JP2019169087A - Information aggregation device, information aggregation method, and program - Google Patents

Abstract

To provide an information aggregation device capable of reducing an amount of trace information while maintaining required accuracy without performing previous setting such as an aggregation condition, and to provide an information aggregation method, and a program.SOLUTION: A monitoring device 100 includes a calculation part 120 and an aggregation part 140. The calculation part 120 calculates importance of each event in a history on the basis of trace information indicating the history of the event relating to an object to be monitored. The aggregation part 140 aggregates the history of the event in the trace information on the basis of the calculated importance of each event.SELECTED DRAWING: Figure 10

Description

  The present invention relates to an information aggregating apparatus, an information aggregating method, and a program.

  In performance monitoring of a transaction executed on a computer, it is possible to easily identify a problem occurrence point when a performance problem occurs by collecting processing time for each process in the transaction as performance information. For example, in performance monitoring of a transaction processing system that involves execution of an application such as a Web system, the processing time for each function or object in the application is collected, and the problematic function or object is specified. The problem with this monitoring method is that the performance information becomes enormous due to the collection of information for each of the processes (functions and objects) within the subdivided application, and a large amount of resources are required to accumulate the performance information.

  As a technique for reducing the amount of resources required for performance monitoring of such transaction processing, for example, instead of collecting and storing performance information for all processing, functions and objects that are commonly executed in general transactions A method for collecting only the processes is known. Patent Document 1 discloses a technique for processing performance information in accordance with a predetermined processing method when a transaction processing time is equal to or less than a predetermined value in an apparatus for collecting transaction performance information. Patent Document 2 discloses a technique for determining an element to be collected based on a dependency relationship between components of a storage network in an apparatus for collecting storage network performance information.

  As a related technique, Patent Document 3 discloses a technique for sampling performance information having a variation rate of a predetermined value or more and extracting performance information having a sampling rate of a predetermined value or more in an analyzer. Patent Document 4 discloses a technique for changing a transmission interval according to a position and time in a position information transmission device. Patent Document 5 discloses a technique for calculating a standard work time in production line management.

JP 09-244998 A JP 2005-157933 A Japanese Patent Application Laid-Open No. 2006-149080 JP 2012-257006 A JP 2010-128654 A

  In the techniques described in Patent Documents 1 and 2 described above, it is necessary for an administrator or the like to predefine and set conditions relating to performance information to be collected, such as a transaction processing method and dependency between elements. . In general, it is difficult to define such a condition related to a collection target for a complex transaction in which various processes are mixed. Also, if an incorrect condition is set or if the set condition is insufficient, the performance information necessary to identify the problem is not collected, or a large amount of performance information is unintentionally collected and the resources are depleted. Problems occur.

  An object of the present invention is to solve the above-mentioned problems and to reduce the amount of trace information while maintaining necessary accuracy without performing pre-setting of collection conditions and the like, an information aggregation device, an information aggregation method, and Is to provide a program.

  The information aggregating apparatus in one aspect of the present invention is based on the trace information representing the history of events related to the monitoring target, calculates the importance of each event in the history, and based on the calculated importance of each event, Aggregating means for aggregating the history of the events in the trace information.

  In the information aggregation method according to one aspect of the present invention, the importance level of each event in the history is calculated based on the trace information indicating the history of the event related to the monitoring target, and the trace information in the trace information is calculated based on the calculated importance level of each event. The event history is aggregated.

  The program according to one aspect of the present invention calculates the importance of each event in the history based on the trace information indicating the history of the event related to the monitoring target, and the trace information based on the calculated importance of each event. The process of aggregating the history of the events in is executed.

  The effect of the present invention is that the amount of trace information can be reduced while maintaining the required accuracy without pre-setting collection conditions and the like.

