storage unit; (3) the reference entire data storage unit stores the entire data of the reference storage target data that is the storage target data acquired at an arbitrary time; (4) The front whole data holding unit holds whole data of the front storage target data that is the storage target data acquired at a time before the reference storage target data, and (5) the difference data generation unit includes: Difference data between the whole data stored by the reference whole data storage unit and the whole data held by the front whole data storage unit is generated, (6 The difference data storage means, characterized by storing the difference data the differential data generating means has generated.

  A monitoring apparatus according to a fourth aspect of the present invention is (1) a monitoring apparatus that collects data related to monitoring of the node from one or a plurality of nodes and monitors the node. (2) data collected from the node Is stored using the data storage system of the first aspect of the present invention.

  According to the present invention, resources necessary for operating stored data can be reduced.

(A) Main Embodiment Hereinafter, an embodiment of a data storage system, program and method, and monitoring apparatus according to the present invention will be described in detail with reference to the drawings. Note that the monitoring device of this embodiment collects and stores data related to monitoring from one or a plurality of nodes, and applies the data storage system of this embodiment.

(A-1) Configuration of Embodiment FIG. 1 is a block diagram showing a functional configuration of a data storage system 1 of this embodiment.

  In FIG. 1, the data storage system 1 collects data from each of three data collection targets 2 (2-1 to 2-3), stores version data at each time, and receives a request from the client 3 Then, data corresponding to the request is extracted from the stored data and returned to the client 3. In FIG. 1, three data collection targets 2 are arranged. However, the number may be single, and the number is not limited.

  The data collection target 2 stores data to be collected by the data storage system 1, and includes, for example, a MIB database stored in a network node, a storage device mounted on a database server, and the like. It is done. The data collection target 2 may be data on a computer or a file storing data, and is not limited. In this embodiment, for example, the data collection target 2 is mounted on a network node. It is assumed that the data storage system 1 collects and stores status information (hereinafter referred to as “status information”) of different network nodes. The data storage system 1 may collect a plurality of data (MIB data) from one node, but in this embodiment, it is assumed that only status information is collected for all nodes. As status information, for example, information such as ACT (indicating that the network node is active), BUSY (indicating that the network node is busy), and the like are collected.

  The data storage system 1 collects data to be collected from the data collection target 2 (2-1 to 2-3), performs version management for each collected time, and stores the data. Then, the data storage system 1 searches for an arbitrary version of data and outputs the detected data. The output of data detected by the data storage system 1 may be displayed on a display device such as a display, printed on a printing device such as a printer, or stored in a storage device such as a disk device. In this embodiment, the data storage system 1 searches for data at an arbitrary time (version) in response to a request from the client 3 and outputs the detected data to the client 3. To reply to.

  In this embodiment, the data storage system 1 is described as collecting data from the data collection target 2 at a timing according to a request from the client 3, but data may be collected periodically. The user may directly operate the data storage system 1 or may collect data at a randomly set timing. The data storage system 1 may collect data from the data collection target 2. Is not limited.

  In a conventional data storage system, when data is first collected from the data collection target, all the data collection target data is collected, the entire data (hereinafter referred to as “full data”) is stored, and then If data is collected from the data collection target at the point of time, only the difference from the saved full data is extracted and saved. On the other hand, in the data storage system 1 of this embodiment, contrary to the conventional system, the version collected at the latest time is full data (data collected from all the data collection targets 2-1 to 2-3 at the same time). The entire version) is saved, and for the version at a time earlier than that, the difference based on the full data of the latest version is held. As a method of generating the difference data based on the latest full data as described above in the data storage system 1, for example, in the state where the previous version of the full data is already held, the latest version When full data is collected, a difference between two full data may be extracted. The data storage system 1 stores data for each time (version) at which data is collected by repeatedly storing the extracted difference.

  In this way, the data storage system 1 performs data storage for each time (version) of data collected from the data collection target, and further searches and extracts data at a desired time (version).

  The client 3 is a client device that operates the data storage system 1. For example, a data collection instruction to the data storage system 1, a past version data search request to the data storage system 1, and a past version data to the data storage system 1. This is an instruction to delete the file.

  Next, details of each component of the data storage system 1 will be described.

  The data storage system 1 includes a data collection unit 11, a temporary storage unit 12, a current data storage unit 13, a difference extraction unit 14, a database 15, a past version data search unit 16, and a previous data deletion unit 17. The data storage system 1 is, for example, a data storage program according to the embodiment (not limited to one, but may be a system that can perform a plurality of distributed processing) such as a personal computer. It may be constructed by installing (including fixed data) and functionally can be represented as in FIG.

