Abstract:
A computer, which is communicably connected to a plurality of computers having respective storage areas for storing data and in which second data that is replication of first data arranged in a storage area of own computer is arranged in storage areas of other computers, and the computer holds capacities of the storage areas of the respective computers and determines first data ranges for arranging the first data in the storage areas of the own computer and the plurality of other computers in accordance with the capacities, determines a second data range that is a largest data range or has a largest capacity, with, as a starting point, a data range that is different from a largest data range or a data range having a largest capacity in the first data ranges, and arranges the data in the storage areas of the respective computers.

Description:
TECHNICAL FIELD 
       [0001]    The present invention relates to a system in which data is distributed to and arranged in a plurality of computers and, in particular, to a system in which master data and replicated data are distributed and arranged. 
       BACKGROUND ART 
       [0002]    In recent years, a data amount has been explosively increased in a computer system for executing applications using Web, and there are known various systems for improving accessibility to data by distributing the data to a plurality of computers. For example, in an RDBMS (Relational DataBase Management System), there is known a method for improving accessibility of an entire system by partitioning data by predetermined ranges and arranging the partitioned data in a plurality of computers. 
         [0003]    As a system for use in a cache server or the like, a NoSQL (Not only SQL) database is known, such as KVS (Key Value Store) for arranging, in a plurality of computer systems, cache data having an identifier (key) of the data and a data value (value) in accordance with a predetermined distribution method. 
         [0004]    In the KVS, various configurations can be employed, such as a configuration for storing data in a volatile storage medium capable of accessing the data at a high speed, such as a main memory, a configuration for storing data in a nonvolatile recording medium having excellent persistence in storage of data, such as an SSD (Solid State Drive) and an HDD, and a configuration in which the both configurations described above are employed. 
         [0005]    In the configuration in which the both configurations are employed, balance between a memory store configured by unifying memories of a plurality of computers and a disk store including a nonvolatile storage medium of at least one computer can be variously changed depending on various operation policies such as a policy in which high-speed accessibility is regarded as important and a policy in which a storage performance is regarded as important. 
         [0006]    Data in which an identifier (key) of the data and a data value (value) are paired is stored in the memory store and the disk store. 
         [0007]    In the KVS, a cluster is configured by a plurality of servers, and parallel processing is achieved by distributing data to the servers and arranging the data in the servers. Specifically, data in each data management range (hereinafter, referred to as “data range”) managed by a corresponding server is stored in the server. Each server executes processing of the data (hereinafter, referred to as “master data”, and, hereinafter, a data range of the master data is referred to as “master data range”) included in the corresponding data range managed by the server. That is, in response to a reading request having a predetermined key, a server managing data in a data range having the key reads the data corresponding to the key. This makes it possible to improve performance of the parallel processing in the KVS by scale out. 
         [0008]    In the KVS, in order to secure reliability of data, there is known a configuration in which a server configuring a cluster stores replicated data (hereinafter, referred to as “replicated data”, and, hereinafter, a data range of the replicated data is referred to as “replicated data range”) of data managed by another server. That is, each server is not only a master for managing data included in a predetermined data range but also a slave for holding replicated data of data managed by another server. With this, even in a case where failure occurs in a server, another server holding, as replicated data, data managed by this failed server as a master can continue processing. Thus, failure resistance can be secured. 
         [0009]    PTL 1 discloses, as a method of holding master data in servers in the KVS described above, a technique in which increase in a load onto a single server is prevented by partitioning a master data range of a certain server and causing an adjacent server to hold the partitioned master data. 
       CITATION LIST 
     Patent Literature 
       [0010]    PTL 1: JP-A-2012-48424 
       SUMMARY OF INVENTION 
     Technical Problems 
       [0011]    However, in the technique described in PTL 1, there is no description regarding determination of data ranges of master data and replicated data to efficiently use memory capacities of the servers. For example, in a case where replicated data of master data having a large data amount in a server is held by a server having a small free memory capacity, page-out occurs, and it is necessary to access data stored in a disk. Therefore, speed performance for accessing the data is reduced. On the contrary, in a case where replicated data of master data having a small data amount in a server is held by a server having a large free memory capacity, an unused memory area is increased and a utilization ratio of a memory is reduced. Further, in a case where data amounts to be stored in the servers are changed in accordance with a usage situation of the servers, memories cannot be efficiently used in accordance with such change in the data amounts. 
