JP6646340B2 - Dispersing apparatus and dispersing method - Google Patents

Description

  The present invention relates to a dispersing apparatus and a dispersing method.

  2. Description of the Related Art In general, a distributed DB system that stores large-scale data in a plurality of databases (DBs) in a distributed manner is known. For example, in a system in which a predetermined Web server executes a process for a user's request for each request, data required for processing each request is stored in a DB of each Web server (see Patent Document 1).

  On the other hand, in a distributed DB system that stores subscriber data of services such as telephone services, subscriber data is distributed and stored in a plurality of DBs for each community in the area to which the subscriber belongs. A service use request by a subscriber is processed in a DB that stores the data of the subscriber. Note that statistical data of daytime population and day / night population ratio of each prefecture is disclosed (see Non-Patent Document 1).

JP 2014-096113 A

“I Daytime Population”, [online], 2000, Statistics Bureau, Ministry of Internal Affairs and Communications, [Search January 5, 2017], Internet <URL: http://www.stat.go.jp/data/kokusei/2000/ jutsu1 / 00 / 01.htm>

  However, if subscriber data of a community in an area where population changes day and night, such as an urban area or a bed town, is stored in a distributed DB system, the traffic volume for a DB that stores data of the community subscriber fluctuates day and night. I do. In the case of a community in such a region, when a DB that accommodates subscriber data is determined assuming a population of day or night, a time zone outside the assumption occurs, and resources of each DB are effectively used. There was a fear that it could not be used.

  Also, if data is stored in the same DB with a bias toward either the data of the subscribers in the community where the daytime population tends to be large or the data of the subscribers in the community where the nighttime population tends to be large In addition, the amount of traffic is unevenly distributed between DBs depending on the time zone. Then, there is a possibility that the traffic that can be processed by the entire distributed DB system cannot be effectively processed.

  The present invention has been made in view of the above, and it is an object of the present invention to provide a highly efficient distributed DB system that responds to a temporal change in the population of a community to which a user belongs.

  In order to solve the above-described problems and achieve the object, a distributed device according to the present invention is a database system that accommodates data of a plurality of users in a distributed manner in a plurality of databases in units of a community to which each user belongs. A calculating unit that calculates the traffic volume transmitted from each community at each time point using the population of each community and the average value of the traffic volume per user at a plurality of predetermined time points; A counting unit that counts the traffic volume transmitted at each time from the community corresponding to the accommodated data; and in each database, a value indicating a variation in the calculated traffic volume at each time is greater than a predetermined threshold. If large, the extreme value of the time variation of the traffic volume in each database A changing unit that changes the accommodating contributing data to other databases, characterized in that it comprises a.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to provide the highly efficient distributed DB system corresponding to the time variation of the population of the community to which a user belongs.

FIG. 1 is an explanatory diagram for explaining a processing target of the distribution apparatus according to the embodiment of the present invention. FIG. 2 is an explanatory diagram for explaining an outline of processing of the distribution apparatus of the present embodiment. FIG. 3 is an explanatory diagram for explaining an outline of the processing of the distribution apparatus of the present embodiment. FIG. 4 is an explanatory diagram for explaining an outline of the processing of the distribution apparatus of the present embodiment. FIG. 5 is a schematic diagram illustrating a schematic configuration of the dispersion apparatus according to the present embodiment. FIG. 6 is an explanatory diagram for describing the processing of the changing unit. FIG. 7 is a flowchart illustrating a distributed processing procedure according to the present embodiment. FIG. 8 is a diagram illustrating a computer that executes a distributed program.

  Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. The present invention is not limited by the embodiment. In the description of the drawings, the same portions are denoted by the same reference numerals.

[Processing Overview of Distributed Device]
First, a processing target of the distribution apparatus according to the present embodiment will be described with reference to FIG. In the present embodiment, the distribution apparatus stores data of a user who is a service subscriber such as a telephone service in a plurality of DBs in units of local communities such as prefectures or municipalities to which the user belongs. And a distributed DB system to be processed.

  In the distributed DB system 1 illustrated in FIG. 1, data belonging to a community A and a community B are contained in a DB # 1, and data belonging to a community C and a community D are contained in a DB # 2.

