JP2013003716A - Data storage device, control method of data storage device, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To properly restart data optimization processing even if data optimization processing is suspended under situations where calculation resources can be not fully used.SOLUTION: In a data storage device, even if data optimization processing is suspended, a data difference quantity for data updates from the time of suspension is used to determine proper restarting of the optimization processing, and thus the data storage device can efficiently perform optimization processing and is excellent in response performance.

Description

  The present invention relates to a data storage device that performs data optimization processing, a control method thereof, and a program.

  With the increase in flash memory capacity in recent years, even resource-saving devices with limited computing resources, such as digital cameras, photo frames, and inkjet multifunction devices, have a storage capacity that can store tens of thousands to hundreds of thousands of data. It is like that. In addition, various attribute values such as personal names and place names can be assigned. Using these attribute values, there is a demand for the convenience of performing a large amount of data search at high speed even in resource-saving devices. It is growing.

  In the case of photo data, attribute values such as date, shooting parameters, and GPS (Global Positioning System) coordinates as position information are given at the time of shooting, and attribute values such as a favorite degree and print designation are given at the time of reproduction. A typical framework for storing these attribute values is Exif (Exchangeable image file format). It is useful to use these attribute values when searching for data desired by the user. However, when there are a large amount of data and attribute values, performing a search process by performing a full scan on each data results in an enormous amount of calculation for collation and a delay in response time.

  Therefore, in order to perform a search at a high speed, a general technique is that an index containing index information is built in advance and the response time is shortened by using the index during the search. However, in order to always obtain a correct search result, when search target data is added / updated, it is necessary to add / update the index in synchronization. If such data update occurs frequently and the local update of the index continues, fragmentation occurs in the index. That is, an unbalanced structure unsuitable for search processing in which unused space increases and the data storage position is biased is born. When a search is performed in this situation, the amount of data access increases compared to the case where an index with little fragmentation is used, and the calculation performance of the entire apparatus is reduced. In general, in order to solve this problem, an intermediate layer such as a cache mechanism is provided in the RAM or the main storage unit to suppress the read / write frequency. However, in a resource-saving device, the cache mechanism has a small capacity due to the limitation of computing resources, and an index that has a large amount of fragmentation increases the degree of influence that degrades the calculation performance of the entire apparatus.

  For example, in a digital camera or the like, a personal name may be registered afterwards with reference to a personal name dictionary or the like for a photograph taken. When post-registration of such attribute values is performed, index fragmentation is induced in order to rearrange a part of the constructed index. As a result, the cache hit rate at the time of data access decreases, and data reading from the database file tends to occur frequently. Therefore, it is necessary to perform an optimization process for eliminating index fragmentation at an appropriate timing.

  Conventionally, as disclosed in Patent Document 1, for example, image data is optimized when the transmission rate of the image data falls below a predetermined value. Further, as disclosed in Patent Document 2, there is an apparatus that automatically executes optimization in consideration of the device mounting state, the power supply state, and the fragmentation rate.

JP 2002-84499 A JP 2005-242717 A

Further, when the data optimization process is interrupted, it is desirable to appropriately restore the process and restart it. When resuming after the optimization process is interrupted, it is possible to determine whether to continue using the optimization process result that has been optimized halfway or to start a new optimization process, and perform the optimization process appropriately. I need it.
The present invention has been made in view of the above problems, and improves response performance by appropriately performing optimization processing even when the optimization processing is interrupted when a situation in which computational resources cannot be secured is detected. The purpose is to improve convenience.

  The data storage device according to the present invention has the following configuration. That is, an optimization execution unit that performs optimization processing of data fragmentation, a detection unit that detects that the optimization process is interrupted, and an optimization process that is detected by the detection unit that is interrupted Determining means for determining whether the data can be continuously resumed based on the amount of data updated from the interruption. The optimization execution unit restarts the data optimization process when the determination unit determines that the optimization process can be restarted.

  According to the present invention, even if the data optimization process is interrupted, the optimization process is restarted appropriately, so that the fragmentation of data can be eliminated to improve the response performance, and the convenience for the user is enhanced.

