JP2005309684A - Database system and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve the efficiency of parallel distributed processing in a database system in a cluster environment. <P>SOLUTION: A control node 100 generates a common execution instruction instructing execution of arithmetic processing in execution nodes 200, and generates a transfer instruction instructing transfer of data used for the arithmetic processing. The control node 100 generates instruction information by mutually connecting the generated execution instruction and transfer instruction, and simultaneously delivers it to a plurality of execution nodes 200 through a communication network 10. The execution nodes 200 which received the instruction information perform transmitting and receiving of data with other execution nodes 200 through the communication network 10 based on the received transfer instruction to acquire data necessary for processing. The execution nodes 200 execute the arithmetic processing by use of the data accumulated therein and the data received from the other execution nodes 200 based on the received execution instruction. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a database system and a program, and more particularly to a database system and a program suitable for parallel distributed processing.

  In a parallel database system (Shared Nothing Type) in which data (for example, table data) is distributed to multiple computers (nodes) without using a shared disk, data between tables existing on different nodes is required. As a method for executing the processing (mainly join operation processing), for example, a method of distributing each node by hashing each table is known (for example, Non-Patent Document 1).

  For example, when performing a join operation on a table (distributed table) distributed on all nodes and a table (specific table) that exists only on a specific node, the above method joins based on the join conditions of the join operation. A key is generated, and the table is rearranged by hashing the target table with each join key. That is, the distributed table and the specific table are rearranged at each node. Since the distributed table and the specific table are rearranged at each node, a join operation for joining them can be executed at each node.

In this method, since each table to be calculated is hashed and rearranged, if the number of tables to be processed is large, the amount of processing becomes enormous and the processing efficiency decreases. Moreover, the communication load between nodes is also large.
Kazuo Goda and two others, “High-speed information retrieval using parallel database kernel DBKernel: Experiments with TREC data”, IEICE, 12th Data Engineering Workshop DEWS2001, March 9, 2001

  The present invention has been made in view of the above circumstances, and an object thereof is to provide a database system that has a low processing load and can execute processing at high speed.

In order to achieve the above object, a database system according to the first aspect of the present invention provides:
In a database system that performs parallel distributed processing on multiple nodes,
The plurality of nodes are composed of a central node that controls the parallel distributed processing and a plurality of execution nodes that perform data accumulation and arithmetic processing, which are interconnected via a communication network.
The supervising node is
Execution instruction generation means for generating a common execution instruction for instructing execution of arithmetic processing in each execution node;
Transfer instruction generation means for generating a transfer instruction for instructing transfer of data used in the arithmetic processing instructed by the execution instruction;
Instruction distribution means for broadcasting the instruction information obtained by combining the execution instruction generated by the execution instruction generation means and the transfer instruction generated by the transfer instruction generation means to the plurality of execution nodes via the communication network; ,
With
The execution node is
Command receiving means for receiving command information distributed from the command distributing means of the supervising node via the communication network;
Data transfer means for transmitting and receiving data to and from other execution nodes via the communication network based on the transfer command received by the command receiving means;
Based on the execution command received by the command receiving means, arithmetic means for performing arithmetic processing using the stored data and the data received by the data transfer means;
It is characterized by providing.

In the above database system,
It is desirable that the transfer command generation unit generates a transfer command specifying an execution node that should transmit data and an execution node that should receive data.

In the above database system,
The supervising node is
It is desirable to further include arrangement information acquisition means for acquiring and storing arrangement information indicating which data is stored in which execution node.
The transfer command generation unit can generate the transfer command based on the arrangement information stored in the arrangement information acquisition unit.

In the above database system,
The instruction distribution means distributes the instruction information of a tree structure in which the execution instruction generated by the execution instruction generation means and the transfer instruction generated by the transfer instruction generation means are combined to the plurality of execution nodes,
The arithmetic means preferably executes arithmetic processing indicated by an execution instruction included in the instruction information by recursively executing the instruction information of the tree structure received by the instruction receiving means.