  Here, the processing outline of the distribution apparatus according to the present embodiment will be described with reference to FIGS. FIG. 2 is an explanatory diagram for explaining temporal fluctuation of the population of each community. Assuming that each community is a prefecture, as shown in FIG. 2A, there is a community whose daytime population and nighttime population are significantly different (see Non-Patent Document 1). One reason for this is that as shown in FIG. 2 (b), the population moves during the day from a bed town such as Nara to a city center such as Osaka. In this case, in the community of the bed town such as Nara, the daytime population is lower than the nighttime population. On the other hand, in urban communities such as Osaka, the daytime population exceeds the nighttime population.

  When such a population migration occurs, in the distributed DB system 1, the traffic amount to each DB changes over time. For example, in the distributed DB system 1 shown in FIG. 1, it is assumed that the population in the daytime is increasing in the communities A and B, and the population in the nighttime is increasing in the communities C and D. In this case, as illustrated in FIG. 3A, the traffic volume to DB # 1 that stores the data of the community A and the community B (data A and data B) increases as illustrated in FIG. On the other hand, as illustrated in FIG. 3B, the traffic volume to DB # 2 that stores the data of community C and community D (data C and data D) is high as illustrated in FIG. 3B.

  As described above, if the data of the community where the daytime population is increasing and the data of the community where the nighttime population is increasing are accommodated in the same DB, the traffic volume between the DBs varies depending on the time zone. Would. For example, in the case of the example shown in FIG. 3, the daytime traffic amount is largely biased toward DB # 1 as shown in FIG. 4 (a), and the nighttime traffic amount is as shown in FIG. 4 (b). Largely biased toward DB # 2. Then, the resources of each DB and the processing capacity of the entire distributed DB system cannot be used to the maximum. Therefore, the distribution apparatus of the present embodiment changes the DB in which the data of the community is accommodated so as to smooth the temporal fluctuation of the traffic volume of each DB by the distribution processing described later.

[Configuration of Distributed Device]
Next, a schematic configuration of the dispersion apparatus according to the present embodiment will be described with reference to FIG. As shown in FIG. 5, the distribution apparatus 10 according to the present embodiment is realized by a general-purpose computer such as a workstation or a personal computer, and includes an input unit 11, an output unit 12, a communication control unit 13, a storage unit 14, a control unit 15 is provided.

  The input unit 11 is realized using an input device such as a keyboard and a mouse, and inputs various kinds of instruction information to the control unit 15 in response to an input operation by an operator. The output unit 12 is realized by a display device such as a liquid crystal display, a printing device such as a printer, an information communication device, and the like, and outputs a result of a later-described distributed process to an operator.

  The communication control unit 13 is realized by a NIC (Network Interface Card) or the like, and controls communication between the control unit 15 and an external device such as a management server via an electric communication line such as a LAN (Local Area Network) or the Internet. .

  The storage unit 14 is realized by a semiconductor memory device such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. In the storage unit 14, a processing program for operating the distribution apparatus 10, data used during execution of the processing program, and the like are stored in advance, or temporarily stored for each processing. The storage unit 14 may be configured to communicate with the control unit 15 via the communication control unit 13.

  As illustrated in FIG. 3, the control unit 15 executes a processing program stored in the memory by an arithmetic processing device such as a CPU (Central Processing Unit), thereby forming a calculation unit 15a, a tallying unit 15b, and a changing unit 15c. Function.

  In a database system that stores data of a plurality of users in a plurality of databases in a unit of a community to which each user belongs, in a database system, the calculation unit 15a calculates the population of each community and the traffic volume per user at a plurality of predetermined time points. Using the average value, the traffic amount transmitted from each community at each time point is calculated.

  Specifically, the calculation unit 15a first obtains the population of each community at a plurality of predetermined time points via the input unit 11 or the communication control unit 13. For example, the calculation unit 15a acquires the population of each community at a plurality of predetermined time points such as 0:00 and 12:00 with reference to statistical data (see Non-Patent Document 1) such as a census.