  The data collection unit 11 is means for reading data to be collected from the data collection targets 2-1 to 2-3. As a means for the data collection unit 11 to read data to be collected from the data collection targets 2-1 to 2-3, the data collection unit 11 may be connected via a wired or wireless network, or directly by a wired or wireless interface. You may connect. Further, for example, data may be read off-line using a recording medium such as DAT (Digital Audio Tape) or CD, and the method of reading the data is not limited.

  The data collection unit 11 collects data from the data collection target 2 and temporarily stores the collected data in the temporary storage unit 12. In addition, the data collection unit 11 adds 1 to the value of the version_count column of the version number registration unit 151 in the database 15 and updates the data collection target 2-1 to 2-3 at each timing of data collection. Further, the data collection unit 11 may collect data from the data collection target 2 in accordance with an operation from the client 3.

  The difference extraction unit 14 extracts a difference between the latest collected data held in the temporary storage unit 12 and the previously collected data held in the current data storage unit 13, and the result is stored in the database 15 (difference To the data management table 153).

  The previous data deletion unit 17 deletes data collected last time. When the difference extraction unit 14 completes the difference extraction process, the previous data deletion unit 17 performs batch deletion of the previously collected data stored in the full data table 152.

  When the previous data deletion unit 17 completes the deletion of the previously collected data stored in the full data table 152, the current data storage unit 13 stores the latest full data stored in the temporary storage unit 12 as the full data. Save in table 152. The format of data stored in the data storage unit 13 this time is the same format as the contents of the full data table 152 described later.

  The past version data search unit 16 searches the data in the database 15 when a client 3 requests a past version data search, and if the requested data is detected from the client 3, Data is returned to the client 3. Further, when there is an instruction to delete data of the past version from the client 3, it is also possible to search the table in the database 15 and delete the version management information to be deleted.

  The temporary storage unit 12 is a storage unit that temporarily saves the latest full data collected by the data collection unit 11.

  The database 15 is a database that manages collected data and collected data in the data storage system 1, and includes a version number registration unit 151, a full data table 152, and a difference data management table 153.

  FIG. 2 is an explanatory diagram showing an example of contents stored in the version number registration unit 151.

  The version number registration unit 151 is a version number table in the database 15. The version number registration unit 151 has, for example, a column (hereinafter referred to as “column”) for storing data in a format as shown in FIG.

  The version number registration unit 151 has a column called version_count as shown in FIG. The version_count is a variable that is incremented by 1 each time the data collection unit 11 collects data from the data collection targets 2-1 to 2-3. Also, version_count will be described assuming that the default value when the data storage system 1 is started is “0”. In this way, the version number registration unit 151 manages, for example, what version the latest version data is.

  FIG. 3 is an explanatory diagram showing the contents stored in the full data table 152.

  The full data table 152 is a table for managing full data in the database 15. The full data table 152 stores data having three columns of name, date, and status as shown in FIG. In this embodiment, the database 15 will be described assuming that information collected from the data collection targets 2-1 to 2-3 is stored for each data collection target 2.

  The “name” column is an identifier for identifying data to be stored, and is set with unique contents in the full data table 152.

  If the content set in the name column is unique in the full data table 152 as described above, the node names (for example, host names) of the nodes related to the data collection targets 2-1 to 2-3, The contents to be set such as random contents and consecutive numbers are not limited.

  The “status” column is a column for storing status information acquired from the data collection target 2 corresponding to the “name” column. In this embodiment, in order to simplify the description, it is assumed that the data collected from each data collection target 2 is only status. However, as described above, a plurality of data may be stored or collected. When the data is a file storing data, the file is linked to the full data table 152 (for example, the file is stored in another storage area, and the storage location is specified in the full data table 152). The content of the data collected from the data collection target 2 is not limited. As described above, information such as “ACT” and “BUSY” is stored in the “status” column.

  The “date” column is a column for storing information on the time when the information stored in the “status” column is acquired.

  FIG. 4 is an explanatory diagram showing contents stored in the difference data management table 153.

  The difference data management table 153 is a table for managing the difference data from the full data table 152 for each version in the database 15.

  In the differential data management table 153, compared with the full data collected at the previous collection, added data (hereinafter referred to as “additional data”), deleted data (hereinafter referred to as “deletion data”), and updated. Data (hereinafter referred to as “update data”) is stored.