       Solution to Problems 
       [0012]    A representative embodiment of the invention is a computer, which is communicably connected to a plurality of computers having respective storage areas for storing data and in which second data that is replication of first data arranged in a storage area of own computer is arranged in storage areas of other computers, the computer holding capacities of the storage areas of the respective computers and determining first data ranges for arranging the first data in the storage areas of the own computer and the plurality of other computers in accordance with the capacities, arranging the second data in the storage areas of the own computer and the other computers by determining a second data range that is a largest data range or has a largest capacity, with, as a starting point, a data range that is different from a largest data range or a data range having a largest capacity in the first data ranges, and arranging the data in the storage areas of the respective computers in accordance with the first data ranges and the second data ranges. 
       ADVANTAGEOUS EFFECTS OF INVENTION 
       [0013]    According to the invention, it is possible to improve speed performance and a memory utilization ratio of a system while maintaining failure resistance. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0014]    [ FIG. 1 ]  FIG. 1  is a view illustrating a relationship between computers and corresponding data ranges managed by the respective computers as a precursor technique of a computer system to which the invention of the present application is applied. 
           [0015]    [ FIG. 2 ]  FIG. 2  is a view illustrating outline of processing of a computer system of an embodiment to which the invention of the present application is applied. 
           [0016]    [ FIG. 3 ]  FIG. 3  is a view illustrating an entire configuration of a computer system in a computer system of this embodiment. 
           [0017]    [ FIG. 4A ]  FIG. 4A  is a view showing an example of configuration information in a computer system of this embodiment. 
           [0018]    [ FIG. 4B ]  FIG. 4B  is a view showing an example of configuration information in a case where data is managed on a block basis in a computer system of this embodiment. 
           [0019]    [ FIG. 4C ]  FIG. 4C  is a view showing an example of server load information in a computer system of this embodiment. 
           [0020]    [ FIG. 5 ]  FIG. 5  is a flowchart showing a flow of data range determination processing executed by a data range management unit in a computer system of this embodiment. 
           [0021]    [ FIG. 6A ]  FIG. 6A  is a flowchart showing a flow of data range determination processing based on data positions, which is executed by a machine information management unit in a computer system of this embodiment. 
           [0022]    [ FIG. 6B ]  FIG. 6B  is a view showing an example where data range determination processing based on data positions is executed in a computer system of this embodiment and data ranges of replicated data are determined. 
           [0023]    [ FIG. 7 ]  FIG. 7  is a flowchart showing a flow of data range determination processing based on blocks, which is executed by a machine information management unit in a computer system of this embodiment. 
           [0024]    [ FIG. 8A ]  FIG. 8A  is a view showing an example where data range determination processing based on blocks is executed in a computer system of this embodiment and data ranges of replicated data are determined. 
           [0025]    [ FIG. 8B ]  FIG. 8B  is a view showing an example of configuration information of master data and replicated data corresponding to  FIG. 8A  in a computer system of this embodiment. 
           [0026]    [ FIG. 9 ]  FIG. 9  is a flowchart showing data block determination processing using distribution information as input, which is executed by a machine information management unit in a computer system of this embodiment. 
           [0027]    [ FIG. 10A ]  FIG. 10A  is a view illustrating an example of block determination using distribution information as input in a computer system of this embodiment. 
           [0028]    [ FIG. 10B ]  FIG. 10B  is a view showing an example of configuration information of block Ins corresponding to  FIG. 10A  in a computer system of this embodiment. 
           [0029]    [ FIG. 11 ]  FIG. 11  is a flowchart of block determination processing using density information as input, which is performed by a machine information management unit in a computer system of this embodiment. 