  In addition, the calculation unit 15a acquires, via the input unit 11 or the communication control unit 13, the average value of the traffic volume per user at the same time as described above. For example, the calculation unit 15a acquires the traffic volume of the target service and the number of subscribers of the service, that is, the number of users at the same time as described above, from the system for monitoring the traffic volume of each service in the distributed DB system 1. Then, the calculation unit 15a divides the traffic volume of the service by the number of users to obtain an average value of the traffic volume per user at a plurality of predetermined time points.

  Next, the calculation unit 15a calculates the traffic volume transmitted from each community at each time point by multiplying the acquired population of each community at each time point by the average value of the traffic volume per user.

  The counting unit 15b counts, for each DB, the traffic volume transmitted at each time from the community corresponding to the data stored in each DB. For example, the tallying unit 15b calculates the sum of the traffic volume transmitted from the community A at each time and the traffic volume transmitted from the community B at each time, calculated by the calculation unit 15a, for DB # 1 shown in FIG. The value is calculated and set as the traffic volume to DB # 1 at each time. Similarly, the tallying unit 15b calculates the total value of the traffic volume transmitted from the community C at each time and the traffic volume transmitted from the community D for DB # 2, and calculates the traffic volume at each time to DB # 2. Amount.

  The change unit 15c determines, in each DB, a storage destination of data that contributes to the extreme value of the time variation of the traffic volume in each DB when the value indicating the aggregated traffic volume variation at each time point is larger than a predetermined threshold. Change to another DB. That is, when the value indicating the variation in the traffic volume at each time point is larger than the predetermined threshold, the changing unit 15c determines that the community with the maximum traffic volume at the time when the traffic volume is maximum in the DB, or that the traffic volume is minimal. At least one of the communities with the smallest traffic volume at a certain time is specified, and the data storage destination of the user belonging to the specified community is changed to another DB.

  Specifically, the changing unit 15c calculates, for example, a standard deviation, a value indicating the variation of the traffic volume at each point in time to each DB, that is, the variation of the time variation of the traffic volume, to each DB calculated by the tallying unit 15b. In addition, when the value indicating the calculated variation is larger than a predetermined threshold value, the change unit 15c instructs a change to another DB in which the data of the user stored in this DB is stored.

  Here, FIG. 6 is an explanatory diagram for explaining the processing of the changing unit 15c. FIG. 6 illustrates a time variation of the traffic amount to DB # 1 of the distributed DB system 1 illustrated in FIG. When the value indicating the variation of the time variation of the traffic amount to the DB is larger than a predetermined threshold, the changing unit 15c sets the circle in FIG. 6 to smooth the time variation of the traffic amount as shown by a straight line in FIG. Change the storage destination of data that contributes to the extreme value of the traffic volume enclosed by.

  That is, the change unit 15c specifies the data of the community having the largest traffic amount among the communities whose data is accommodated in this DB as the accommodation destination change target at the time when the traffic amount becomes maximum. Further, at the time when the traffic volume becomes minimum, the change unit 15c specifies, as the target of the accommodation destination change, the data of the community having the smallest traffic volume among the communities whose data is stored in this DB.

  Further, the change unit 15c selects, for example, a DB with the smallest traffic amount at the same time as the time when the traffic amount to the DB before the change becomes the maximum as the DB of the accommodation destination after the change. Similarly, the change unit 15c selects the DB having the largest traffic amount at the same time as the time when the traffic amount to the DB before the change is minimal as the accommodation destination DB after the change. Note that the change unit 15c may change both accommodation destinations of the data contributing to the local maximum value of the traffic amount and the data contributing to the local minimum value of the traffic amount, or may change one of the accommodation destinations. You may.

  Further, the changing unit 15c may change the storage destination of data that contributes to a plurality of extreme values in one process. In this case, the changing unit 15c may change the storage destination of the data of a plurality of communities corresponding to each extreme value. Alternatively, the changing unit 15c specifies, for example, a community in which the average value of the contribution rate of each traffic value to each extreme value at the same time as each extreme value is the largest, and sets the data of this community as a target of accommodation change. Is also good.

  The totaling unit 15b and the changing unit 15c repeatedly perform the above-described processing, so that the time variation of the traffic amount can be smoothed for all the DBs in the distributed DB system 1.