  The additional data is generated when newly added data is collected as compared to the previous data collection time. In this embodiment, for example, additional data is generated when the data collection target 2 is added.

  Deleted data is generated when there is deleted data compared to the previous data collection. In this embodiment, for example, this occurs when there is a data collection target 2 that has been removed (deleted) from the collection target.

  The update data is generated when there is updated data as compared to the previous data collection time. In this embodiment, for example, this occurs when the data collected for the same data collection target 2 is different from the previous collection.

  The difference data management table 153 will be described as having six columns of name, date, status, add, del, and update as shown in FIG.

  Since name, date, and status are substantially the same as those of the above-described full data table 152, detailed description thereof is omitted.

  The “add” column indicates whether or not the data is additional data and at what time (version) the data is added. If it is not additional data (that is, if it is deletion or update data), “NULL” is stored in the add column, and if it is additional data, the number of the version immediately before being added (that is, The value of version_count-1) is stored. In this embodiment, “NULL” is input to the status and date of the additional data in the difference data management table 153.

  The “del” column indicates whether or not the data is deleted data, and if it is deleted data, the time (version) at which the data was deleted. If it is not deleted data (that is, if it is addition or update data), “NULL” is stored in the del column, and if it is deleted data, the version number immediately before deletion (that is, The value of version_count-1) is stored. In the status column, data in the status column immediately before deletion is stored.

  The “update” column indicates whether or not the data is update data, and if it is update data, at which time (version) it was updated. When it is not update data (that is, when it is addition or deletion data), “NULL” is stored in the update column, and when it is update data, the number of the version immediately before being updated (that is, when it is update data) The value of version_count-1) is stored. In the case of update data, the status column stores data in the status column immediately before being updated.

(A-2) Operation of Embodiment Next, the operation of the data storage system of this embodiment having the above-described configuration (data storage method of the embodiment) will be described.

(A-2-2) Differential Data Extraction First, in the data storage system 1, data is collected from the data collection target 2, differential data between the data collected last time and the data collected this time is generated, and the differential data management table 153 The operation to store in will be described.

  FIG. 5 is a flowchart showing an operation of generating and storing deletion data and update data among the difference data in the data storage system 1.

  First, it is assumed that the data storage system 1 has been activated (S101).

  Next, when a data collection request is notified from the client 3 to the data storage system 1, in the data storage system 1, the data collection unit 11 causes the data collection target 2-1 to 2-3 to collect data to be collected. Are collected and held in the temporary storage unit 12 (S102).

  Next, in the data storage system 1, 1 is added to the value of version_count in the version number registration unit 151 (S103).

  Next, it is determined whether or not the version_count value of the version number registration unit 151 is 1, that is, whether or not it is the first data collection in the data storage system 1. If version_count = 1, step S107 described later is performed. If version_count = 1 is not satisfied, the operation starts from the processing of step S105 described later (S104).

  If it is determined in S <b> 104 that version_count = 1 is not satisfied, the data storage system 1 stores the previous collection data stored in the full data table 152 and the current collection stored in the temporary storage unit 12. The difference data is extracted and stored in the difference data management table 153 (S105). Details of the processing in S105 described above will be described later.

  Next, in the data storage system 1, the data collected last time stored in the full data table 152 is deleted (S106).

  If it is determined that version_count = 1 in step S104 described above, or if data collected last time is deleted in step S106 described above, the data storage system 1 stores the temporary storage unit 12 in the full data table 152. The data collected this time is held.

  Then, the data storage system 1 shifts to the sleep state, and when the next data collection instruction is issued from the client 3, it starts again from the above-described step S102 (S108).

  Next, the details of the differential data extraction operation in step S105 described above will be described. In the data storage system 1, since the difference data extraction is different between the operation of the deletion and update data and the operation of the addition data, in this embodiment, the operation of extracting the deletion and update data will be described first, and then added. An operation for extracting data will be described. In the data storage system 1, the order of extracting the deletion data, the update data, and the additional data is not limited.

  FIG. 6 is a flowchart showing an operation of generating and storing deletion and update data among the difference data in the data storage system 1.

  First, when the differential data extraction process is started (S201), the differential extraction unit 14 acquires data for the previous collection stored in the full data table 152 (S202).

  Next, the difference extraction unit 14 extracts one piece of data stored in the name column from the acquired data for the previous collection (S203).