In order to achieve the above object, a program according to the second aspect of the present invention is:
To the computer that supervises the database system that performs parallel and distributed processing,
Obtaining and storing arrangement information indicating which data is stored in which of the plurality of computers constituting the database system;
Generating an execution instruction including information indicating contents of arithmetic processing to be executed by each of the plurality of computers, and information specifying data used in the arithmetic processing;
Generating, based on the arrangement information, a transfer instruction including information indicating a computer that should transmit data to another computer and information indicating a computer that should receive data from the other computer;
Broadcasting instruction information obtained by combining the generated execution instruction and transfer instruction to the plurality of computers via a communication network;
Is executed.

In order to achieve the above object, a program according to the third aspect of the present invention is:
In the computer that constitutes the database system that performs parallel and distributed processing,
Storing data used for arithmetic processing;
Receiving an execution instruction and a transfer instruction distributed from a computer controlling the database system via a communication network;
Transmitting and receiving data to and from another computer via the communication network based on the received transfer command;
A step of performing arithmetic processing using the stored data and data received from another computer based on the received execution instruction;
Is executed.

  According to the present invention, in a database system that performs parallel and distributed processing, processing is executed by distributing one command information including a command for instructing processing to be executed and a command for instructing transfer of data necessary for processing. Therefore, the load on each node and communication network can be reduced, and the processing efficiency of the entire database system can be improved.

(First embodiment)
Embodiments according to the present invention will be described below with reference to the drawings.

  FIG. 1 is a diagram schematically illustrating a configuration of a database system 1 according to the present embodiment. The database system 1 according to the present embodiment includes a plurality of information processing apparatuses (for example, workstations and personal computers), that is, “nodes”. As shown in FIG. 1, a plurality of nodes constituting the database system 1 is composed of a central node 100 and a plurality of execution nodes 200, and each node is interconnected via a predetermined communication network 10. Yes.

  Here, the database system 1 according to the present embodiment is a parallel distributed database in a so-called cluster environment in which data is distributed and arranged in a plurality of nodes (execution nodes 200), and predetermined execution is executed in each execution node 200. . The supervising node 100 supervises such parallel and distributed processing, and functions as a DBMS (DataBase Management System) that manages a database composed of a plurality of execution nodes 200.

  The communication network 10 is a communication medium based on a communication standard such as IEEE802.3, for example, and mediates data transmission / reception between nodes based on a communication protocol such as TCP / IP (Transmission Control Protocol / Internet Protocol). .

  The configurations of the central node 100 and the execution node 200 will be described below with reference to the drawings.

  The supervising node 100 is a node (coordinator node) that supervises parallel and distributed processing in the database system 1, and has a configuration as shown in FIG. As shown in the figure, the central node 100 includes a control unit 110, a communication control unit 120, an input control unit 130, an output control unit 140, a program storage unit 150, and a storage unit 160.

  The control unit 110 includes, for example, a CPU (Central Processing Unit) and a predetermined storage device (RAM (Random Access Memory)) serving as a work area, and controls each unit of the overall node 100. Each process described later is executed based on a predetermined operation program stored in the program storage unit 150.

  The communication control unit 120 is composed of a predetermined communication device such as a NIC (Network Interface Card), for example, and connects the central node 100 and the communication network 10 to communicate with the execution node 200.

  For example, the input control unit 130 connects a predetermined input device 13 such as a keyboard or a pointing device, and transmits an instruction or the like input from the input device 13 to the control unit 110.

  For example, the output control unit 140 connects a predetermined output device 14 such as a display device or a printer, and outputs the processing result of the control unit 110 to the output device 14 as necessary.