  In the distributed DB system 1, the first request from the user after the change to the data whose accommodation destination has been changed is responded by a route change by redirection. As a result, it is possible to suppress an increase in the processing load of the DB by increasing the inter-DB communication due to the change in the accommodation of the data.

[Distributed processing]
Next, the distribution processing of the distribution apparatus 10 will be described with reference to FIG. The flowchart in FIG. 7 is started, for example, at a timing when an operation input for instructing the start of the distributed processing is received.

  First, the calculation unit 15a calculates the traffic volume transmitted from each community at each time point using the population of each community at a plurality of predetermined time points and the average value of the traffic volume per user (step S1). Further, the tallying unit 15b counts, for each DB, the traffic amount transmitted at each time from the community corresponding to the data accommodated in each DB (Step S2).

  Next, the change unit 15c calculates, for each of the tabulated DBs, a value indicating the variation in the traffic volume at each point in time, that is, the value indicating the variation in the time variation of the traffic volume to each DB. It is determined whether or not the value is larger (step S3).

  When the value indicating the variation is larger than the predetermined threshold (Step S3, Yes), the change unit 15c changes the storage destination of the data that contributes to the extreme value of the time variation of the traffic amount of the DB to another DB. (Step S4). In other words, the change unit 15c specifies, in each DB, a community where the traffic volume is maximum when the traffic volume is maximum, or both or one of the communities where the traffic volume is minimum when the traffic volume is minimum, The storage destination of the data of the user belonging to the specified community is changed to another DB. After that, the changing unit 15c returns the process to step S2. Thereby, the processing of steps S2 to S4 is repeated.

  On the other hand, in the process of step S3, if the value indicating the variation is equal to or smaller than the predetermined threshold value for any of the DBs (step S3, No), the series of distributed processing ends.

  As described above, in the distributed apparatus 10 of the present embodiment, in the distributed DB system 1 in which the calculation unit 15a distributes and accommodates data of a plurality of users in a plurality of DBs in units of communities to which the users belong. The traffic amount transmitted from each community at each time point is calculated using the population of each community and the average value of the traffic amount per user at a plurality of predetermined time points. Further, the tallying unit 15b counts, for each DB, the traffic amount transmitted at each time from the community corresponding to the data stored in each DB. Further, the change unit 15c stores the data that contributes to the extreme value of the time variation of the traffic amount in each DB when the value indicating the aggregated traffic amount variation at each time point is larger than the predetermined threshold value in each DB. Change the destination to another DB.

  Thus, according to the distributed processing of the distributed apparatus 10 of the present embodiment, the temporal fluctuation of the traffic volume of each DB is smoothed in accordance with the temporal fluctuation of the population of the community in the area to which the subscriber belongs. Therefore, the load on each DB can be leveled, resources can be used effectively, and traffic that can be processed by the entire distributed DB system can be effectively processed. As described above, the distributed DB system accommodates the subscriber data so that processing can be performed with high efficiency in response to temporal fluctuations in the population of the community to which the user belongs, and processing delay and restrictions on the number of expandable DBs can be suppressed. it can.

[program]
It is also possible to create a program in which the processing executed by the distribution apparatus 10 according to the above embodiment is described in a language that can be executed by a computer. As one embodiment, the distribution apparatus 10 can be implemented by installing a distribution program that executes the above-described distribution processing on a desired computer as package software or online software. For example, by causing the information processing apparatus to execute the distribution program, the information processing apparatus can function as the distribution apparatus 10. The information processing device referred to here includes a desktop or notebook personal computer. In addition, the information processing apparatus includes a mobile communication terminal such as a smartphone, a mobile phone and a PHS (Personal Handyphone System), and a slate terminal such as a PDA (Personal Digital Assistants). Further, the terminal device used by the user may be a client, and may be implemented as a server device that provides the client with the services related to the above-described distributed processing. For example, the distributed apparatus 10 receives the population of each community at a plurality of predetermined times and the average value of the traffic volume per user as inputs, and executes a distributed processing service that outputs a community that changes the data storage destination and a storage destination DB. It is implemented as a server device to provide. In this case, the distribution apparatus 10 may be implemented as a Web server, or may be implemented as a cloud that provides services related to the above-described distributed processing by outsourcing. Hereinafter, an example of a computer that executes a distributed program that realizes the same function as the distributed device 10 will be described.