It is a figure which shows the structure of the principal part which concerns on control of the data storage device by this embodiment. It is a figure which shows simply the example in which the effect of this embodiment appears It is a figure which shows the flash memory card used by this embodiment, the typical example of the attribute value of Exif as a data example, and an example which constructed | assembled the index with B-Tree. It is a functional block diagram of the data storage device by this embodiment It is a figure which shows the example of the search object data used by this embodiment, and the example of the index of search object data. It is a figure which shows the example of the SQL sentence which described the search instruction | indication used by this embodiment, and a screen when performing a search process It is a flowchart which shows the flow of the power-on process of 1st Embodiment. It is a flowchart which shows the flow of the search process of 1st Embodiment. It is a flowchart which shows the flow which the index optimization process of 1st Embodiment starts. It is a flowchart which shows the detailed flow of the index optimization process of 1st Embodiment.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments to which the invention is applied will be described in detail with reference to the accompanying drawings.

First Embodiment Basic Operation FIG. 1 is a configuration diagram showing an apparatus to which this embodiment is applied. A data storage device 1000 represents the entire database control device. A microprocessor CPU (Central Processing Unit) 1001 performs operations for information processing, logical determination, and the like. Each component connected to these buses is controlled via the system bus 1010. A read-only fixed memory ROM (Read Only Memory) 1002 stores control program codes such as processing programs executed in the present embodiment. A writable RAM (Random Access Memory) 1003 is used for temporary storage of various data from each component. An instruction from the user is input to the input unit 1004. The power supply unit 1005 supplies necessary power to the data storage device 1000, and responds to power supply and charging from the outside as necessary. In a display unit 1009 such as a liquid crystal panel, display of image information on the display unit is controlled by a display controller 1006. The external storage unit 1007 stores various data and image information. As a storage medium for storing these data, a memory card, HDD, DVD-RAM, or the like can be used. The communication unit 1008 can be connected to other devices.

  The data storage device 1000 including the above components operates in response to various inputs from the input unit 1004 and various inputs via the network supplied from the communication unit 1008. That is, when an input from the input unit 1004 and an input from the communication unit 1008 are supplied, an interrupt signal is first sent to the CPU 1001. Then, the CPU 1001 reads out various control signals stored in the ROM 1002, RAM 1003, and external storage unit 1007, and various controls are performed according to these control signals.

  The present embodiment can also be achieved by supplying a storage medium storing a program according to the present embodiment to a system or apparatus, and the system or apparatus reading and executing the program code stored in the storage medium.

  FIG. 2 shows an index example of the B-Tree structure in which the present embodiment shows an effective situation. For example, when an attribute value is assigned to the index in the initial state shown in FIG. 2A so as to be updated from the personal name “none” to the personal name “Taro”, the index is updated as shown in FIG. An empty area is created in the part where the previous attribute value was stored. Search target index data is dispersed. As a result, the amount of access data increases, and the response performance at the time of search and update deteriorates. Therefore, index optimization processing is performed at an appropriate timing, and unnecessary empty areas are arranged as shown in FIG. By organizing the free space, the amount of access data can be reduced and the response performance can be improved.

FIG. 3A is a diagram showing an internal configuration of a memory card for a digital camera as an example of the external storage unit 1007. Various types of data such as photographs and videos are stored in the memory card 3000 in conformity with DCF (Design rule for Camera File System) (3001). In addition, attribute values, which are additional information for explaining the contents of the data, are given to the photo and video data. In the case of photo data, Exif (Exchangeable image file format), which is a framework for storing dates, shooting parameters, GPS coordinates, and the like, is a typical example (3002).
FIG. 3B shows an example of attribute values of Exif, in which date, GPS coordinates, place name, photographing device manufacturer, photographing device model name, personal name, and the like are stored. Further, in order to perform the search processing at high speed, various indexes (3004 to 3007) storing index information are built in the index storage area 3003 in advance, and the response time can be reduced by using the built indexes at the time of the search. The method of shortening is common. The index has a logical structure such as B-Tree or hash, and a high-speed search is possible by associating a search key with data. The index storage area 3003 holds a date index 3004, a GPS coordinate index 3005, a place name index 3006, and a person name index 3007. Each index 3004 to 3007 is made permanent in the index storage area 3003 in the form of a database file or the like.
FIG. 3C is a diagram when the place name index 3006 has a B-Tree structure. B-Tree is a data structure having a hierarchical structure and has a feature that data can be easily inserted, searched, and deleted. An index record 3008 represents an index record from a place name to a data file name.