It is a block diagram which shows the structure of the performance monitoring base | substrate 1 in 1st Embodiment. It is a block diagram which shows the structure of the monitoring apparatus 100 mounted in the computer in 1st Embodiment. It is a figure which shows the example of the trace information (performance information) in 1st Embodiment. It is a figure which shows the example of the identification result of a trace pattern in 1st Embodiment. It is a figure which shows the example of the total result in 1st Embodiment. It is a figure which shows the example of the trace information preserve | saved at the trace information storage part 150 in 1st Embodiment. It is a figure which shows the other example of the trace information preserve | saved at the trace information storage part 150 in 1st Embodiment. It is a flowchart which shows operation | movement of the monitoring apparatus 100 of 1st Embodiment. It is a figure which shows the example of the complementation result in 1st Embodiment. It is a block diagram which shows the characteristic structure of 1st Embodiment. It is a block diagram which shows the structure of the performance monitoring base | substrate 1 in 2nd Embodiment. It is a figure which shows the example of the display screen in 2nd Embodiment. It is a block diagram which shows the structure of the position monitoring base | substrate 2 in 3rd Embodiment. It is a figure which shows the example of the trace information (position information) in 3rd Embodiment.

  DESCRIPTION OF EMBODIMENTS Embodiments for carrying out the invention will be described in detail with reference to the drawings. Note that, in each drawing and each embodiment described in the specification, the same reference numerals are given to the same components, and description thereof will be omitted as appropriate.

<First Embodiment>
A first embodiment will be described. In the first embodiment, a case where the monitoring target is a transaction executed on a computer will be described as an example.

  First, the configuration of the first embodiment will be described. FIG. 1 is a block diagram showing a configuration of a performance monitoring base 1 in the first embodiment. The performance monitoring platform 1 is a system that collects and analyzes performance information, such as a system that monitors Web system performance and application performance.

  Referring to FIG. 1, the performance monitoring base 1 of the first embodiment includes a monitoring device 100, a processing device 200, and a client terminal 300. The monitoring device 100 is an embodiment of the information aggregation device of the present invention.

  The monitoring device 100 and the processing device 200, and the processing device 200 and the client terminal 300 are connected by a network or the like.

  The client terminal 300 is a terminal such as a user of the processing device 200, for example, and requests the processing device 200 to execute a transaction.

  The processing device 200 is a computer such as a server device, for example, and executes an application program corresponding to a transaction in response to a request from the client terminal 300. Thereby, a series of processes such as functions and objects included in the application program are executed in order according to the program. Each time the processing device 200 executes a transaction, the processing device 200 acquires information such as a start time and an end time for each processing of functions, objects, and the like included in the transaction.

  The monitoring device 100 includes a collection unit 110, a calculation unit 120, a total data storage unit 130, an aggregation unit 140, and a trace information storage unit 150.

  The collection unit 110 collects information acquired by the processing device 200 as trace information (performance information) related to a monitoring target (transaction). The trace information represents a history of events to be monitored (hereinafter also referred to as monitoring events) for the monitoring target (transaction).

  In the first embodiment, the monitoring event is each process included in the transaction, and the history of the monitoring event (process) is represented by the start time and end time (information on the monitoring event (process)) of each process. Is done.

  The calculation unit 120 identifies the trace pattern of the trace information of each transaction collected by the collection unit 110. The trace pattern is a pattern of processing order in a transaction. Also, total information is generated based on the trace information of each transaction. The total information represents the average processing time (average time length) and importance of each process in each trace pattern. The calculation unit 120 stores the trace pattern and the total information in the total data storage unit 130.

  The total data storage unit 130 stores the trace pattern identified by the calculation unit 120 and the total information.

  The aggregation unit 140 stores the trace information collected by the collection unit 110 in the trace information storage unit 150. Further, the aggregating unit 140 aggregates processing histories for each piece of trace information stored in the trace information storage unit 150 based on the importance included in the aggregated information.

  The trace information storage unit 150 stores trace information.

  Note that the monitoring device 100 may be a computer that includes a CPU (Central Processing Unit) and a recording medium that stores a program and that operates by control based on the program.

  FIG. 2 is a block diagram illustrating a configuration of the monitoring device 100 mounted on a computer according to the first embodiment.

  Referring to FIG. 2, the monitoring apparatus 100 includes a CPU 101, a storage device 102 (recording medium), an input / output device 103, and a communication device 104. The CPU 101 executes an instruction (Instruction) of a program for mounting the collection unit 110, the calculation unit 120, and the aggregation unit 140. The storage device 102 is, for example, a hard disk, a memory, or the like, and stores data in the total data storage unit 130 and the trace information storage unit 150. The input / output device 103 is a keyboard, a display, or the like, for example, and receives an instruction to collect trace information from an administrator of the monitoring apparatus 100 or the like. The communication device 104 receives information acquired by the processing device 200 from the processing device 200.