The program storage unit 150 is configured from a predetermined storage device such as a hard disk device or a ROM (Read Only Memory), and stores various operation programs executed by the control unit 110. The operation program stored in the program storage unit 150 is used to implement each process described later in cooperation with the OS, in addition to an arbitrary OS (Operating System: basic software) that controls the basic operation of the overall node 100. It is assumed that the following operation program is stored. Processing performed by the central node 100 described later is realized by the control unit 110 executing these operation programs.
(P1-1) “Communication control program”: a program for controlling the communication control unit 120 to communicate with the execution node 200 via the communication network 10 (P1-2) “DBMS program”: in each execution node 200 A program for instructing input / output, etc., and for managing and managing parallel distributed processing in the database system 1 (P1-3): “instruction generation program”: Instructing operations at each execution node 200 when executing parallel distributed processing That generates instructions to execute

When the control unit 110 of the supervising node 100 executes the above program, the supervising node 100 realizes the following functions.
(F1-1) “Execution instruction generation function”: common to specify the content of parallel processing executed in each execution node 200 and data used in the processing based on a query input from the input control unit 130 or the like Function for generating an execution instruction (F1-2) “transfer instruction generation function”: a transfer instruction that specifies from which execution node 200 to which execution node 200 data to be used for processing specified by the execution instruction should be transferred (F1-3) “command distribution function”: a function for combining an execution command and a transfer command and broadcasting (broadcasting) from the communication control unit 120 to the execution node 200 via the communication network 10

  In the present embodiment, the control unit 110 executes the program stored in the program storage unit 150 to realize the above functions by so-called software processing. However, a circuit specialized for these functions (so-called ASIC ( The above function may be realized by so-called hardware processing by configuring the application specific integrated circuit)) in the integrated node 100.

  The storage unit 160 includes a predetermined storage device such as a RAM or a hard disk device, and stores information distributed to each execution node 200, information received from the execution node 200, and other data used for processing. The “data arrangement information” as shown in FIG. 3A indicating whether the execution node 200 is arranged is stored.

  As shown in the figure, the “data arrangement information” is stored in the execution node 200 of the node ID in a record using “node ID” as a key for specifying a plurality of execution nodes 200 constituting the database system 1. A “data ID” for specifying the current data is recorded. The “node ID” is unique identification information assigned to each execution node 200 such as an IP address. The “data ID” is identification information uniquely assigned to each of a plurality of data stored in the entire database system 1.

  Such data arrangement information is automatically acquired by, for example, being input from an operator via the input control unit 130 or by the supervising node 100 inquiring each execution node 200 via the communication network 10. May be accumulated. Further, in the case where the supervising node 100 divides data and places it in each execution node 200, the supervising node 100 may generate and store data placement information at that time.

  In addition, an “instruction management table” as shown in FIG. 3B is created in the storage unit 160 for managing instructions sent to the execution node 200. As shown in the figure, in the “instruction management table”, a record is created with an instruction ID that is uniquely assigned to each input instruction (such as a query) instructing execution of parallel distributed processing using the database system 1 as a key, In each record, items such as “input command”, “target data”, “target node”, “transfer command”, “execution command”, “distribution command”, and “distribution destination node” are prepared.

  In the item “input command”, information indicating a command input to the overall node 100 is recorded. In the item “target data”, information (identification information) for specifying data used for the processing instructed by the command is recorded. In the item “target node”, information (node ID) for specifying the node that executes the process instructed by the command is recorded. In the items “transfer command” and “execution command”, information indicating a transfer command and an execution command (detailed later) created in “command processing” described later is recorded. In the item “distribution instruction”, an instruction that is actually delivered to the execution node 200 and is combined with a transfer instruction and an execution instruction is recorded. In the item “distribution destination node”, information indicating the execution node 200 that is the distribution destination of the instruction is recorded.

  Further, a “processing result management table” as shown in FIG. 3C is created in the storage unit 160 for storing the processing results of the respective execution nodes 200. As shown in the figure, the “processing result management table” has a record for each “processing result ID” (which may be the same as the command ID) uniquely assigned to the processing result corresponding to each input command of the “command management table”. Items such as “command ID”, “individual processing result”, and “final processing result” are prepared in each record. In the item “command ID”, a command ID assigned to an input command instructing execution of the process is recorded. In the item “individual processing result”, a processing result executed by the execution node 200 based on the command is recorded. In the item “final process result”, a final process result obtained by integrating the individual process results recorded in the “individual process result” is recorded.