           [0030]    [ FIG. 12 ]  FIG. 12  is an image of data block determination processing using density information as input in a computer system of this embodiment. 
           [0031]    [ FIG. 13 ]  FIG. 13  is a view illustrating a display example of a user operation screen in a computer system of this embodiment. 
           [0032]    [ FIG. 14 ]  FIG. 14  is a view illustrating a display example of a user setting screen in a computer system of this embodiment. 
       
    
    
     DESCRIPTION OF EMBODIMENTS 
       [0033]      FIG. 1  is a view illustrating a relationship between computers and corresponding data ranges managed by the respective computers in a computer system that is an embodiment to which the invention is applied. 
         [0034]    For example,  FIG. 1  shows that, in a system including computers A to E, the computer B manages data in “400 to 700” as a master data range and manages data in “1401 to 1500” and “1 to 200” as replicated data ranges. As a method of distributing data to the computers, various methods, such as a Consistent Hashing method, a Range method, and a List method, are used. 
         [0035]      FIG. 2  is a view simply illustrating outline of processing in an embodiment to which the invention is applied. In S 101 , master data ranges of respective servers are determined from a total data range. The master data ranges are determined based on memory capacity ratios of the servers. 
         [0036]    In S 102 , a largest data range (hereinafter, referred to as “largest data range”) is specified among the master data ranges held by the respective servers. 
         [0037]    In S 103 , replicated data ranges held by the respective servers are determined based on the largest data range. In an embodiment to which the invention is applied, the replicated data ranges are determined based on data positions or data amounts. 
         [0038]      FIG. 3  illustrates an entire configuration of a computer system that is an embodiment to which the invention is applied. 
         [0039]    The computer system includes a plurality of servers  301 , client devices  302 , and networks  303 . The servers  301  are connected to one another and the servers  301  and the client devices  302  are connected to one another via the network  303 . 
         [0040]    As the network  303 , various wired and wireless configurations can be employed, such as a LAN, a WAN, and a SAN. In this embodiment, the network  303  may be any network as long as the network  303  can cause the servers  301  and the client devices  302  to communicate. Note that the network  303  includes a plurality of network devices. The network devices include, for example, a switch and a gateway. 
         [0041]    The server  301  includes a processor  304 , a main storage  305 , and a secondary storage  306 , and is a computer configuring KVS. Although not illustrated in this embodiment, the server  301  includes a network interface to be connected to the network  303 . The server  301  executes reading processing and writing processing of data in response to a request from the client device  302  and returns results of the processing to a client. Note that all the servers  301  have the same configuration. 
         [0042]    The processor  304  executes a program stored in the main storage  305 . By executing the program, the processor  304  can realize a function that the server  301  has. 
         [0043]    The main storage  305  stores a program to be executed by the processor  304  and information needed to execute the program. 
         [0044]    In the main storage  305  of the this embodiment, programs for realizing a data management unit  307 , a distribution control unit  308 , a data range management unit  310 , a configuration information holding unit  311 , a machine information management unit  312 , and a statistical information management unit  313  are stored. In the main storage  305 , configuration information  314  and server load information  315  are further held. 
         [0045]    A data store  316  that is a database configuring the KVS is further stored in the main storage  305 . In the data store  316 , data in which a key and a value are paired is stored. 
         [0046]    The data management unit  307  controls various kinds of processing of data managed by the server  301 . The data management unit  307  receives a request from the client device  302  and, in response to the request, controls processing such as reading and writing of data. 
         [0047]    The distribution control unit  308  controls change in various setting items such as data multiplicity, the number of blocks of data, a memory threshold, and a determination method of data blocks. Such control is performed on a user setting screen illustrated in, for example,  FIG. 14 . 
         [0048]    The data range management unit  310  manages storage locations of master data and replicated data to be stored in each server. The configuration information holding unit  311  manages the configuration information  314 . The machine information management unit  312  executes data range determination processing of the replicated data. The statistical information management unit  313  acquires information on a load of each server  301  and renews the server load information  315  on the basis of the acquired information. 