  As shown in FIG. 8, the computer 1000 that executes the distributed program includes, for example, a memory 1010, a CPU 1020, a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, a network interface 1070. These components are connected by a bus 1080.

  The memory 1010 includes a ROM (Read Only Memory) 1011 and a RAM 1012. The ROM 1011 stores, for example, a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to the hard disk drive 1031. The disk drive interface 1040 is connected to the disk drive 1041. For example, a removable storage medium such as a magnetic disk or an optical disk is inserted into the disk drive 1041. For example, a mouse 1051 and a keyboard 1052 are connected to the serial port interface 1050. The display 1061 is connected to the video adapter 1060, for example.

  Here, as shown in FIG. 8, the hard disk drive 1031 stores, for example, an OS 1091, an application program 1092, a program module 1093, and program data 1094. Each table described in the above embodiment is stored in, for example, the hard disk drive 1031 or the memory 1010.

  The distributed program is stored in the hard disk drive 1031 as, for example, a program module 1093 in which an instruction to be executed by the computer 1000 is described. Specifically, a program module 1093 in which each processing executed by the distribution apparatus 10 described in the above embodiment is described is stored in the hard disk drive 1031.

  Further, data used for information processing by the distributed program is stored, for example, in the hard disk drive 1031 as program data 1094. Then, the CPU 1020 reads the program module 1093 and the program data 1094 stored in the hard disk drive 1031 into the RAM 1012 as necessary, and executes the above-described procedures.

  The program module 1093 and the program data 1094 relating to the distributed program are not limited to being stored in the hard disk drive 1031. For example, the program module 1093 and the program data 1094 are stored in a removable storage medium and read out by the CPU 1020 via the disk drive 1041 or the like. May be done. Alternatively, the program module 1093 and the program data 1094 related to the distributed program are stored in another computer connected via a network such as a LAN (Local Area Network) or a WAN (Wide Area Network), and are stored in a network interface 1070. It may be read by the CPU 1020.

  As described above, the embodiment to which the invention made by the inventor is applied has been described. However, the present invention is not limited by the description and the drawings that constitute a part of the disclosure of the present invention according to the present embodiment. That is, other embodiments, examples, operation techniques, and the like performed by those skilled in the art based on this embodiment are all included in the scope of the present invention.

DESCRIPTION OF SYMBOLS 1 Distributed database (DB) system 10 Distributed device 11 Input part 12 Output part 13 Communication control part 14 Storage part 15 Control part 15a Calculation part 15b Total part 15c Change part

Claims (3)

In a database system in which data of a plurality of users is distributed and accommodated in a plurality of databases in units of a community to which each user belongs, a population of each community at a plurality of predetermined times and an average value of traffic volume per user are used. A calculating unit that calculates the amount of traffic transmitted from each community at each time;
A tally unit for tallying the traffic volume transmitted at each time from a community corresponding to data contained in each database,
In each of the databases, when a value indicating the aggregated traffic volume variation at each point in time is larger than a predetermined threshold value, the storage destination of data contributing to the extreme value of the time variation of the traffic volume in each database is changed to another database. A changing unit to change to
A dispersing device comprising:   The changing unit, when the value indicating the variation is larger than a predetermined threshold value, in the database, the community where the traffic volume is maximum when the traffic volume is maximum, or the traffic volume when the traffic volume is minimum in the database is the minimum. 2. The distributed apparatus according to claim 1, wherein both or any one of the communities is specified, and the accommodation destination of the data of the user belonging to the specified community is changed to another database. A distribution method performed by a distribution device,
In a database system in which data of a plurality of users is distributed and accommodated in a plurality of databases in units of a community to which each user belongs, a population of each community at a plurality of predetermined time points and an average value of traffic volume per user are used. Calculating the amount of traffic transmitted from each community at each point in time;
A tallying step of tallying the traffic volume transmitted at each time from a community corresponding to data accommodated in each database for each of the databases;
In each of the databases, when a value indicating the aggregated traffic volume variation at each point in time is larger than a predetermined threshold value, the storage destination of data contributing to the extreme value of the time variation of the traffic volume in each database is changed to another database. A change process to change to
A dispersing method comprising:

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