Tabular data retrieval support program, tabular data retrieval support apparatus, tabular data retrieval support method, and recording medium

Abstract

To provide a tabular data retrieval support program configured to record tabular data so as to be easily retrieved.SOLUTION: A tabular data retrieval support program includes a feature information analysis step and a retrieval data recording step. The feature information analysis step includes analyzing tabular data and analyzing feature information. The retrieval data recording step includes recording retrieval data obtained by adding the feature information to the tabular data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a tabular data search support program, a tabular data search support device, a tabular data search support method, and a recording medium. [Background technology]

[0002] In the operation of a computer system, logs output from each computer are recorded, and when a system failure occurs, the log system is analyzed to estimate the cause of the failure, etc. In this regard, Patent Document 1 discloses a log analysis device that receives and analyzes logs from multiple computers that generate multiple logs, and corrects the timestamp recorded in each log for the multiple logs output from the multiple computers using a date and time correction log and consistency rules between the logs. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2008-269084 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when analyzing logs, if the log data is in a table format, searching the data is difficult.

[0005] Therefore, an object of the present disclosure is to provide a tabular data search support program, a tabular data search support device, a tabular data search support method, and a recording medium that can record tabular data in an easily searchable manner. [Means for solving the problem]

[0006] In order to achieve the above object, the tabular data search support program of the present disclosure comprises: It includes a procedure for analyzing characteristic information and a procedure for recording data for searching, the step of analyzing characteristic information analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; The tabular data search support program causes a computer to execute each of the above procedures.

[0007] The tabular data search support device of the present disclosure comprises: a feature information analysis unit and a search data recording unit; the characteristic information analysis unit analyzes the tabular data to analyze the characteristic information; The search data recording unit records search data in which the feature information is added to the tabular data.

[0008] The tabular data search support method of the present disclosure includes: A feature information analysis step and a search data recording step are included, the characteristic information analyzing step analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; The tabular data search support method is a method in which each of the steps is executed by a computer.

[0009] The recording medium of the present disclosure includes: It includes a procedure for analyzing characteristic information and a procedure for recording data for searching, the step of analyzing characteristic information analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; A computer-readable recording medium stores a tabular data search support program for causing a computer to execute each of the above procedures. [Effects of the Invention]

[0010] According to the present disclosure, tabular data can be recorded in an easily searchable manner. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing a configuration of an example of a tabular data search support device according to the present disclosure. [Figure 2] FIG. 2 is a block diagram showing an example of a hardware configuration of the tabular data search support device of the present disclosure. [Figure 3] FIG. 3 is a flowchart showing an example of processing in the tabular data search support device of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiments. In the following drawings, the same parts are denoted by the same reference numerals. Furthermore, the descriptions of the embodiments can be mutually incorporated unless otherwise specified, and the configurations of the embodiments can be combined unless otherwise specified. It can be obtained.

[0013] [Embodiment 1] The tabular data search support program of the present disclosure is a program for causing a computer to execute a characteristic information analysis procedure and a search data recording procedure. The tabular data search support program of the present disclosure can also be said to be a program for causing a computer to function as the characteristic information analysis procedure and the search data recording procedure. Furthermore, the tabular data search support program of the present disclosure can also be said to be a program for causing a computer to execute, for example, each step of a tabular data search support method described below.

[0014] the step of analyzing characteristic information analyzes the tabular data to analyze the characteristic information; The search data recording step records search data in which the feature information is added to the tabular data.

[0015] For example, the "procedure" in each of the steps can be read as a "process." The tabular data search support program of the present disclosure may be recorded on a computer-readable recording medium. The recording medium may be a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (e.g., solid state drive (SSD), USB flash memory, SD / SDHC card, etc.), optical disk (e.g., CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), and floppy disk (FD). The tabular data search support program of the present disclosure (also referred to as a programming product or program product) may be distributed from an external computer. The "distribution" may be, for example, via a communication network or a device connected via a wire. The tabular data search support program of the present disclosure may be installed and executed on the device to which it is distributed, or may be executed without being installed. An information processing device capable of executing the tabular data search support program of the present disclosure can be referred to as, for example, the tabular data search support device of the present disclosure.