         [0049]    The client devices  302  transmit processing requests to the servers via the network. Note that a management terminal  309  is connected to the client devices  302  and a processing request is transmitted from the management terminal  309  in some cases. 
         [0050]    A processor  317  executes a program stored in a main storage  318 . In the main storage  318 , the data management unit  307 , the distribution control unit  308 , the data range management unit  310 , the configuration information management unit  311 , the machine information management unit  312 , and the statistical information management unit  313  are configured by cooperating a CPU and the programs. Hereinafter, in a case where processing is explained by using “program” as a subject, it is indicated that the program is executed by the processor  317 . 
         [0051]      FIG. 4  is schematic diagrams showing an example of the configuration information  314  and the server load information  315  managed as tables in the computer system. The configuration information  314  stores information on data ranges managed by the respective servers. Each of the servers may store the configuration information  314  illustrated in  FIG. 4A  and  FIG. 4B  or may store the configuration information  314  illustrated in any one of  FIG. 4A  and  FIG. 4B . 
         [0052]    The configuration information  314  of  FIG. 4A  has a server ID  401 , a master data range  402 , and a replicated data range  403 . 
         [0053]    The server ID  401  stores identifiers for uniquely identifying the servers. In the master data range  402 , values indicating data ranges of the master data of the respective servers are stored. In the replicated data range  403 , values indicating data ranges of the replicated data of the respective servers are stored. 
         [0054]    The configuration information  314  of  FIG. 4B  is configuration information used in a case where data is managed as a single data set (hereinafter, referred to as “block”) by combining a plurality of pieces of data. The configuration information  314  of  FIG. 4B  has a server ID  410 , a block ID  411  of the master data, a data range  412  corresponding to the block ID  411 , and a block ID  413  of the replicated data. 
         [0055]    The server ID  410  and the data range  412  of the master data and the replicated data are similar to those of  FIG. 4B . The block IDs  411  and  413  are identifiers for managing a plurality of pieces of data in combination. For example, it is indicated that data having the block ID  411  of “1” is configured by data “1 to 150” in the master data range  412 . 
         [0056]    The server load information  315  of  FIG. 4C  is a view showing an example of load information of the servers configuring the system. The server load information  315  has a server ID  420 , a memory size  423 , and a data size  425 . The server load information  315  may further have information such as a CPU utilization rate and a network utilization rate of each server. 
         [0057]    The server ID  420  stores identifiers for uniquely identifying the servers. The memory size  423  indicates memory capacities that the respective servers have. 
         [0058]    The data size  425  indicates data amounts stored in the respective servers. 
         [0059]      FIG. 5  is a flow showing entire processing of replicated data range determination. Note that the master data ranges have been determined in advance on the basis of the memory capacity ratios of the servers. In this embodiment, as a method of the data range determination processing, there are data range determination processing based on data and data range determination processing based on blocks. 
         [0060]    In S 501 , the data range management unit determines whether or not the load information of the servers is stored. In a case where the load information of the servers is stored (S 501 : Yes), the processing proceeds to S 503 . In a case where the load information of the servers is not stored (S 501 : No), the processing proceeds to S 507 . By determining whether or not the load information of the servers is stored, whether the system is before operation or is being operated is grasped. 
         [0061]    In S 503 , the data range management unit determines whether or not estimation of the data amounts to be processed in the respective servers is set. In a case where the estimation of the data amounts is set (S 503 : Yes), the processing proceeds to S 507 . In a case where the estimation of the data amounts is not set (S 503 : No), the processing proceeds to S 505 . The estimation of the data amounts means estimated values of the data amounts to be stored in the system. 
         [0062]    In S 505 , the data range management unit executes data range determination processing based on data positions. Data range determination processing based on data ranges will be described in detail with reference to  FIG. 6 . 