  Note that some or all of the components of the monitoring device 100 may be implemented by general-purpose or dedicated circuits, processors, or combinations thereof. These circuits and processors may be constituted by a single chip or may be constituted by a plurality of chips connected via a bus. Moreover, a part or all of each component may be implemented by a combination of the above-described circuit and the like and a program. In addition, when a part or all of each component is implemented by a plurality of information processing devices and circuits, the plurality of information processing devices and circuits may be centrally arranged or distributedly arranged. Also good. For example, the information processing apparatus, the circuit, and the like may be implemented in a form in which each is connected via a communication network, such as a client and server system and a cloud computing system.

  Next, the operation of the first embodiment will be described.

  First, transaction processing executed by the processing device 200 and trace information (performance information) generated by the collection unit 110 will be described. FIG. 3 is a diagram illustrating an example of trace information (performance information) in the first embodiment.

  FIG. 3 shows an example of trace information generated when the transaction T is executed by the processing device 200. In the trace information, the actual time (for example, UTC (Coordinated Universal Time)) is used for the start time and end time of each process. In the example of FIG. The time set to 0 is described. In the trace information of FIG. 3, the trace ID (Identifier) is an identifier for identifying the start and end of processing.

  As shown in FIG. 3, when the transaction T is started, the trace ID “PS” is recorded together with the start time of the transaction. Next, when the process a is started, the trace ID “PaS” is recorded together with the start time of the process a. Next, when the process b is called from the process a, the trace ID “PbS” is recorded together with the start time of the process b. When the process b ends, the trace ID “PbE” is recorded together with the end time of the process b. Next, when the process c is called from the process a, the trace ID “PcS” is recorded together with the start time of the process c. When the process c ends, the trace ID “PcE” is recorded together with the end time of the process c. When the process a ends, the trace ID “PaE” is recorded together with the end time of the process a. When all the processes are completed and the transaction is completed, the trace ID “PE” is recorded together with the end time.

  Next, a trace pattern identification process by the calculation unit 120 will be described. FIG. 4 is a diagram illustrating an example of the trace pattern identification result in the first embodiment.

  FIG. 4 shows an example of trace information collected for the transactions T1 and T2 and trace patterns identified for these trace information.

  In transaction T1, processing c is executed after processing a and processing b are executed. In transaction T2, process d is executed after process a and process b are executed. In this case, since the recorded trace IDs are partially different between the transactions T1 and T2, they are identified as different trace patterns.

  In this case, as shown in FIG. 4, the trace patterns of the trace information T1a and the trace information T2a are identified as the trace pattern TP1 and the trace pattern TP2, respectively.

  The calculation unit 120 stores the identified trace pattern in the total data storage unit 130.

  Next, the aggregation process by the calculation unit 120 will be described. FIG. 5 is a diagram illustrating an example of a totaling result in the first embodiment.

  FIG. 5 shows an example of the aggregation process using the trace information T1a and T1b collected for the transaction T1 and the trace information T2a and T2b collected for the transaction T2. The trace information T1a and T1b are identified as the trace pattern TP1 in FIG. 4, and the trace information T2a and T2b are identified as the trace pattern TP2.

  The calculation unit 120 performs aggregation processing using the trace information identified by the same trace pattern. When some patterns are the same between different trace patterns, the calculation unit 120 performs aggregation processing for the some patterns using the trace information identified by the different trace patterns.

  The calculation unit 120 calculates the average processing time and the importance of each section divided by the trace ID as a totaling process. In the example of FIG. 5, the average processing time and the importance are calculated for each section in which two consecutive trace IDs in the trace pattern are set as a start point (from) and an end point (to), respectively.

  In the total information of FIG. 5, the average processing time and the importance are calculated for each section in which two consecutive trace IDs in the trace pattern are set as a start point (from) and an end point (to), respectively.

  Here, the average processing time is an average value of the processing time (time length) of each section.

  In the total information of FIG. 5, the processing time of each trace information T1a, T1b, T2a, T2b is set in the “processing time” column for each section, and the average processing time calculated based on these processing times is “average processing”. It is set in the "Time" column.