FIG. 4A shows the configuration of the RAM 1003. It is mainly composed of a file cache 4001 and a database cache 4002. The file cache 4001 is arranged to improve the response speed to requests from the database engine 4004 and the search application 4008 by passing access request data for the external storage unit 1007 via the RAM 1003.
FIG. 4B is a functional block diagram according to the present embodiment. The device state change detection unit 4003 monitors the power supply state, resource state, communication state, acceleration sensor, and the like, and determines the operation of the device according to the state change. A search application 4008 that executes search processing of the data storage device includes a data registration processing unit 4009 and a data search processing unit 4010. The database engine 4004 is used to perform search processing at high speed. The search application 4008 performs data registration processing and data search processing using the database engine 4004.

A data table 5001 in FIG. 5A is an example of a search database according to the present embodiment. It is assumed that RowID is assigned as a key for uniquely identifying each data and stored in a database file or the like in a table format. The RowID is a numerical value that is uniquely assigned and assigned so as not to be duplicated in the database or table, and is used in a general database engine.
FIG. 5B shows an example of an index stored in the index storage area 3003 according to this embodiment. By generating the index of the Exif data 3002 assigned to each data in advance by the index registration processing unit 4005, it is possible to quickly find data that matches the search condition and execute the search process at high speed. For example, the date index 3004 holds a data map in which a date and RowID are linked, and the person name index 3007 holds a data map in which a person name and RowID are linked. It is possible to uniquely specify data from the associated RowID and present the search result.

  The data storage device is not limited to the data search function but may be equipped with various functions such as a data transfer function, a data registration function, and an imaging function. Therefore, the data storage device detects the state of the device and operates by selecting an appropriate function. FIG. 7 shows an example of a flowchart showing an operation after power-on of the data storage device 1000. When the power is turned on, initialization processing after the power is turned on is performed in step S7001. In step S7002, an event such as a change in the state of the device or an input from the user is waited for, and if detected, the process proceeds to the next step. A change in the state of the device may be a change in the power supply state or a communication state. In step S7003, it is determined what the detected event is, and the event is passed to step S7004. Appropriate processing is performed according to the event determined in step S7004, and the result is displayed on the display unit 1009 in step S7005. Typical examples of events include a data search processing start command and a data registration processing start command. In addition, replacement of power switch, change in power supply state, change in connection state with other devices, change in external storage state, change in acceleration, change in radio wave intensity, change in communication state, change in device resource state, instructions from outside, A time change etc. are also mentioned.

  Here, details of the data search process using the index, the data registration process, the process of fragmentation, and the index optimization process for eliminating fragmentation will be described.

  First, the data search process will be described. For example, when the data search process is instructed by the user, the data search process flow shown in FIG. 8 is called to activate the data search processing unit 4010. The data search processing unit 4010 executes a search process according to the search instruction received from the search condition input unit 4011 and performs a process of returning the search process result to the search result display control unit 4012. In step S8001, a search condition input from the search condition input unit 4011 is received. Subsequently, in step S8002, based on the search condition, the data search processing unit 4010 is activated to execute the search process. The data search processing unit 4010 calls the index search processing unit 4006 included in the database engine 4004 according to the search condition, and acquires data that matches the search condition. Subsequently, the search result display control unit 4012 presents the result acquired in step S8003 to the user.

FIG. 6B shows an example of a user interface that displays the search result of the data search process. An area 6001 is a search condition display area. A box 6002 is a drop-down box for selecting a search condition designated by the user. An area 6003 is a search result display area that displays a list of search results as thumbnails in the area based on the search condition. An area 6004 is a search result information display area that presents the number of pages of search results.
FIG. 6A shows an example of an SQL (Structured Query Language) statement expressing a search instruction given by the user to the search condition input unit 4011. Generated by the search condition input unit 4011 or the like according to the search conditions specified by the user. The generated SQL sentence is interpreted and executed by the index search processing unit 4006, and data search processing is performed.

  Next, the data registration function will be described. The data registration processing unit 4009 is executed when an event such as imaging or external data replication occurs. The data registration processing unit 4009 is called and executed from step S7004, and perpetuates data that has received a request for registration, update, or deletion in the data storage unit 3001. Further, the data registration processing unit 4009 calls the index registration processing unit 4005 to update each necessary index 3004 to 3007 and store it in the index storage area 3003 in order to speed up the search process. Thus, in step S7004, processing corresponding to various events is performed, and index fragmentation occurs as a result of the called data registration processing unit 4009 and index registration processing unit 4005. In general, an index file for making an index permanent is managed in units of a certain amount of blocks. The logical structure is represented by a hash, AVL Tree, B-Tree, a bitmap, and the like.