  Next, it is determined whether or not data that matches the data extracted in step S203 described above exists in the data for the current collection held in the temporary storage unit 12 (S204), and the corresponding data exists. If it is determined, the operation starts from step S206 described later. If it is determined that the corresponding data does not exist, the operation starts from step S205 described later.

  If it is determined in step S204 that there is no corresponding data, the data retrieved in step S203 is deleted between the time when the data was collected from the time when the data was collected last time. Since it is data, deletion data is created and stored in the difference data management table 153 (S205). Details of the deletion data creation operation in step S205 will be described later.

  On the other hand, if it is determined in step S204 that the corresponding data exists, the name column, date between the data extracted in step S203 described above and the data detected in step S204 described above. It is determined whether or not the contents of all the columns and the Status column match (S206). In step S206, if all the contents of the name column, date column, and status column match in the two data, the data has been updated between the time when the previous data was collected and the time when the data was collected this time. This indicates that the content has not been updated, and if any of the contents do not match, it indicates that the content has been updated, and the operation starts from step S207 described later.

  In the above-described step S206, when it is determined that the data has been updated between the time when the previous data was collected and the time when the data was collected this time, the update data is stored for the data extracted in the above-described step S203. Created and stored in the difference data management table 153 (S207). Details of the operation in which update data is created in step S207 and stored in the difference data management table 153 will be described later.

  When one of the processes in steps S205 to 207 is completed, it is determined whether or not the determination in step S204 or S206 is performed for all the data acquired in step S202. If there is data that has not been determined, the operation starts again from the above-described step S203 (S208).

  When it is determined in step S208 described above that the determinations in S204 and S206 have been made for all data, the deletion and update data extraction processing ends (S209).

  FIG. 7 is a flowchart illustrating an operation of generating and storing additional data among the difference data in the data storage system 1.

  In the difference extraction unit 14, when the deletion and update data extraction operations are completed by the process shown in FIG. 6 described above, an operation of extracting additional data from the difference data is started (S301).

  And the difference extraction part 14 acquires the data for the last collection stored in the full data table 152 (S302).

  Next, the difference extraction unit 14 extracts one piece of data stored in the name column from the data collected this time stored in the temporary storage unit 12 (S303).

  Next, it is determined whether there is data that matches the data extracted in step S303 described above in the previous collection data acquired in step S302 (S304), and it is determined that the corresponding data exists. If it is determined, the operation starts from step S306 described later. If it is determined that the corresponding data does not exist, the operation starts from step S305 described later.

  If it is determined in step S304 that there is no corresponding data, the data extracted in step S303 is added between the time when the data was collected this time and the time when the data was collected this time. Since it is data, additional data is created and stored in the difference data management table 153 (S305). The details of the operation in step S305 where additional data is created and stored in the difference data management table 153 will be described later.

  When it is determined in step S304 described above that the corresponding data exists, or when the processing in step S305 described above ends, all of the data for the current collection acquired in step S303 described above is stored in step S304 described above. If there is data for which the determination in step S304 has not been performed and the determination in step S304 has not been performed, the operation starts again from step S303 described above (S306).

  If it is determined in step S306 described above that the determination in step S304 has been performed for all data, the additional data extraction process of the difference data ends (S307), and the deletion data, update data, The extraction process is completed for all the additional data.

  Next, the deletion data storing operation in step S205 described above will be described.

  FIG. 8 is a flowchart illustrating an operation in which deletion data is generated and stored by the difference extraction unit 14.

  First, in the above-described step S205, when the deletion data storage process in the difference data management table 153 is started (S401), the data extracted in the above-described step S203 (part of the previously collected data) An entry is added to the difference data management table 153, and the contents of the corresponding name column, date column, and status column are input (S402).

  In step S402 described above, the version number of the data collected last time, that is, the value obtained by subtracting 1 from the value in the version_count column of the version number registration unit 151 is stored in the del column of the entry added to the difference data management table 153. (S403).

  Then, “null” is stored in the add column and the update column of the entry added to the differential data management table 153 in step S402 described above (S404), and the operation of storing the deleted data ends (S405).

  Next, the update data storage operation in step S207 will be described.

  FIG. 9 is a flowchart showing the operation of generating and storing update data by the difference extraction unit 14.

  First, when storage processing of update data in the difference data management table 153 is started in step S207 described above (S501), an entry is added to the difference data management table 153 for the data extracted in step S203 described above. The contents of the corresponding name column, date column, and Status column are input (S502).