  The storage unit 160 stores information necessary for communication with each node included in the database system 1, for example, address information such as an IP address and a MAC address that are destinations in communication via the communication network 10. It shall be. In this case, identification information indicating each node and the address information of the node are stored in association with each other.

  Next, the configuration of the execution node 200 will be described. The execution node 200 is a node (subnode) that accumulates data distributed in the database system 1 and executes arithmetic processing based on an instruction from the supervising node, and has a configuration as shown in FIG. As illustrated, the execution node 200 includes a control unit 210, a communication control unit 220, an input control unit 230, an output control unit 240, a program storage unit 250, and a storage unit 260.

  The control unit 210 includes, for example, a CPU and a predetermined storage device (such as a RAM) serving as a work area, controls each unit of the execution node 200, and is based on a predetermined operation program stored in the program storage unit 250. Then, each process described later is executed.

  The communication control unit 220 includes, for example, a predetermined communication device such as a NIC, connects the execution node 200 and the communication network 10, and communicates with the central node 100 and other execution nodes 200.

  The input control unit 230 connects, for example, a predetermined input device 23 such as a keyboard or a pointing device, and transmits an instruction input from the input device 23 to the control unit 210.

  The output control unit 240 connects a predetermined output device 24 such as a display device or a printer, and outputs the processing result of the control unit 210 to the output device 24 as necessary.

The program storage unit 250 includes a predetermined storage device such as a hard disk device or a ROM, and stores various operation programs executed by the control unit 210. The operation program stored in the program storage unit 250 is an operation program as described below for realizing each process described later in cooperation with the OS in addition to an arbitrary OS that controls the basic operation of the execution node 200. Is stored. Processing performed by the execution node 200 described later is realized by the control unit 210 executing these operation programs.
(P2-1) “Communication control program”: Program (P2-2) “Processing execution program for controlling the communication control unit 220 to communicate with the central node 100 and other execution nodes 200 via the communication network 10 ": A program for executing arithmetic processing using data distributed in the execution node 200 based on an instruction from the supervising node 100

When the control unit 210 of the execution node 200 executes the program, the execution node 200 realizes the following functions.
(F2-1) “Data transfer function”: a function of transmitting designated data to another execution node 200 or receiving from another execution node 200 based on a transfer command received from the supervising node 100 (F2-2) “Processing execution function”: a function for executing arithmetic processing using designated data based on an execution instruction received from the overall node 100

  In this embodiment, the control unit 210 executes the program stored in the program storage unit 250 to realize the above functions by so-called software processing. However, a circuit specialized for these functions (so-called ASIC ( By configuring the Application Specific Integrated Circuit)) in the execution node 200, the above function may be realized by so-called hardware processing.

  The storage unit 260 is configured from a predetermined storage device such as a RAM or a hard disk device, for example, and accumulates data used in the parallel distributed processing of the database system 1.

  In the present embodiment, it is assumed that predetermined table data (table data) TB is used for parallel distributed processing. Such table data is distributed and arranged in a plurality of execution nodes 200, but an arbitrary distribution method is applied to each table data TB. In the present embodiment, as shown in FIG. 5, table data (hereinafter referred to as “specific table ST”) stored only in a specific execution node 200 among a plurality of execution nodes 200, and one table data Table data (hereinafter referred to as “partition table PT”) that is divided and arranged in a plurality of execution nodes 200 is assumed.

  The divided table PT is a table in which the contents of the table data are divided and arranged in a plurality of execution nodes 200. In other words, when the divided tables PT arranged in the plurality of execution nodes 200 are combined, one table is obtained. It becomes. Here, whether the table data stored in the database system 1 is the specific table ST or the divided table PT depends on, for example, the size of each table data. That is, the size of table data is relatively large, and table data that requires considerable processing capability and processing time to process the entire table data with one node is divided into a plurality of execution nodes 200. Placed in. On the other hand, for table data that is relatively small in size and can be processed efficiently by one node, the entire table data is arranged in a specific execution node 200.