         [0063]    In S 507 , the data range management unit executes block determination processing. In this embodiment, as the block determination processing, block determination processing using distribution information as input or block determination processing using density information as input is performed. The block determination processing will be described in detail with reference to  FIG. 9  and  FIG. 11 . 
         [0064]    In S 509 , the data range management unit executes the data range determination processing based on the blocks. The data range determination processing based on the blocks will be described in detail with reference to  FIG. 7 . 
         [0065]    In S 511 , the data range management unit shares configuration information of all machines in the system. 
         [0066]    The data range determination processing based on the data can optimize the system also in a case where a data amount existing in a predetermined data position is indefinite, and therefore the data range determination processing based on the data is suitable mainly in a case where the data amounts to be stored in the servers are unpredictable, for example, before the system is operated. The data range determination processing based on the blocks can optimize the system in real time in accordance with the server load information  315 , and therefore the data range determination processing based on the blocks is suitable mainly in a case where the data amount can be estimated during operation of the system. 
         [0067]      FIG. 6  is views showing the data range determination processing based on the data positions.  FIG. 6A  shows a flow of the data range determination processing based on the data positions (S 505  in  FIG. 5 ). 
         [0068]    In S 601 , the machine information management unit  312  calculates a memory amount ratio of each server. The memory amount ratio is a ratio of a memory capacity of own server to the memory capacities of all the servers. 
         [0069]    In S 603 , the machine information management unit  312  determines whether or not a server having a memory amount ratio exceeding 1/multiplicity N exists. The multiplicity N is an index indicating how many pieces of the replicated data to be held in the system in order to improve the reliability and the failure resistance of the data. By limiting the memory amount ratio to 1/multiplicity N, it is possible to achieve multiplexing without overlapping, in the same server, data ranges of the master data and the replicated data of the master even in a case where a difference in memory performance between the servers is large. 
         [0070]    In a case where the server having the memory amount ratio exceeding 1/multiplicity N exists (S 603 : Yes), the memory amount is corrected in S 605  so that the memory amount ratio becomes 1/N or less. This correction of the memory amount is performed in such a manner that the machine information management unit  312  changes the ratio of the server having the memory amount ratio exceeding 1/multiplicity N to 1/multiplicity N and allots data of an insufficient memory amount to another server. In a case where the server having the memory amount ratio exceeding 1/multiplicity N does not exist (S 603 : No), the processing proceeds to S 606 . 
         [0071]    In S 606 , the data range management unit  312  determines the master data range of each server in accordance with the memory amount ratio. 
         [0072]    In S 607 , the data range management unit  312  specifies a largest data range and a server ID having the largest data range among all the servers by referring to a master data range  612  of the configuration information  314 . 
         [0073]    In S 609 , the data range management unit allots leading data in the largest data range, as leading data in a replicated data range, to a server having a server ID subsequent to the server ID having the largest data range. 
         [0074]    For example, as illustrated in  FIG. 6B , among the data ranges of the master data stored in the servers A to E, a data width “500” in a master data range “701 to 1200” is specified as the largest data range in the master data range  612 . A server ID  610  having the largest data range is specified as “C”. Then, master data “701” that is leading data in the largest data range is allotted, as the leading data in the replicated data range, to a server ID “D” that is a server ID subsequent to the server ID “C” having the largest data range. Note that, in this embodiment, the server IDs are managed in descending order, but may be managed in ascending order. 
         [0075]      FIG. 7  shows a flow of the data range determination processing based on the blocks. 
         [0076]    In S 701 , the machine information management unit  312  calculates the memory amount ratio of each server. The memory amount ratio is a ratio of a memory capacity of the own server to the memory capacities of all the servers. 
         [0077]    In S 703 , the machine information management unit  312  determines whether or not a server having a memory amount ratio exceeding 1/multiplicity N exists. In a case where the server having the memory amount ratio exceeding 1/multiplicity N exists (S 703 : Yes), the machine information management unit  312  corrects the memory amount in S 705  so that the memory amount ratio is 1/multiplicity N or less. This correction of the memory amount is achieved by allotting data so that the ratio of the server having the memory amount ratio exceeding 1/multiplicity N is changed in the same way as the data range determination processing based on the data positions. In a case where the server having the memory amount ratio exceeding 1/multiplicity N does not exist (S 703 : No), the processing proceeds to S 707 . 