  In step S502 described above, the update column of the entry added to the difference data management table 153 stores the version number of the previously collected data, that is, a value obtained by subtracting 1 from the value of the version_count column of the version number registration unit 151. (S503).

  In step S502, “null” is stored in the add column and del column of the entry added to the difference data management table 153 (S504), and the update data storage operation ends (S505).

  A procedure for adding additional data to the difference data management table 153 is shown in FIG. 7, and a detailed description of the procedure in FIG. 7 is given below.

  FIG. 10 is a flowchart illustrating the operation of saving and storing additional data by the difference extraction unit 14.

  First, in the above-described step S305, when the storage process of additional data to the differential data management table 153 is started (S601), an entry storing null in the name column, the date column, and the Status column is stored in the differential data management table 153. It is added (S602).

  In step S602 described above, the add column of the entry added to the difference data management table 153 stores the version number of the previously collected data, that is, a value obtained by subtracting 1 from the value of the version_count column of the version number registration unit 151. (S603).

  In step S602 described above, “null” is stored in the update column and the del column of the entry added to the difference data management table 153 (S604), and the operation of storing additional data ends (S605).

  As described above, the data storage system 1 of this embodiment performs data collection and differential data extraction. By such a procedure, only the latest version data is always stored in the full data table 152, and the difference data between versions is managed together with the version number for the previous collection in the difference data management table 153. It becomes the structure which does not need to preserve | save full data.

(A-2-2) Specific Example of Differential Data Extraction Next, in the database 15 of the data storage system 1, how full data and differential data are specifically processed, a full data table 152, and a differential data management table 153 will be described.

  FIG. 15 is an explanatory diagram of data stored in the full data table 152.

  FIG. 15A is an explanatory diagram showing an example of data stored in the full data table 152 at the time when data is collected for the first time (version_count = 1). FIG. 15B is an explanatory diagram showing an example of data stored in the full data table 152 at the time when data was collected for the second time (version_count = 2). FIG. 15C is an explanatory diagram showing an example of data stored in the full data table 152 at the time when data was collected for the third time (version_count = 3).

  FIG. 16 is an explanatory diagram of data stored in the difference data management table 153. FIG. 16A is an explanatory diagram showing an example of data stored in the differential data management table 153 at the time when data is collected for the second time (version_count = 2). FIG. 16B is an explanatory diagram showing an example of data stored in the difference data management table 153 at the time when data is collected for the third time (version_count = 3).

  15 and 16, the contents set in the name column corresponding to the data collection targets 2-1, 2-2, and 2-3 are “node A”, “node B”, and “node C”, respectively. It will be explained as a thing.

  At the time when data is collected for the second time (when version_count = 2), the contents of FIG. 15A are stored in the full data table 152, and the contents of FIG. 15B are stored in the temporary storage unit 12. Then, the contents shown in FIG. 16A are created and stored in the difference data management table 153 by the operations shown in the flowcharts of FIGS. At this time, since the data of the node A and the node B is updated, the data of L221 and L222 are additionally stored as update data.

  Next, at the time when data is collected for the third time (when version_count = 3), the content of FIG. 15B is stored in the full data table 152 and the content of FIG. 15C is stored in the temporary storage unit 12. Assuming that the difference data is added by the operations shown in the flowcharts of FIGS. 5 to 10 described above, the contents of FIG. 16B are stored in the difference data management table 153. At this time, since the data of the node B and the node C are updated, the data of L231 and L232 are additionally stored as update data.

(A-2-3) Search for Arbitrary Data Next, an operation for searching for past versions of data in the data storage system 1 will be described.

  FIGS. 11 to 13 are flowcharts showing an operation of searching for past versions of data in the data storage system 1 in the data storage system 1.

  In FIG. 11 to FIG. 13, when the data collection system is activated and the version_count of the current version number registration unit 151 is m, that is, when the number of times of data collection in the past is m, the VerSion_count is received from the client 3. Assume that there is a request to search past data whose name is “A” at the time of n (m> n).

  When the past version data search unit 16 starts searching for data whose name is A when the version_count is n (S701), first, in the differential data management table 153, name = A and the value of the del column (hereinafter, Among the entries of data in which “del_num” is n or more and m or less, the entry having the smallest del_num in the del column (hereinafter referred to as “del_entry”) is searched (S702).