[0016] Next, the configuration of an example of a tabular data search support device according to the present disclosure will be described with reference to FIG. 1. FIG. 1 is a block diagram showing the configuration of an example of a tabular data search support device 10 according to this embodiment (hereinafter also referred to as "the device"). As shown in FIG. 1, the device 10 includes a feature information analysis unit 11 and a search data recording unit 12. The device 10 may also include, for example, an input unit, an output unit, a display unit, and / or a storage unit, although these are not shown. The feature information analysis unit 11 and the search data recording unit 12 can respectively execute, for example, a feature information analysis procedure and a search data recording procedure in the tabular data search support program according to the present disclosure.

[0017] The device 10 may be, for example, a single device including the above-described units, or a device in which the units can be connected via a communication network. The device 10 can also be connected to an external device (described later) via the communication network. The communication network is not particularly limited and any known network can be used, for example, a wired or wireless network. Examples of the communication network include the Internet, the World Wide Web (WWW), a telephone line, a Local Area Network (LAN), a Storage Area Network (SAN), a Delay Tolerant Networking (DTN), a Low Power Wide Area Network (LPWA), and a Local 5G (L5G). Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), Local 5G, and LPWA. Examples of the wireless communication include direct communication between devices (Ad Hoc communication), infrastructure communication, and indirect communication via an access point. The device 10 may be incorporated into a server as a system. Furthermore, the present device 10 may be, for example, a personal computer (PC, for example, desktop or notebook type) on which the program of the present disclosure is installed, a smartphone, a tablet terminal, etc. The present device 10 may be in the form of cloud computing or edge computing, for example, in which at least one of the above-mentioned units is located on a server and the other units are located on a terminal.

[0018] 2 shows a block diagram of the hardware configuration of the device 10. The device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, a memory 102, a bus 103, a storage device 104, an input device 105, an output device 106, and a communication device 107. The components of the device 10 are connected to each other via the bus 103 and their respective interfaces (I / F).

[0019] The central processing unit 101 operates in cooperation with other components via a controller (such as a system controller or an I / O controller) and is responsible for overall control of the device 10. In the device 10, the central processing unit 101 executes, for example, the program of the present disclosure and other programs, and also reads and writes various types of information. Specifically, for example, the central processing unit 101 functions as a feature information analysis unit 11 and a search data recording unit 12. The device 10 may include, as a computing device, other computing devices such as a CPU, a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these.

[0020] The bus 103 can also be connected to, for example, external devices. Examples of the external devices include a user terminal, an external storage device (such as an external database), a printer, an external input device, an external display device, and an external imaging device. The device 10 can be connected to an external network (the communication line network) by, for example, a communication device 107 connected to the bus 103, and can also be connected to other devices via the external network.

[0021] The memory 102 may be, for example, a main memory (primary storage device). When the central processing unit 101 performs processing, the memory 102 reads various operating programs, such as the program of the present disclosure, stored in the storage device 104 (described later), and the central processing unit 101 receives data from the memory 102 and executes the programs. The main memory may be, for example, a RAM (random access memory). The memory 102 may also be, for example, a ROM (read only memory).

[0022] The storage device 104 is also referred to as an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 104 stores an operating program including the program of the present disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive that reads and writes data from and to the recording medium. The recording medium is not particularly limited and may be, for example, an internal or external type, such as a hard disk (HD), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, or memory card. The storage device 104 may be, for example, a hard disk drive (HDD) or a solid state drive (SSD) in which the recording medium and drive are integrated.

[0023] In the present device 10, the memory 102 and the storage device 104 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 10, and information used by the present device 10 when executing processing. In this case, the memory 102 and the storage device 104 may store, for example, the above-mentioned information on users of the present device. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 102 and the storage device 104, or may be stored in a distributed manner across multiple terminals using blockchain technology or the like. Furthermore, when the present device 10 includes the storage unit, for example, the memory 102 and the storage device 104 function as the storage unit.

[0024] The device 10 further includes, for example, an input device 105 and an output device 106. Examples of the input device 105 include pointing devices such as a touch panel, track pad, and mouse; a keyboard; imaging means such as a camera and scanner; card readers such as an IC card reader and a magnetic card reader; and audio input means such as a microphone. Examples of the output device 106 include display devices such as an LED display and a liquid crystal display; audio output devices such as a speaker; a printer; and the like. In the first embodiment, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may be configured as an integrated device, such as a touch panel display.

[0025] An example of processing by the tabular data search support program of the present disclosure will be described in more detail with reference to Fig. 3. Fig. 3 is a flowchart showing an example of each procedure of the tabular data search support program of the present disclosure. The tabular data search support program of the present disclosure is implemented as follows, for example, using the device 10 of Fig. 1 or Fig. 2 in which the tabular data search support program of the present disclosure is installed. Note that implementation of the tabular data search support program of this embodiment is not limited to use of the device 10 of Fig. 1 or Fig. 2.