         [0078]    In S 707 , the data range management unit allots blocks to each server in accordance with the memory amount ratio, thereby determining the master data range. Note that the block determination processing will be described in detail with reference to  FIG. 9  (block determination method using distribution information as input) and  FIG. 11  (block determination method using density information as input). 
         [0079]    In S 709 , the data range management unit  312  specifies a server having a largest data capacity among all the servers in the system and specifies the number of blocks (hereinafter, referred to as “largest block number”) held by the server. 
         [0080]    In S 711 , the data range management unit  312  shifts the master data range of each server by the largest block number. 
         [0081]    In S 713 , the data range management unit  312  calculates a data range of allotted blocks. In the data range, an initial point of an allotted leading block serves as a starting point in the data range, and a terminal point of a last block serves as an end point in the data range. 
         [0082]      FIG. 8  shows a relationship between data storage locations that have been subjected to the data range determination processing based on the blocks and stored data.  FIG. 8A  shows a view in which the replicated data ranges are determined by the data range determination processing based on the blocks. In this embodiment, the master data ranges are determined by determining blocks having the same data amount in a total data range and allotting a plurality of blocks to each server in accordance with the memory amount ratio (S 707  in  FIG. 7 ). 
         [0083]    For example, it is shown that data of the block IDs 8 to 12 is stored as master data in the server C of  FIG. 8A . Then, the server C having the largest data capacity is specified among all the servers, and the largest block number held by the server C is specified to “5” (S 709  of  FIG. 7 ). Thereafter, the number of blocks of the replicated data ranges is shifted by “5” blocks that are the largest block number from the master data ranges of the respective servers. In the server C, data of the block IDs 3 to 7 is stored as the replicated data. In the same procedure, data ranges of replicated data 2 are determined, thereby achieving the multiplexing.  FIG. 8B  shows the configuration information  314  of the master data and the replicated data retained by the servers corresponding to  FIG. 8A . Hereinafter, the block determination method will be described. 
         [0084]      FIG. 9  is a flow showing the data block determination processing using the distribution information as input. 
         [0085]    In S 901 , the machine information management unit  312  calculates an accumulated value of data amounts in the system on the basis of the server load information  315 . 
         [0086]    In S 903 , the machine information management unit  312  calculates, on the basis of the calculated accumulated value of the data amounts, data positions for equally dividing the data amounts by the number of blocks X designated by a user. Note that the number of blocks of the data can be arbitrarily set by a user. 
         [0087]    In S 905 , the machine information management unit  312  determines a data range for each block. 
         [0088]      FIG. 10  is images of the block determination processing using the distribution information as input. 
         [0089]    As illustrated in  FIG. 10A , a relationship between the data positions and the data amounts is shown by a bar graph, and the accumulated value of the data amounts in the system is shown by a line graph.  FIG. 10A  illustrates a state in which the blocks are determined by dividing the accumulated value of the data into 15 equal parts in order to generate “15” data blocks having the same data amount. 
         [0090]      FIG. 10B  is a table showing correspondence between the blocks shown in  FIG. 10A  and data ranges. 
         [0091]    As described above, in the block determination processing using the distribution information as input, the blocks are determined based on the accumulated value of the data amounts in the system, and therefore this block determination method is particularly effective in a case where actual data amounts in the system can be grasped or in a case where the data amounts can be estimated. 
         [0092]      FIG. 11  shows a flow of the block determination processing using the density information as input.  FIG. 12  shows an image of the data block determination processing using the density information as input. 
         [0093]    In S 1101 , the machine information management unit calculates data densities p of all the servers. The data density p is obtained by calculating “master data amount of each server/master data range of each server”. The density p of the server A in  FIG. 12  is 1 GB/400. 