  For example, FIG. 2 shows a personal name index 3007 expressed in a B-Tree structure. In general, the B-Tree structure is roughly divided into three elements: a root node, an intermediate node, and a leaf node. By searching from the root node toward the leaf node and evaluating the data stored in each node, data corresponding to the search condition can be searched without performing a full scan.

  However, in the index registration processing performed by the data registration processing unit 4009, it is necessary to pay attention to fragmentation inside the index. In order to obtain a correct search result, it is necessary to update the index in the same manner every time data to be searched is updated. In the index shown in FIG. 2A, the index is constructed in a state where the personal name “Taro” is not assigned. At this time, when a personal name recognition process or the like is performed and the attribute value “Taro” is given to some of the data having the attribute value “None”, the B-Tree structure is updated as shown in FIG. The The attribute value “Taro” tree is constructed. On the other hand, since the index is updated in response to a high speed, the free area generated in the attribute value “none” portion is finished without being filled. When search processing or registration processing is performed in a state in which such fragmentation occurs, the data to be processed is widely distributed, so that the necessary data access amount increases and the cache is depleted. As a result, the number of access requests to the external storage unit 1007 increases and the processing end is delayed. Such fragmentation of the logical structure occurs not only in the B-Tree but also in a hash, an AVL Tree, a bitmap, and the like. Similarly, when the index file itself is repeatedly updated, fragmentation occurs due to a decrease in the reuse rate of the free area in the unit block. In particular, when flash memory with low rewrite speed is used as an external storage unit, designs that give priority to new appending over reuse of existing areas are often performed, and updates with a low reuse rate are accumulated and fragmentation occurs. Becomes prominent. An index file with much fragmentation requires a large amount of reading, which causes the cache memory of the device to be depleted. When the cache memory is depleted, the frequency of access to the external storage unit increases and the response performance deteriorates.

  Therefore, in order to eliminate fragmentation, it is necessary to periodically perform data optimization processing, that is, index optimization processing. However, since the restructuring process of the structure requires an overview of the entire data, the cost increases according to the number of cases, and the performance of other functions such as photography is deteriorated in an environment where the computational resources such as a digital camera are limited There is. In addition, when a flash memory is used as the external storage unit, small-capacity reading and writing processes such as index-target attribute values are slow. For this reason, the index optimization process is a further processing load. Therefore, in a digital camera or the like, index search must be allowed to continue and search processing must be continued.

  Therefore, in this embodiment, data optimization means is used to perform index optimization processing at an appropriate timing. The device state change detection unit 4003 is used to monitor the state of the device, and a time when there is no influence on other functions such as photography is detected and the index optimization unit 4007 is called. The status monitoring elements are: power supply status, remaining battery level, connection status with other devices, data status, external storage status, acceleration sensor value, radio wave intensity, communication status, device resource status, external Instruction, time, and the like. An index optimization process is performed based on at least one of the state detection results.

  FIG. 9 shows an example of a processing flow in which the index optimization process is performed by monitoring the state of charge and the number of index updates. The index optimization process is performed when charging is started, and the power is turned off when the charging is completed. This is because a digital camera or the like is not likely to be used until charging is completed while the charging process is being performed. In step S9001, the start of the charging process is detected. If detected, it is checked in step S9002 if the number of index updates is greater than or equal to a predetermined value, and it is determined whether index optimization processing is necessary. This is because if the number of index updates is large, there is a high possibility that a large amount of index fragmentation has occurred. If index optimization processing is necessary, the index optimization unit 4007 is activated in step S9003, and if not, nothing is done. Finally, in step S9004, device termination processing is performed to turn off the device. Note that, as a criterion for determining whether or not the index optimization process is necessary, not only the number of updates but also the operating time of the device, the number of activations, and the like may be used. When the index update frequency is almost constant, the operating time is used. When the correlation between the number of activations and the number of updates is high, the cost of counting the number of updates can be omitted by using the number of activations as a reference. .

  Another example in which the optimization process is performed will be given. It may be performed when connected to another device for a long time. It may be performed when the data usage frequency is low. You may perform when the state of the external storage unit is low. It may be performed when it can be determined that the acceleration sensor value is little changed and stable. It may be performed when the radio wave intensity is strong and stable. You may perform when communication is connected for a long time, or when there is little communication volume. It may be performed when the resource status of the device is monitored and the load is low or not used. You may go in the middle of the night when the user is sleeping. Of course, it may be when the user explicitly gives an instruction.