[0026] The feature information analysis unit 11 analyzes the tabular data to analyze the feature information (S1, feature information analysis procedure). The tabular data is, for example, data that has defined columns and rows and can be expressed as a table. Specific examples of the tabular data include text files (.txt files), CSV: Comma Separated Values ​​(.csv files), XML: eXtensible Markup Language (.xml files), and JSON: JavaScript Object Notation (.json files). The information recorded as the tabular data is not particularly limited and may be, for example, computer log data. The characteristic information is, for example, information indicating characteristics of the contents included in the tabular data. The tabular data may be, for example, data recorded in the memory 102 or storage device 104 of the device 10, or may be data input from outside the device 10 via the input device 105. Table 1 below shows a specific example of tabular data. The tabular data shown in Table 1 is, for example, data in which the horizontal axis in the first row contains item names and the values ​​of each item are written in the second and subsequent rows. Note that the tabular data in the present disclosure is not limited to this, and may be, for example, data in which the vertical axis in the first column contains item names and the values ​​of each item are written in the horizontal axes in the second and subsequent columns, as shown in Table 2. [Table 1] [Table 2]

[0027] First, the feature information analysis unit 11, for example, recognizes the tabular data and extracts items and values ​​for each item from the tabular data. Then, the feature information analysis unit 11 can estimate complementary data for each item as the feature information. The complementary data is, for example, data obtained by estimating values ​​for items in the tabular data where no data exists. The feature information analysis unit 11 can, for example, extract items and values ​​for each item from the tabular data, identify index items and their values ​​based on at least one of the items and the values ​​for each item, and estimate the complementary data based on the values ​​of other items for each index value in the index items. The index items are, for example, data for items indicating divisions of the tabular data. The index items can be, for example, date and time items. The date and time can be, for example, the date and time when the value of each item in the tabular data was recorded. The feature information analysis procedure can identify items indicating date and time and their values ​​based on at least one of the items and the values ​​for each item, and estimate the complementary data based on the values ​​of other items for each date and time.

[0028] The characteristic information analysis unit 11 identifies the recording date and time (time) of each item as an index item from the tabular data shown in Table 1, for example. Then, the characteristic information analysis unit 11 calculates the average difference between each time (9:30 to 9:40, 9:40 to 9:50) in the value of each item, for example, to estimate the value of each item corresponding to the time between each time (9:35, 9:45 in the tabular data shown in Table 1) as complementary data. As a specific example, for the value of item B in the tabular data shown in Table 1, the complementary data corresponding to 9:35 can be estimated by calculating the average difference as shown in the following formula (1). (Value of item B at 9:30) + (Value of item B at 9:40 - Value of item B at 9:30) * (9:35 - 9:30) / (9:40 - 9:30) = 1.4 + (5.4 - 1.4) * 5 / 10 = 3.4……(1)

[0029] Furthermore, the feature information analysis unit 11 may, for example, estimate values ​​of other items outside the range of the index items as the complementary data. As a specific example, if the index item is the recording date and time of data, the feature information analysis unit 11 can estimate past or future data in the tabular data as the complementary data. The past data is, for example, the value of another item before the date and time at which the value of another item included in the tabular data was recorded. The future data is, for example, the value of another item after the date and time at which the value of another item included in the tabular data was recorded. The feature information analysis unit 11 can, for example, extract the difference in value for each date and time for each item, calculate the average increase or decrease in value per unit time, and estimate the past or future data based on the average increase or decrease.

[0030] The characteristic information analysis unit 11 identifies the recording date and time (time) of each item as the index item from the tabular data shown in Table 1, for example. Then, for each item, the characteristic information analysis unit 11 extracts values ​​recorded in association with each time (9:30, 9:40, 9:50), for example, and extracts items whose values ​​continuously increase or decrease. In the tabular data shown in Table 1, the value of item B continuously increases from 9:30 to 9:50, from 1.40 to 5.40 to 9.40, so item B is extracted. Then, the characteristic information analysis unit 11 calculates the average increase per minute based on the value of item B at 9:30 (1.40) and the value at 9:50 (9.40), and can calculate, for example, an estimated value (11.4) of item B at 9:55 based on the average increase. It should be noted that the feature information analysis unit 11 may stop estimating the complementary data, for example, if there is no item whose value continuously increases or decreases.