  Further, although identification information for identifying each node is given to each node, in order to facilitate understanding, in the example shown in FIG. 5, the number of execution nodes 200 is set to “5”, and each execution node It is assumed that an identification number of 1 to 5 is assigned to 200. Assume that a table TB1, a table TB2, and a table TB3 are prepared as table data. “Table TB1” is a specific table ST stored only in the execution node 200 with the identification number “1”. The “table TB2” is a divided table PT that is arranged in the execution nodes 200 whose contents are divided (TB2a to TB2d) and whose identification numbers are “1” to “4”. “Table TB3” is a specific table ST stored only in the execution node 200 whose identification number is “5”. In other words, the execution node 200 with the identification number “5” stores only the table TB3.

  In such a case, in the “data arrangement information” stored in the storage unit 160 of the supervising node 100, the identification number of the execution node 200 is recorded in the “node ID”, and information specifying the table (such as “TB1”). Is recorded as “data ID”.

  The storage unit 260 of the execution node 200 stores information necessary for communication with each node constituting the database system 1, for example, an address such as an IP address or a MAC address that is a destination in communication via the communication network 10. Assume that information is stored. In this case, identification information indicating each node and the address information of the node are stored in association with each other.

  Furthermore, information indicating the processing result by the execution node 200 is stored in the storage unit 260 as necessary.

  The operation of the database system 1 having such a configuration will be described below. In the present embodiment, it is assumed that different table data distributed in the execution node 200 of the database system 1 are subjected to a join operation. In the present embodiment, the following description will be made assuming that a join operation is performed between the table TB1 and the table TB2.

  First, “parallel distributed processing” executed in the database system 1 will be described with reference to the flowchart shown in FIG.

  In this “parallel distributed processing”, first, “command processing” for instructing execution of processing from the supervising node 100 to the execution node 200 is executed (step S100). Here, the operation of each execution node 200 for parallel distributed processing is defined, and the execution node 200 is instructed. Then, the execution node 200 that receives the instruction from the supervising node 100 executes “execution process” that performs the process by the operation based on the instruction (step S200). Then, the central node 100 executes “integrated processing” (step S300) in which the processing results of the execution node 200 are aggregated as overall processing results, whereby the parallel distributed processing by the database system 1 is completed.

  Details of each processing will be described below with reference to the drawings. First, the details of the “command processing” (step S100) executed by the supervising node 100 will be described with reference to the flowchart shown in FIG. This “command processing” indicates that a query (for example, an SQL statement) instructing parallel distributed processing using data stored in the database system 1 is input from the input control unit 130 or the like to the control unit 110. It shall be started when triggered. In the present embodiment, it is assumed that a query instructing a join operation between the table TB1 and the table TB2 is input. When a query is input, the control unit 110 creates a new record in the “command management table” in the storage unit 160 and records the query input in the item “input command”.

  The control unit 110 analyzes the input query and identifies data (hereinafter referred to as “target data”) used for the processing instructed by the query (step S101). In this example, since the join operation of the table TB1 and the table TB2 is instructed, “table TB1” and “table TB2” are specified as the target data. Also, identification information (“TB1”, “TB2”, etc.) indicating the specified target data is recorded in the “command management table” of the storage unit 160.

  When the target data is specified, the control unit 110 generates an “execution instruction” for instructing a processing operation to be executed by the target node for the processing (step S102), and records it in the “instruction management table” of the storage unit 160. . This “execution instruction” indicates “what kind of processing (calculation) is to be performed using which data”. That is, it can be the same information as the input query. In other words, the instruction for the entire process can be used as a common instruction for the execution nodes 200 as it is. As in this example, in the case of a process of performing a join operation between the table TB1 and the table TB2, for example, “select * from TB1, TB2 where TB1.attribute a = TB2.attribute b;” can be described by an SQL statement. . The exemplified execution instruction is an instruction for instructing the processing contents of “extract a column in which the attribute a in the table TB1 and the attribute b in the table TB2 match from the table TB1 and the table TB2” in each target node. As described above, the execution instruction generated in the supervising node 100 can be composed of one instruction common to all the execution nodes 200.