  The past version data search unit 16 determines whether or not the corresponding del_entry has been detected in S702 described above (S703). If the corresponding del_entry has been detected, the operation starts from the processing in step S704 described later. If del_entry is not detected, the operation starts from the processing of S705 described later.

  If it is determined in step S703 described above that the corresponding del_entry has not been detected, the version number m is substituted for the variable X (S705), and the operation starts from step S706 described below.

  If it is determined in step S703 described above that the corresponding del_entry has been detected, the value of the del_entry del column is substituted for the variable X (S704), and the operation starts from step S706 described below. Note that in step S704 described above, the corresponding del_entry has been detected. If the current version of the data has the search target name = A, the data of name = A obtained as the search result is currently This is a different system from the version of the data. In this embodiment, a process for executing a search that can return a past series of data even if the series of data of the search result is a series of data different from the current version data will be described in S706 and later.

  After the process of step S704 or S705 described above, from the difference data management table 153, an entry of data (hereinafter referred to as “add_num”) in which name = “A” and the value of the add column (hereinafter referred to as “add_num”) is n or more and X or less. , “Add_entry”) is searched (S706).

  Then, in the above-described step S706, it is determined whether or not the corresponding add_entry has been detected (S707). If the corresponding add_entry is detected, the operation starts from the processing in step S708 described later and is not detected. In the case of failure, the operation starts from step S801 (see FIG. 12) described later.

  If the corresponding add_entry is detected in step S707 described above, the search result is unregistered, the search result is returned to the client 3, and the process ends (S708).

  If the corresponding add_entry is not detected in step S707 described above, the past version data search unit 16 sets name = “A” in the difference data management table 153 and the value of the update column (hereinafter, “ The entry having the smallest update_num in the update column (hereinafter referred to as “update_entry”) is searched for among the data entries in which “update_num” is n or more and X or less (S801).

  In the above-described step S801, it is determined whether or not the corresponding update_entry has been detected (S802). If the corresponding update_entry is detected, the operation starts from the processing of step S803 described later, and the corresponding update_entry must not be detected. For example, the operation starts from the processing in step S901 (see FIG. 13) described later.

  If it is determined in step S802 above that the corresponding update_entry has not been detected, the update_entry entry data is returned to the client 3 as a search result, and the process is terminated (S803).

  In step S702 described above, it is determined whether or not the corresponding del_entry has been detected (S901). If the corresponding del_entry has been detected, the process proceeds from the process of step S902 described later, and the corresponding del_entry is detected. If not, the operation starts from step S903 described later.

  If it is determined in step S901 that the corresponding del_entry has been detected, the entry data of del_entry is returned to the client 3 as a search result, and the process ends (S902).

  If it is determined in step S901 that the corresponding del_entry has not been detected, the past version data search unit 16 makes an entry of name = "A" (hereinafter referred to as "fulldata_entry") in the full data table 152. ) Is retrieved (S903).

  In step S904 described above, it is determined whether or not the corresponding fulldata_entry has been detected (S904). If the corresponding fulldata_entry has been detected, the operation is performed from the processing of step S905 described later, and the corresponding fulldata_entry is detected. If not, the operation starts from step S906 described later.

  If it is determined in step S904 described above that the corresponding fulldata_entry has been detected, the entry data of fulldata_entry is returned to the client 3 as a search result, and the process ends (S905).

  On the other hand, if it is determined in step S904 described above that the corresponding fulldata_entry has not been detected, the search result is returned to the client 3 as unregistered, and the process ends (S906).

  The details of the past data search operation in the data storage system 1 have been described above. It is possible to easily perform a search without needing a procedure for performing a search for data to be searched after expanding the past version data to be searched as full data by the operation shown in FIGS. Is possible.

(A-2-4) Past Version Data Deletion FIG. 14 is a flowchart showing an operation of deleting past data (data older than the specified version) in the data storage system 1.

  In FIG. 14, as an example, when version_count of the current version number registration unit 151 is m, that is, when the current version number is m, from client 3, version_count is n (m> n). It is assumed that there is an instruction to delete old data.

  When there is a request from the client 3 to delete data whose version_count is older than n, in the data storage system 1, the past version data search unit 16 starts the process (S1001).

  In the difference data management table 153, all entries whose add column value is n or less, update column value is n or less, or del column value is n or less are collectively deleted, and the process ends (S1002). .

  By the above-mentioned operation, when deleting data older than the specified version, it is easy without detecting the specified version of the data from the full backup data and the difference information and executing the deletion. Can be deleted.