[0031] In addition, the feature information analysis unit 11 may, for example, determine whether data for a date and time specified by the user exists in the tabular data, and if the specified date and time does not exist, estimate complementary data corresponding to the specified date and time.

[0032] The characteristic information analysis unit 11 may, for example, identify an item indicating a date and time and its value based on at least one of the item and the value of each item, and analyze the values ​​of other items for each date and time to generate the characteristic information. In this case, the characteristic information analysis unit 11 may, for example, analyze the item with the maximum or minimum value for each date and time and its value as the characteristic information.

[0033] For example, the feature information analysis unit 11 extracts the largest value (item A: 200.00, item B: 9.40, item C: 8.00) for each item of the tabular data shown in Table 1 by binary search. Next, the feature information analysis unit 11 extracts, for example, the time corresponding to each value (item A: 200.00 → 9:30, item B: 9.40 → 9:50, item C: 8.00 → 9:50). Then, the feature information analysis unit 11 combines each analysis result and can generate text data such as "item A had a maximum value of 200.00 at 9:30," "item B had a maximum value of 9.40 at 9:50," and "item C had a maximum value of 8.00 at 9:50" as the feature information.

[0034] Furthermore, the feature information analysis unit 11 may analyze, for example, the change in value for each of the other items at each date and time, and generate the feature information based on the change. The change in value may be, for example, the degree of change in value, or the tendency of the change in value. The degree of change is, for example, the difference between the value of each of the index items and the values ​​of the other items, and may be the amount of change or the rate of change. The feature information analysis unit 13 may generate, for example, feature information for items whose change exceeds a specified threshold.

[0035] The characteristic information analysis unit 11 identifies the recording date and time (time) of each item as an index item from, for example, the tabular data shown in Table 1. Then, the characteristic information analysis unit 11 compares the values ​​of each item between each time (9:30 to 9:40, 9:40 to 9:50), for example, to calculate the difference between each item. As a specific example, the feature information analysis unit 11 calculates the rate of change between 9:35 and 9:40 for the value of item B in the tabular data shown in Table 1, as shown in the following formula (2), and based on the calculated rate of change, can generate text data such as "Item B has increased by 285% at 9:40" as the feature information. (5.40-1.40)*100 / 1.40 = 285(%)……(2)

[0036] Furthermore, the feature information analysis unit 11 may analyze whether there is a tendency for change over time for each item from the tabular data shown in Table 1, for example. The feature information analysis unit 11 extracts the value of each item at each time and searches for items with characteristics such as a value that continues to increase or decrease. As a specific example, for item B in Table 1, the value continues to increase between 9:30 and 9:50. Therefore, the feature information analysis unit 11 can generate text data such as "item B increases continuously from 9:30 to 9:50" as the feature information.

[0037] The search data recording unit 12 records search data in which the feature information is added to the tabular data (S2, search data recording step). The search data recording unit 12 can record the search data, for example, by adding the feature information analyzed and generated in S1 as additional information to the tabular data. The search data recording unit 12 may record the search data in the memory unit of the device 10, for example, or may record it on an external recording medium.

[0038] The tabular data search support method of the present disclosure is, for example, a method implemented by replacing the "procedures" in the tabular data search support program of the present disclosure with "processes." Specifically, the tabular data search support method of the present disclosure includes a feature information analysis process and a search data recording process. The feature information analysis process analyzes tabular data to analyze feature information, and the search data recording process records search data in which the feature information is added to the tabular data. The tabular data search support method of the present disclosure can be implemented, for example, using the tabular data search support device 10 of the present disclosure shown in FIG. 1 or FIG. 2. Note that the tabular data search support method of the present disclosure is not limited to methods using the tabular data search support device 10. For example, the descriptions of the tabular data search support program and the tabular data search support device of the present disclosure can be used to implement the tabular data search support method of the present disclosure.

[0039] The tabular data search support program of the present disclosure includes a feature information analysis step and a search data recording step, and the feature information analysis step analyzes tabular data to analyze feature information, and the search data recording step records search data in which the feature information is added to the tabular data. Therefore, according to the tabular data search support program of the present disclosure, for example, search data in which feature information contributing to a search of tabular data is added to tabular data can be recorded, facilitating searches during analysis using the tabular data and improving search accuracy.