  The importance level is a criterion for determining the trace IDs to be aggregated and deleted when the aggregation unit 140 aggregates the processing history in the trace information. For example, the importance value is calculated so as to be smaller as the average processing time of the section is shorter, the number of processing executions is larger, and the variation in the processing time is smaller. In this case, the importance is calculated, for example, by calculating a standard deviation of the processing time, calculating a variation coefficient obtained by dividing the standard deviation by the average processing time, and further dividing the variation coefficient by the number of executions.

  In the total information of FIG. 5, the number of executions, standard deviation, coefficient of variation, and importance of each section calculated based on the trace information T1a, T1b, T2a, T2b are respectively shown in the “execution count” column, “standard”. It is shown in the “deviation” column, the “variation coefficient” column, and the “importance” column.

  In addition, if the value which can judge the importance of each area can be calculated, the calculation part 120 may calculate importance by another method. The calculation unit 120 may calculate the importance by a calculation method according to the characteristics of the trace information.

  Further, it is not necessary for the population to be aggregated to be trace information of all collected transactions. The calculation unit 120 may calculate the importance from the processing time of the trace information of the latest arbitrary transaction (for example, the latest 100 transactions) for each section as the population. The number of transactions used as a population is reflected in the sensitivity of importance. When using the most recent transaction as a population, if the processing time of a new transaction deviates significantly from the average processing time up to a certain point, the average processing time obtained by the new aggregation processing fluctuates greatly, and the importance increases. . In addition, when the processing time deviating from the average processing time up to a certain point continues, the new average processing time is calculated from the latest processing time, so the coefficient of variation gradually decreases and the importance also increases. It becomes small in the beginning.

  The calculation unit 120 stores the average processing time and importance of each section calculated by the aggregation process in the aggregation data storage unit 130.

  Next, the aggregation process performed by the aggregation unit 140 will be described. 6 and 7 are diagrams illustrating examples of trace information stored in the trace information storage unit 150 according to the first embodiment.

  The aggregating unit 140 assigns the trace pattern identified by the calculation unit 120 and the importance to each trace information, and stores the trace information in the trace information storage unit 150. Here, for example, the aggregation unit 140 adds the importance of the section having the trace ID as the end point to each trace ID included in the trace information.

  In the example of FIG. 6, trace information T1a 'is shown in which the trace pattern TP1 and the importance of each section of FIG. 5 are added to the trace information T1a of FIG.

  The aggregating unit 140 further aggregates the processing history by deleting the information of the trace ID whose importance is less than a predetermined threshold from the processing history in each trace information stored in the trace information storage unit 150.

  In the example of FIG. 7, information of trace IDs “PaS”, “PbS”, “PbE”, and “PE” having importance less than the threshold value “0.02” is deleted from the trace information T1a ′, and the trace information T1a ′ is deleted. '' Has been updated.

  The aggregation timing may be a timing at which the aggregation unit 140 stores the trace information in the trace information storage unit 150, or an arbitrary timing after the storage. For example, when resources that can be used as the trace information storage unit 150 are compressed due to the storage of trace information over a long period of time, the aggregation unit 140 increases the importance threshold and deletes trace ID information less than the threshold. Run again. As a result, even if the resource is limited, it is deleted from the trace ID information of low importance and efficient trace information can be stored.

  FIG. 8 is a flowchart illustrating the operation of the monitoring apparatus 100 according to the first embodiment.

  The collection unit 110 collects trace information from the processing device 200 (step S101).

  For example, the collection unit 110 collects the trace information T1a, T1b, T2a, and T2b in FIG.

  The calculation unit 120 identifies the trace pattern of the trace information (Step S102).

  For example, the calculation unit 120 identifies the trace information T1a and T1b as the trace pattern TP1 in FIG. 4, and identifies the trace information T2a and T2b as the trace pattern TP2 in FIG.

  The calculation unit 120 generates aggregate information based on the trace information (step S103).

  For example, the calculation unit 120 generates the aggregate information illustrated in FIG. 5 based on the trace information T1a, T1b, T2a, and T2b.

  The aggregation unit 140 stores the trace information in the trace information storage unit 150 (Step S104).