(A-3) Effects of Embodiment According to this embodiment, the following effects can be achieved.

  In the data storage system 1, only the latest version of data is stored in the full data table 152, and the difference data between versions is managed in the difference data management table 153, so that it is not necessary to take a full backup for each version. Therefore, the storage capacity required in the data storage system 1 can be reduced.

  In the data storage system 1, when searching for arbitrary data of an arbitrary version in the past, the procedure for executing search of data to be searched after expanding the past version of data to be searched as full data is as follows. Since it is possible to search the data of the past version target easily and at high speed only by the search in the difference data management table 153 without the necessity, the processing amount required for the data detection can be reduced.

  Furthermore, in the data storage system 1, it is possible to select whether or not data of the same series as arbitrary data to be searched is extracted as a search result or not depending on the mounting method.

  Furthermore, the data storage system 1 does not require a procedure for detecting and deleting the specified version data from the full backup data and the difference information when deleting the version older than the specified version. Therefore, it is possible to perform deletion only by condition matching deletion in the difference data management table 153, and the processing amount and storage capacity required for deletion can be reduced. This also facilitates maintenance and management of machines used in the version management system. For example, it is possible to delete all data older than a specified version with an SQL (Structured Query Language) statement of about one line from the differential data management table 153.

  As described above, the data storage system 1 can reduce resources such as a processing amount and a storage capacity required for performing an operation such as searching or deleting an arbitrary version of the stored data. . This has an effect that more resources can be reduced, particularly when a large amount of data needs to be collected in a short cycle.

(B) Other Embodiments The present invention is not limited to the above-described embodiments, and may include modified embodiments as exemplified below.

(B-1) The data storage system 1 in the above embodiment is applied to a monitoring device that collects MIB data acquisition by SNMP from nodes such as network devices and various servers, for example, and collected data of the monitoring system You may make it preserve | save. In addition, the data storage system in the above embodiment may be applied to a system or apparatus that stores data at a plurality of times.

  In particular, the monitoring information is collected in a large amount (for example, about 260,000) in a short period (for example, about 5 minutes), and applied to a monitoring device that must keep the state of the past network. In this case, it is possible to search for the load status and connection status of the nodes existing on the network at any time, and to delete data of any past version with a smaller amount of processing, and to reduce the required storage capacity. Can do.

(B-2) In the above embodiment, the data storage system 1 stores the latest version of the full data and the difference data of the version at each past time, but is not limited to the latest version, and before that Save the full data acquired at the time of, and use the full data (hereinafter referred to as “reference full data”) as a reference to the full data acquired at the time before the reference full data (hereinafter referred to as “front full data”). Such difference data may be stored. Further, the data storage system 1 may store difference data relating to full data (hereinafter referred to as “rear full data”) collected at a time after the reference full data. Extraction of the difference data related to the backward full data can be realized by applying a procedure similar to the procedure applied to the existing system for saving (backup) data.

  The forward full data is not limited to data collected from the data collection target immediately before the reference full data. Further, the rear full data is not limited to data collected from the data collection target immediately after the reference full data. In the above embodiment, the data storage system 1 stores only the latest version of the full data, but stores the full data for a plurality of versions, and uses the plurality of full data as reference full data. Difference data before and after the reference full data may be saved.

(B-3) In the above embodiment, the operation of searching for arbitrary data of an arbitrary version by the processing of the flowcharts shown in FIGS. 11 to 13 described above has been described. For example, the above-described data search of FIGS. 11 to 13 may be performed for all data in the full data table 152.

  In addition, for example, the data corresponding to the specified version may be restored by sequentially performing processing corresponding to the additional data, the deletion data, and the update data of the difference data management table 153 on the full data table 152. For example, if there is additional data, the corresponding data is deleted. Conversely, if there is deleted data, the corresponding data is added. If there is updated data, the data is reversed. The reverse update that returns the data update can be performed for all the difference data for each version, and can be traced back to the specified version. Since the difference data of each version can be recognized by checking the version number (version_count) entered in any of the add column, del column, or update column, for example, the current version_count is 5, and restoration is specified. If the version is 2, the difference data of the version number 4, the difference data of 3, the difference data of 2, and the difference data of 2, if all the data of the specified version (2) is applied by applying the above-mentioned processing in order Can be restored.