[0040] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0041] <Additional Notes> Some or all of the above embodiments can be described as, but are not limited to, the following supplementary notes. (Appendix 1) It includes a procedure for analyzing characteristic information and a procedure for recording data for searching, the step of analyzing characteristic information analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; A tabular data search support program for causing a computer to execute each of the above procedures. (Appendix 2) The tabular data search support program according to claim 1, wherein the feature information analysis step extracts items and values ​​for each item from the tabular data, estimates complementary data for the items as the feature information, and generates the feature information based on the complementary data. (Appendix 3) The characteristic information analysis step extracts items and values ​​for each item from the tabular data; identifying index items and their values ​​based on at least one of the items and the values ​​for each of the items; 3. The tabular data search support program according to claim 2, wherein the supplementary data is estimated based on values ​​of other items for each index value in the index item. (Appendix 4) the characteristic information analyzing step includes identifying an item indicating a date and time and its value based on at least one of the item and a value for each item; 4. The tabular data search support program according to claim 3, wherein the supplementary data is estimated based on values ​​of other items for each date and time. (Appendix 5) The feature information analysis step includes: 5. A tabular data search support program according to any one of appendices 1 to 4, which identifies an item indicating a date and time and its value based on at least one of the item and the value for each item, analyzes the values ​​of other items for each date and time, and generates the feature information. (Appendix 6) 6. The tabular data search support program according to claim 5, wherein the characteristic information analysis step analyzes changes in values ​​for each of the other items at each date and time, and generates the characteristic information based on the changes. (Appendix 7) 7. The tabular data search support program according to any one of appendices 1 to 6, wherein the tabular data is computer log data. (Appendix 8) a feature information analysis unit and a search data recording unit; the characteristic information analysis unit analyzes the tabular data to analyze the characteristic information; The search data recording unit records search data in which the feature information is added to the tabular data. (Appendix 9) The tabular data search support device according to claim 8, wherein the feature information analysis unit extracts items and values ​​for each item from the tabular data, estimates complementary data for the items as the feature information, and generates the feature information based on the complementary data. (Appendix 10) The feature information analysis unit extracting items and values ​​for each item from the tabular data; identifying index items and their values ​​based on at least one of the items and the values ​​for each of the items; 10. The tabular data search support device according to claim 9, wherein the supplementary data is estimated based on values ​​of other items for each index value in the index item. (Appendix 11) the characteristic information analysis unit identifies an item indicating a date and time and its value based on at least one of the item and the value of each item; 11. The tabular data search support device according to claim 10, wherein the supplementary data is estimated based on values ​​of other items for each date and time. (Appendix 12) 12. The tabular data search support device according to claim 8, wherein the feature information analysis unit identifies an item indicating a date and time and its value based on at least one of the item and the value of each item, and analyzes values ​​of other items for each date and time to generate the feature information. (Appendix 13) 13. The tabular data search support device according to claim 12, wherein the feature information analysis unit analyzes changes in values ​​for each of the other items at each date and time, and generates the feature information based on the changes. (Appendix 14) 14. The tabular data search support device according to any one of appendices 8 to 13, wherein the tabular data is computer log data. (Appendix 15) A feature information analysis step and a search data recording step are included, the characteristic information analyzing step analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; A tabular data search support method in which each of the steps is executed by a computer. (Appendix 16) 16. The tabular data search support method according to claim 15, wherein the feature information analysis step extracts items and values ​​for each item from the tabular data, estimates complementary data for the items as the feature information, and generates the feature information based on the complementary data. (Appendix 17) The characteristic information analysis step includes: extracting items and values ​​for each item from the tabular data; identifying index items and their values ​​based on at least one of the items and the values ​​for each of the items; 17. The tabular data search support method according to claim 16, wherein the complementary data is estimated based on values ​​of other items for each index value in the index item. (Appendix 18) the characteristic information analyzing step identifies an item indicating a date and time and its value based on at least one of the item and the value of each item; 18. The tabular data search support method according to claim 17, wherein the complementary data is estimated based on values ​​of other items for each date and time. (Appendix 19) The characteristic information analysis step includes: 19. A tabular data search support method according to any one of appendices 15 to 18, wherein an item indicating a date and time and its value are identified based on at least one of the item and the value of each item, and the feature information is generated by analyzing the values ​​of other items for each date and time. (Appendix 20) 20. The tabular data search support method according to claim 19, wherein the feature information analysis step analyzes changes in values ​​for each of the other items at each date and time, and generates the feature information based on the changes. (Appendix 21) 21. The tabular data search support method according to any one of appendices 15 to 20, wherein the tabular data is computer log data. (Appendix 22) It includes a procedure for analyzing characteristic information and a procedure for recording data for searching, the step of analyzing characteristic information analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; A computer-readable recording medium storing a tabular data search support program for causing a computer to execute each of the above procedures. (Appendix 23) The recording medium of claim 22, wherein the feature information analysis step extracts items and values ​​for each item from the tabular data, estimates complementary data for the items as the feature information, and generates the feature information based on the complementary data. (Appendix 24) The feature information analysis step includes: extracting items and values ​​for each item from the tabular data; identifying index items and their values ​​based on at least one of the items and the values ​​for each of the items; 24. The recording medium of claim 23, wherein the complementary data is estimated based on values ​​of other items for each index value in the index item. (Appendix 25) the characteristic information analyzing step includes identifying an item indicating a date and time and its value based on at least one of the item and a value for each item; 25. The recording medium of claim 24, wherein the complementary data is estimated based on values ​​of other items for each date and time. (Appendix 26) The feature information analysis step includes: Identifying an item indicating a date and time and its value based on at least one of the item and the value of each item, and analyzing the values ​​of other items for each date and time to generate the characteristic information; 26. The recording medium according to any one of appendices 22 to 25, wherein the search data recording step includes adding the item with the maximum or minimum value for each date and time and its value to the tabular data as the characteristic information. (Appendix 27) the step of analyzing the characteristic information analyzes a change in the value for each of the other items at each date and time, and generates the characteristic information based on the change. 27. The recording medium according to claim 26, wherein the search data recording step adds the change to the tabular data as the feature information. (Appendix 28) the step of analyzing the characteristic information analyzes a change in the value for each of the other items at each date and time, and generates the characteristic information based on the change. The search data recording procedure includes: 28. The recording medium according to claim 22 or 27, wherein the change is added to the tabular data as the characteristic information. (Appendix 29) 29. The recording medium according to any one of appendices 22 to 28, wherein the tabular data is computer log data. [Industrial Applicability]