  For example, the aggregation unit 140 stores the trace information T1a in the trace information storage unit 150 as the trace information T1a ′ as illustrated in FIG. The calculation unit 120 similarly stores other trace information T1b, T2a, and T2b.

  The aggregating unit 140 aggregates the history of processing in each piece of trace information based on the importance included in the aggregate information (step S105).

  For example, the aggregating unit 140 aggregates the processing history in the trace information T1a ′ based on the aggregation information in FIG. 5 as the trace information T1a ″ in FIG.

  Thereafter, the processing from step S101 is repeatedly executed.

  Thus, the operation of the embodiment is completed.

  Note that the monitoring apparatus 100 may further include a complementing unit (not shown) that supplements information deleted by aggregation in each trace information in response to a request from an administrator or the like.

  FIG. 9 is a diagram illustrating an example of a complement result in the first embodiment.

  In this case, the complement unit complements the information deleted from the trace information based on the trace pattern in which the trace information is identified and the average processing time of each section, which is stored in the aggregate data storage unit 130. Since the section having the deleted trace ID as the end point has low importance, there is little variation in processing time. For this reason, the approximate value of the time of the deleted trace ID can be calculated by using the average processing time of the section as an approximate value of the processing time of the section. For the trace ID that has not been deleted, the actual time of the trace ID is used as it is.

  For example, as illustrated in FIG. 9, the complement unit supplements the trace IDs “PaS”, “PbS”, “PbE”, and “PE” based on the trace pattern “TP1” of the trace information T1a ″. Further, the complementing unit calculates an approximate value of the time of the complemented trace ID “PaS” by adding the average processing time between the trace IDs “PS” and “PaS” to the time of the trace ID “PS”. . Further, the complementing unit adds the average processing time between the trace IDs “PaS” and “PbS” to the approximate value of the time of the supplemented trace ID “PaS”, so that the time of the complemented trace ID “PbS” is obtained. The approximate value of is calculated.

  Next, a characteristic configuration of the first embodiment will be described. FIG. 10 is a block diagram showing a characteristic configuration of the first embodiment.

  Referring to FIG. 10, the monitoring device 100 (information aggregation device) includes a calculation unit 120 and an aggregation unit 140. The calculation unit 120 calculates the importance of each event in the history based on the trace information that represents the history of the event related to the monitoring target. The aggregating unit 140 aggregates event histories in the trace information based on the calculated importance of each event.

  Next, the effect of the first embodiment will be described.

  According to the first embodiment, it is possible to reduce the amount of trace information, such as transaction performance information, while maintaining necessary accuracy without setting collection conditions and the like in advance. The reason is that the monitoring device 100 calculates the importance of each event (process) in the history based on the trace information (performance information) representing the history of the event (process) related to the monitored object, and the importance of each event (process). This is because the history of events in the trace information (performance information) is aggregated based on the degree.

  As a result, the amount of resources for storing trace information can be reduced while maintaining the required accuracy. Therefore, even if the resources for storing the trace information are limited, the trace information necessary for analyzing the monitoring target can be accumulated. In addition, since it is not necessary to set in advance the conditions for collecting trace information by an administrator or the like, it is possible to efficiently reduce the amount of trace information and the amount of necessary resources.

<Second Embodiment>
Next, a second embodiment will be described. The second embodiment is different from the first embodiment in that trace information is displayed in response to a request from an administrator or the like.

  FIG. 11 is a block diagram showing a configuration of the performance monitoring base 1 in the second embodiment. Referring to FIG. 11, the performance monitoring platform 1 of the second embodiment includes a client terminal 400 in addition to the components of the performance monitoring platform 1 of the first embodiment. The monitoring device 100 according to the second embodiment includes a display control unit 160 in addition to the components of the monitoring device 100 according to the first embodiment.

  The client terminal 400 is, for example, a terminal such as an administrator, acquires trace information from the monitoring apparatus 100, and outputs (displays) the information to the administrator or the like. Hereinafter, the client terminal 400 is also referred to as a display device.

  The display control unit 160 generates a screen for displaying trace information in response to a request from the client terminal 400 and transmits the screen to the client terminal 400. The display control unit 160 extracts the trace ID to be displayed based on the importance.

  FIG. 12 is a diagram illustrating an example of a display screen in the second embodiment.