  By the way, in a small viewer, digital camera or the like, it is necessary to interrupt the index optimization process in order to avoid affecting the performance of the main function in a situation where charging is interrupted and taken out. On the other hand, abandoning a suspended index is not desirable in terms of the efficiency of index optimization processing. Therefore, it is necessary to efficiently enable data optimization suspension and data optimization restart after interruption appropriately.

  FIG. 4C shows an example of a detailed functional block diagram of the index optimization unit 4007 that suspends and resumes the index optimization process. An example of the operation will be described in detail with reference to the index optimization processing flowchart of FIG.

  First, in step S10001, the index optimization schedule generation unit 4013 is executed. Here, index optimization scheduling according to the device state is performed by referring to and analyzing the power supply state and the resource state. For example, if it can be determined that the battery level of the device is low and the remaining charge time is long, it may be determined that the frequency of use of the device will be low and scheduling a large-scale index optimization process. Subsequently, the index optimization starting unit 4014 starts or restarts the index optimization process corresponding to the schedule.

  In step S10002, it is detected whether the index optimization process has been interrupted before. If an interruption is detected, the process proceeds to step S10003 to attempt to continue the optimization process and restart. If not, index creation is newly started from the beginning in step S10006.

  In step S10003, it is extracted how much the search target data has a difference due to the data update compared to when the data is interrupted. In step S10004, the index optimization restart unit 4015 is called to restart the index optimization process. Based on the extracted difference amount, it is determined whether or not the index optimization process can be resumed. As a reference example of the difference amount, a change in index file size, the number of updates, an elapsed time since the interruption, and the like are used. Whether or not the optimization process can be resumed is determined by the number of data updates / deletions.

  When the number of data updates / deletions is small, update / deletion of data corresponding to the index optimized portion is detected, the corresponding index is updated, and the subsequent optimization is resumed. When most of the data is updated or deleted, the optimization is executed from the beginning without using the index data that has been optimized by the time of interruption.

  That is, if there is a data difference in the optimized part before the interruption, the difference is applied to the optimized part if the difference amount is within an allowable range.

  If the result of step S10004 is true, index creation is resumed in step S10005. If false, the process proceeds to step S10006 to create a new index. In response to the flow from step S10005 or step S10006, index creation is performed in the loop from step S10007 to step S10011.

  However, for each loop, in step S10007 and step S10008, the device state such as the charging state is monitored to determine whether or not the index optimization process should be interrupted. If it is determined that the index optimization process is to be interrupted due to charging interruption or the like, the index optimization process is interrupted in step S10012. As an interruption method, for example, a new index is created while leaving the old index before the end of optimization, and the new and old indexes are replaced after the new index construction is completed.

  FIG. 2C shows an example in which the index fragmentation shown in FIG. 2B is eliminated by the index optimization process. The free space has been filled up by reconstruction, and the total number of nodes has decreased. It should be noted that not only B-Tree but also optimization processing such as organizing free areas that are not reused is performed on indexes having other logical structures such as AVL Tree, and index files themselves. To eliminate fragmentation. This reduces the amount of data required for search and registration, and improves response time.

  With the above processing, the index optimization processing can be interrupted and restarted at an arbitrary timing according to the state of the device. Since the old index is not overwritten during the creation of a new index, it is possible to recover from a suspended state even in the event of a sudden power interruption or communication interruption. This makes it possible to optimize the index by efficiently using the computing resources of the device. As a result, the response speed during data retrieval is improved.

  This embodiment is based on an environment where the update speed is low, such as a flash memory, but it is effective in improving the response time in any environment such as a RAM drive, a hard disk drive, or a flash memory with improved speed. As an application example of the present embodiment, it is also effective in efficiently using computing resources that index optimization processing is distributed or commissioned with other devices when connected to other devices.

  Further, the present embodiment is not limited to index optimization processing, and can be applied to various use cases. For example, the present invention can be applied to file system optimization processing. In this case, the data optimization process is started, interrupted, and restarted at an appropriate timing based on the device state detection result. As a result, free space in the external storage unit 1007 and fragmentation of registered data are eliminated without degrading the performance of the main function. This has the effect of improving the data scanning time and writing time delay.

(Second Embodiment)
Next, as a second embodiment of the present invention, a thumbnail image construction process, that is, a method for achieving both improved search response speed and browsing image quality by creating a reduced image will be described in detail. This embodiment has the same configuration as that of the first embodiment. In the present embodiment, a reduced image (thumbnail) for browsing is created in image search or the like. By doing so, an object is to achieve both the image quality at the time of data browsing and the response performance at the time of retrieval.