         [0094]    In S 1103 , the machine information management unit  312  calculates a total value of a total data amount of the servers existing in the system. In the system illustrated in  FIG. 12 , the total data amount stored in the servers A to E are now 1 GB+1 GB+1.5 GB+0.5 GB+0.5 GB=4.5 GB. 
         [0095]    In S 1103 , the machine information management unit  312  calculates a data amount for each block. The number of blocks of data can be arbitrarily set by a user. In a case where the data is partitioned into “15” blocks in the system of  FIG. 12 , a data amount for each section is 0.3 GB by calculating the total data amount 4.5 GB/15 blocks. 
         [0096]    In S 1105 , the machine information management unit  312  determines a data range for each block. The data range is calculated on the basis of the data density p of each server and the data amount for each block. For example, in a case where the data density p of the server A is 1 GB/400 and the data amount for each block is 0.3 GB, the data range is “0.3 GB/(1 GB/400)=120”. 
         [0097]    In S 1107 , the machine information management unit  312  determines a data range width of each server. 
         [0098]    The data block determination processing in which the data density information is used is particularly suitable in a case where data is equally arranged in the servers and a data amount for each piece of data is substantially the same. 
         [0099]      FIG. 13  is an explanatory view illustrating a display example of a user operation screen in this embodiment. The user operation screen includes a table showing the server load information in the system and a schematic diagram showing the data managed by the servers as the master data or the replicated data. 
         [0100]    In the table showing a server load state, the memory capacities and the data amounts of the respective servers in the system are included. 
         [0101]    In a case where the replicated data ranges are determined based on the data positions, the data schematic diagram shows the data ranges as in (A). In a case where the replicated data ranges are determined based on the data blocks, locations of the master data and the replicated data of each server are shown on a data block basis as in (B). 
         [0102]      FIG. 14  is an explanatory view illustrating a display example of a user setting screen of this embodiment. The user setting screen has data multiplicity, the number of blocks of data, a memory threshold, a determination method of data blocks and the partitioned data number. 
         [0103]    In the data multiplicity, multiplicity of holding the data in the system is set The number of blocks of the data is for designating the number of blocks in a case where the data range determination processing of the replicated data is performed based on the blocks. 
         [0104]    The memory threshold is an index for performing rebalance of the data in accordance with memory loads of the servers during operation of the system. 
         [0105]    In this embodiment, it is possible to select, as the block determination method, at least the block determination method using the distribution information of data as input or the block determination method using the density information of data as input. 
         [0106]    As described above, according to an embodiment of the invention, the replicated data ranges can be determined based on the master data ranges in accordance with the load state of the servers. Therefore, even in a case where a cluster includes servers having different performance, it is possible to prevent a server having low performance from being a bottleneck of the system. 
         [0107]    Because it is possible to achieve the multiplexing without overlapping the master data ranges and the replicated data ranges, the reliability of the system can be secured. 
         [0108]    By determining the blocks of the data using the distribution information and the density information of the system as input, the replicated data range can be determined in accordance with the load state of the servers. This makes it possible to efficiently use memories. 
         [0109]    Note that various kinds of software exemplified in this embodiment can be stored in various (non-transitory) recording media, such as electromagnetic, electronic, and optical media, and can be downloaded to a computer via a communication network such as Internet. 
         [0110]    In this embodiment, an example where control is performed by software has been described. However, a part thereof can be also realized by hardware. 
         [0111]    In the above description, although the computer system has been described in detail with reference to the drawings, the invention is not limited to various examples described above, and, as a matter of course, the various modifications can be made within the scope of the invention. 
       REFERENCE SIGNS LIST 
       [0000]    
       
           301  server 
           302  client device 
           303  network 
           304 ,  317  processor 
           305 ,  318  main storage 
           306 ,  319  secondary storage 
           307  data management unit 
           308  distribution control unit 
           309  management terminal 
           310  data range management unit 
           311  configuration information holding unit 
           312  machine information management unit 
           313  statistical information management unit 
           314  configuration information 
           315  server load information 
           316  data store