  When the display control unit 160 receives designation of the trace information to be displayed from the client terminal 400, the display control unit 160 acquires the trace information from the trace information storage unit 150. Then, the display control unit 160 generates a screen for displaying the acquired trace information and transmits it to the client terminal 400. Here, the display control unit 160 sets trace ID information having a high importance level (the importance level is equal to or higher than a predetermined threshold) on the screen.

  For example, as shown in FIG. 12, the display control unit 160 generates a screen (a) in which the trace ID information equal to or greater than the threshold value “0.02” is set for the above-described trace information T1a ′. The client terminal 400 outputs the screen (a) to an administrator or the like.

  The display control unit 160 receives from the client terminal 400 designation of a trace ID on which detailed information is to be displayed (to be drilled down) on the screen. The display control unit 160 drills down (expands) information on the trace ID between the designated trace ID and the next displayed trace ID, which has a low importance (the importance is less than a predetermined threshold). And generate a screen to display.

  For example, when the trace ID “PaE” is designated on the screen (a), the display control unit 160 generates the screen (b) in which the information of the trace ID “PE” after the trace ID “PaE” is also developed.

  Similarly, when the trace ID “PS” is designated on the screen (b), the display control unit 160 sets the trace IDs “PaS”, “PbS”, and “PbE” between the trace IDs “PS” and “PcS”. A screen (c) in which information is also developed is generated.

  Here, a case has been described as an example where all the information of the trace IDs with low importance between the specified trace ID and the next trace ID is expanded. However, the present invention is not limited to this, and a plurality of importance thresholds may be set to perform development in multiple stages. For example, when a trace ID having a high importance level is designated, the display control unit 160 expands information on a trace ID having a medium importance level between the trace ID and the next trace ID. If a medium trace ID is designated, trace ID information of low importance between the trace ID and the next trace ID may be developed.

  In addition, when the information of the trace ID to be expanded is deleted by aggregation, the display control unit 160, as described in the first embodiment, based on the trace pattern and the average processing time, Information may be complemented and displayed.

  Next, effects of the second embodiment will be described.

  Normally, when displaying trace information related to a transaction in a drill-down format in this way, hierarchization is performed in units of functions and objects. That is, on the first screen, upper functions and the like are displayed. When a function or the like to be drilled down is designated, a function or the like to be executed by the designated function or the like is displayed. Therefore, when the processing hierarchy is deep, it is necessary to repeat the expansion up to the deep hierarchy, and the number of operations required for the expansion increases.

  On the other hand, in the second embodiment, the hierarchization is performed based on the importance. That is, in the first screen, trace ID information with high importance is displayed, and when a trace ID to be drilled down is specified, a trace ID with low importance between the trace ID and the next trace ID is specified. Information is displayed. For this reason, by appropriately setting the threshold value of importance, the amount of history displayed with the expansion can be suppressed to the allowable range of the screen resource. Therefore, according to the second embodiment, a portion that needs to be confirmed in the trace information can be efficiently displayed with few operations.

<Third Embodiment>
Next, a third embodiment will be described. The third embodiment is different from the first embodiment in that the monitoring target is a stay position accompanying movement of a person or an object.

  FIG. 13 is a block diagram showing a configuration of the position monitoring base 2 in the third embodiment. The position monitoring platform 2 collects and analyzes position information, such as a system that performs correlation analysis with movements of people and goods, a traffic control system, a system that monitors and analyzes movements of goods in production lines and logistics, and the like. System.

  Referring to FIG. 13, the location monitoring infrastructure 2 of the third embodiment includes a mobile terminal 201 instead of the client terminal 300 and the processing device 200 of the performance monitoring infrastructure 1 of the first embodiment.

  In the third embodiment, the monitoring event is a stay at each position accompanying the movement of a person or an object, and the history of the monitoring event (stay) is the start time (arrival time) of the stay at each position, and It is represented by information (information related to a monitoring event (stay)) such as an end time (leave time).

  The mobile terminal 201 is a terminal possessed by a person or attached to an object. The mobile terminal 201 detects the position of its own terminal using GPS or the like, and acquires information such as the start time (arrival time) and end time (leave time) of the stay each time it stays at each position.

  The collection unit 110 of the monitoring device 100 collects information acquired by the mobile terminal 201 as trace information (position information) related to the monitoring target (stay).