  An imaging device such as a digital camera can record a high-resolution image exceeding 10 million pixels. On the other hand, in order to view such high-quality images, a calculation amount proportional to the amount of data is required, and a calculation load increases in use cases such as continuous browsing of a large amount of data. For this reason, a reduced image is stored in advance in the Exif area, and high-speed image switching is enabled by preferentially displaying this. However, the display resolution is improved by the advancement of the display device, and there are cases where sufficient image quality cannot be ensured only by displaying the reduced image of the conventional Exif standard.

  Therefore, in this embodiment, by performing device state detection, a reduced image is constructed at an intermediate resolution between the original image and the Exif reduced image at an appropriate timing, and the image quality and response are preferentially viewed during browsing. Balance performance.

  This embodiment is also applicable in the example of the flowchart shown in FIG. When detecting a change in the device state such as charging disconnection and performing the interruption process in step S10012, the progress of creating the intermediate resolution reduced image is stored. When the creation of the next intermediate resolution reduced image is started, the creation of the intermediate resolution reduced image is resumed in step S10005 according to the progress. In this way, the intermediate resolution reduced image can be smoothly created by effectively using the state at the time of interruption, and both the response performance at the time of retrieval and the browsing image quality can be achieved.

  The present invention can also be applied to digest image creation processing of moving image data. Similar to the present embodiment, the creation according to the state of the device is effective in improving the convenience during data retrieval without degrading the performance of the main function.

(Other examples)
The present invention can also be realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

File cache 4001
Database cache 4002
Device state change detection unit 4003
Database engine 4004
Index registration processing unit 4005
Index search processing unit 4006
Index optimization unit 4007
Search application 4008
Data registration processing unit 4009
Data search processing unit 4010
Search condition input part 4011
Search result display control unit 4012
Index optimization schedule generation unit 4013
Index optimization start unit 4014
Index optimization restart unit 4015

Claims (10)

In a data storage device,
An optimization execution means for optimizing data fragmentation;
Detecting means for detecting that the optimization process is interrupted;
A determination unit that is detected by the detection unit, and that determines whether or not the suspended optimization process can be resumed continuously is determined based on the amount of data updated from the interruption, and
The data storage device, wherein the optimization execution unit restarts the data optimization process when the determination unit determines that the optimization process can be restarted. Further comprising detecting means for detecting the state of the data storage device;
The data storage device according to claim 1, wherein the data optimization execution unit interrupts data optimization when the detection unit detects a predetermined state of the data storage device.   3. The data storage device according to claim 2, wherein the data optimization execution unit plans and executes data optimization based on the state of the data storage device detected by the detection unit.   The detection means detects the power supply state, the remaining amount of electricity, the connection state with other devices, the data state, the state of the external storage unit, the acceleration sensor value, the radio wave intensity, the communication state, the resource state of the device, from the outside The data storage device according to claim 3, wherein at least one of the instruction and the time is selected.   The data optimization execution unit updates the optimized part by applying the updated data to the part subjected to the optimization process before the interruption when the amount of the updated data is small. The data storage device according to claim 1.   The data storage device according to claim 1, wherein the data to be optimized is index data.   7. The data according to claim 6, wherein the data optimization execution means performs optimization while leaving the old index before the optimization is completed, and replaces the new index and the old index that are optimized after the optimization is completed. Storage device.   The data storage device according to claim 1, wherein the data to be optimized is thumbnail image data. In a method for controlling a data storage device,
An optimization execution step for performing optimization processing of data fragmentation;
A detection step of detecting that the optimization process is interrupted;
A determination step that is detected in the detection step, and that is determined based on the amount of data updated from the interruption whether the optimization process that has been interrupted can be resumed continuously,
The method for controlling a data storage device, wherein the optimization execution step restarts the data optimization processing when it is determined in the determination step that the optimization processing can be restarted. A program for causing a computer to execute a control method for a data storage device,
Optimization execution procedure to optimize data fragmentation,
A detection procedure for detecting that the optimization process is interrupted;
A determination procedure that is determined by the amount of data updated from the interruption whether the optimization process that has been interrupted detected in the detection procedure can be resumed continuously,
The optimization execution procedure causes a computer to restart the data optimization processing when it is determined by the determination procedure that the optimization processing can be restarted.

Images