It is a block diagram which shows the functional structure of the data storage system which concerns on embodiment. It is explanatory drawing shown about the content preserve | saved in the version number registration part among the databases which concern on embodiment. It is explanatory drawing shown about the content preserve | saved in a full data table among the databases which concern on embodiment. It is explanatory drawing shown about the content preserve | saved in a difference data management table among the databases which concern on embodiment. It is the flowchart shown about the operation | movement which produces | generates and preserve | saves difference data in the data storage system which concerns on embodiment which concerns on embodiment. It is explanatory drawing shown about the operation | movement which produces | generates and preserve | saves deletion and update data among difference data in the data storage system which concerns on embodiment. It is explanatory drawing shown about the operation | movement which produces | generates and preserve | saves additional data among difference data in the data storage system which concerns on embodiment. It is explanatory drawing shown in detail about the operation | movement which produces | generates and preserve | saves deletion data among difference data in the data preservation | save system which concerns on embodiment. It is explanatory drawing shown in detail about the operation | movement which produces | generates and preserve | saves update data among difference data in the data storage system which concerns on embodiment. It is explanatory drawing shown in detail about the operation | movement which produces | generates and preserve | saves additional data among difference data in the data preservation | save system which concerns on embodiment. It is the flowchart (1) shown about the operation | movement which searches the data of the past version in the data storage system which concerns on embodiment. It is the flowchart (2) shown about the operation | movement which searches the data of the past version in the data storage system which concerns on embodiment. It is the flowchart (3) shown about the operation | movement which searches the data of the past version in the data storage system which concerns on embodiment. It is the flowchart shown about the operation | movement which deletes the data older than the designated version in the data storage system which concerns on embodiment. It is explanatory drawing which showed the specific example of the data stored in the full data table which concerns on embodiment. It is explanatory drawing which showed the specific example of the data stored in the difference data management table which concerns on embodiment.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Data storage system, 11 ... Data collection part, 12 ... Temporary storage part, 13 ... Current data storage part, 14 ... Difference extraction part, 15 ... Database, 16 ... Past version data search part, 17 ... Previous data deletion part, 151: Version number registration unit, 152 ... Full data table, 153 ... Difference data management table, 2, 2-1 to 2-3 ... Data collection target, 3 ... Client.

Claims (7)

In a data storage system that acquires and stores data to be stored at multiple different times,
Reference whole data storage means for storing the whole data of the reference storage target data which is the storage target data acquired at an arbitrary time;
Forward whole data holding means for holding the whole data of the forward saving target data which is the saving target data acquired at a time before the reference saving target data;
Difference data generation means for generating difference data between the whole data stored in the reference whole data storage means and the whole data held in the front whole data holding means;
A data storage system comprising: difference data storage means for storing the difference data generated by the difference data generation means.   The difference data generation means is updated with at least deleted data in the whole data held by the front whole data holding means with respect to the whole data saved by the reference whole data saving means. 2. The data storage system according to claim 1, wherein difference data is generated based on the extracted data and extracted data.   The data storage system according to claim 1 or 2, wherein the reference storage target data is the latest acquired storage target data.   The data storage system according to any one of claims 1 to 3, wherein the forward storage target data is storage target data acquired immediately before the reference storage target data. A computer installed in a data storage system that acquires and stores data to be stored at multiple different times.
Reference whole data storage means for storing the whole data of the reference storage target data which is the storage target data acquired at an arbitrary time;
Forward whole data holding means for holding the whole data of the forward saving target data which is the saving target data acquired at a time before the reference saving target data;
Difference data generation means for generating difference data between the whole data stored in the reference whole data storage means and the whole data held in the front whole data holding means;
A data storage program that functions as a differential data storage unit that stores differential data generated by the differential data generation unit. In a data storage method in a data storage system that acquires and stores data to be stored at a plurality of different times,
Reference whole data storage means, front whole data holding means, difference data generation means, difference data storage means,
The reference entire data storage means stores the entire data of the reference storage target data that is the storage target data acquired at an arbitrary time,
The front whole data holding means holds the whole data of the forward storage target data which is the storage target data acquired at a time before the reference storage target data,
The difference data generation means generates difference data between the whole data stored by the reference whole data storage means and the whole data held by the front whole data holding means,
The difference data storage unit stores the difference data generated by the difference data generation unit. The data storage system according to any one of claims 1 to 4, wherein data relating to monitoring of the node is collected from one or a plurality of nodes, and the data collected from the node is collected in the monitoring device that monitors the node. The monitoring apparatus characterized by storing using.

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