  As in the first embodiment, the calculation unit 120 uses the trace pattern of the trace information as an identifier and generates aggregate information based on the trace information. In this case, the trace pattern is a pattern of order of stay accompanying movement. The total information represents the average stay time (average time length) and importance of staying at each position in each trace pattern.

  The aggregation unit 140 aggregates the stay history in each piece of trace information stored in the trace information storage unit 150, as in the first embodiment.

  FIG. 14 is a diagram illustrating an example of trace information (position information) in the third embodiment. For example, the monitoring apparatus 100 identifies the trace pattern based on the trace information as shown in FIG. 14, and calculates the importance of each section divided by the trace ID. Then, the monitoring device 100 aggregates the stay history in the trace information (position information) by deleting the information of the trace ID whose importance is less than a predetermined threshold.

  Next, the effect of the third embodiment will be described.

  According to the third embodiment, even if the trace information is the position information associated with the movement of a person or an object, the position information The amount can be reduced. The reason is that the monitoring device 100 calculates the importance of each event (stay) in the history based on a plurality of pieces of trace information (position information) representing the history of the event (stay) related to the monitoring target, and each event (stay). This is because the history of events of the trace information (position information) is aggregated based on the importance level.

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

  The present invention can be widely applied to systems that collect trace information to be monitored. For example, the present invention can be used to efficiently accumulate a large amount of performance information in a transaction processing system that executes an application. Further, the present invention can be used for efficiently storing a large amount of position information in a position information management system.

DESCRIPTION OF SYMBOLS 1 Performance monitoring base 2 Position monitoring base 100 Monitoring apparatus 101 CPU
DESCRIPTION OF SYMBOLS 102 Storage device 103 Input / output device 104 Communication device 110 Collection part 120 Calculation part 130 Total data storage part 140 Aggregation part 150 Trace information storage part 160 Display control part 200 Processing apparatus 201 Mobile terminal 300 Client terminal 400 Client terminal

Claims (10)

Based on the trace information representing the history of events related to the monitoring target, calculating the importance of each event in the history;
Aggregating means for aggregating the history of the event in the trace information based on the calculated importance of each event;
An information aggregating apparatus comprising: The calculation means identifies an event pattern in the trace information, and calculates the importance of the event based on the average time length of each event in each pattern.
The information aggregation device according to claim 1. For each event in each pattern, the calculation means determines the importance of the event so that the average time length of the event is short, the number of the event is large, and the variation in the time length of the event is small. calculate,
The information aggregation device according to claim 2. The aggregation unit deletes information on an event having an importance less than a predetermined value from the event history in the trace information.
The information aggregating apparatus according to claim 1. Information related to an event whose importance is less than a predetermined value that has been deleted from the event history in the trace information is based on an average processing time of events whose importance is less than a predetermined value in the pattern in which the trace information is identified. Complement, further equipped with supplement means,
The information aggregation device according to claim 4. When the display unit displays information on an event having an importance level greater than or equal to a predetermined value in the event history of the trace information, and any one of the events having an importance level equal to or higher than the predetermined value is designated, In addition to information about events whose importance is greater than or equal to a predetermined value in the history of elephants, the importance between the specified event and the next event among events whose importance is greater than or equal to a predetermined value is less than the predetermined value Further comprising display control means for causing the display means to display information about the event,
The information aggregating apparatus according to claim 1. The monitoring target is a transaction executed on a computer, the event is each process included in the transaction,
The calculation means calculates the importance of each process in the history,
The aggregation means aggregates the history based on the importance of each process.
The information aggregating apparatus according to claim 1. The monitoring target is the movement of a person or an object, and the event is a stay at each position accompanying the movement,
The calculation means calculates the importance of stay at each position in the history,
The aggregation means aggregates the history based on the importance of stay at each position.
The information aggregating apparatus according to claim 1. Based on the trace information representing the history of events related to the monitoring target, calculate the importance of each event in the history,
Based on the calculated importance of each event, the history of the event in the trace information is aggregated,
Information aggregation method. On the computer,
Based on the trace information representing the history of events related to the monitoring target, calculate the importance of each event in the history,
Based on the calculated importance of each event, the history of the event in the trace information is aggregated,
A program that executes processing.

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