[0042] According to the present disclosure, tabular data can be recorded in an easily searchable manner, and therefore the present disclosure can be suitably used in the IT field. [Explanation of symbols]

[0043] 10. Tabular data search support device 11. Characteristic Information Analysis Department 12 Search data recording section 101 Central Processing Unit 102 memory 103 Bus 104 Storage device 105 Input Device 106 Output Device 107 Communication Devices

Claims

1. It includes a procedure for analyzing characteristic information and a procedure for recording data for searching, the step of analyzing characteristic information analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; A tabular data search support program for causing a computer to execute each of the above procedures.

2. 2. The tabular data search support program according to claim 1, wherein the characteristic information analysis step extracts items and values ​​for each item from the tabular data, estimates complementary data for the items as the characteristic information, and generates the characteristic information based on the complementary data.

3. The characteristic information analysis step extracts items and values ​​for each item from the tabular data; identifying index items and their values ​​based on at least one of the items and the values ​​for each of the items; 3. The tabular data search support program according to claim 2, wherein the supplementary data is estimated based on values ​​of other items for each index value in the index item.

4. the characteristic information analyzing step includes identifying an item indicating a date and time and its value based on at least one of the item and a value for each item; 4. The tabular data search support program according to claim 3, wherein the supplementary data is estimated based on values ​​of other items for each date and time.

5. The feature information analysis step includes:

5. A tabular data search support program according to claim 1, wherein an item indicating a date and time and its value are identified based on at least one of the item and the value for each item, and the characteristic information is generated by analyzing the values ​​of other items for each date and time.

6. 6. The tabular data search support program according to claim 5, wherein said characteristic information analyzing step analyzes a change in value for each of said other items at each date and time, and generates said characteristic information based on said change.

7. 5. The tabular data search support program according to claim 1, wherein the tabular data is log data of a computer.

8. a feature information analysis unit and a search data recording unit; the characteristic information analysis unit analyzes the tabular data to analyze the characteristic information; The search data recording unit records search data in which the feature information is added to the tabular data.

9. A feature information analysis step and a search data recording step are included, the characteristic information analyzing step analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; A tabular data search support method in which each of the steps is executed by a computer.

10. It includes a procedure for analyzing characteristic information and a procedure for recording data for searching, the step of analyzing characteristic information analyzes the tabular data to analyze the characteristic information; the search data recording step includes recording search data obtained by adding the characteristic information to the tabular data; A computer-readable recording medium storing a tabular data search support program for causing a computer to execute each of the above procedures.

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