  When the execution instruction is generated, the control unit 110 refers to the “data arrangement information” stored in the storage unit 160 and executes the execution node 200 (hereinafter referred to as “target node”) in which the specified target data is stored. ) Is specified for each target data (step S103). In the example shown in FIG. 5, since the table TB1 is stored in the execution node 200 with the identification number “1”, this execution node 200 is specified as the target node. Similarly, since the table TB2 is stored in the execution nodes 200 having the identification numbers “1” to “4”, these execution nodes 200 are specified as target nodes. Further, identification information indicating the identified target node is recorded in the “command management table” of the storage unit 160.

  When the target node is specified, the control unit 110 determines the data transfer path so that all of the specified target nodes acquire the target data. In the present embodiment, since each execution node 200 performs parallel distributed processing, each of the execution nodes 200 that are the target nodes needs to acquire data used for the processing. In the present embodiment, the table TB1 that is the specific table ST is transferred to another target node. In this case, the control unit 110 analyzes that the table TB1 should be transferred from the execution node 200 with the identification number “1” to the execution nodes 200 with the identification numbers “2” to “4”.

  When the data transfer path is determined, a “transfer command” (preplan) instructing data transfer to the target node is generated (step S104) and recorded in the “command management table” of the storage unit 160. This transfer instruction instructs execution of data transfer between each target node before executing processing (execution plan) at the target node. It describes whether to transfer data. Here, a node ID is used as information indicating a node, and a data ID is used as information indicating data. A transfer instruction is configured by combining with a predetermined variable indicating an instruction to execute data transfer.

  For example, character string information such as “Data = TB1, sNode = 1, rNode = 2, 3, 4” is generated as a transfer command. In this case, the variable “Data” indicates data (table) to be transferred, the variable “sNode” indicates a node that transmits data (hereinafter referred to as “transmission node”), and the variable “rNode” indicates data. Indicates a node (hereinafter referred to as “receiving node”). Therefore, the transfer command exemplified above says that “send table TB1 from the execution node 200 having the identification number“ 1 ”to the execution node 200 having the identification numbers“ 2 ”,“ 3 ”, and“ 4 ”. It becomes an instruction. In other words, the execution node 200 with the identification numbers “2”, “3”, and “4” is a command “receive the table TB1 from the execution node 200 with the identification number“ 1 ””.

  When the execution instruction is generated, the control unit 110 generates “instruction information” obtained by combining the execution instruction generated in step S102 and the transfer instruction generated in step S104, and broadcast distribution to all execution nodes 200 ( Broadcast) (step S105). That is, the control unit 110 controls the communication control unit 120 and transmits command information to the execution node 200 via the communication network 10. Further, the generated command information and information (identification information) indicating the execution node 200 that is the distribution destination are recorded in the “command management table” of the storage unit 160. Here, it is assumed that a command ID assigned on the command management table of the storage unit 160 is added to the distributed command information. When the command information is distributed to the execution node 200, the “command processing” is terminated, and the process returns to the main flow (FIG. 6) of “parallel distributed processing”.

  In the above “instruction processing”, the data used for processing and the node storing the data are specified according to the parallel distributed processing to be executed. Which data should be transferred to which node Is determined. A transfer instruction based on this determination is generated and broadcast to the execution node 200 together with an execution instruction for instructing execution of the process. Here, the “execution instruction” is not individually defined for each execution node 200 but is one piece of common information, and the “transfer instruction” also includes data to be transferred, a node that transmits the data, and This is very simple information that only indicates the receiving node. Furthermore, since such an execution instruction and a transfer instruction are combined and distributed as one piece of information, the number of instruction transmissions can be reduced to one. Therefore, the instruction information for executing the parallel distributed processing can be distributed to the execution node 200 without imposing a load on the processing of the central node 100 and the communication network 10.

  When the command information is distributed to the execution node 200 by the “command processing”, in each execution node 200, the control unit 210 executes the “execution processing” based on the distributed command information (FIG. 6, step S200). . The details of the “execution process” will be described with reference to the flowchart shown in FIG. The “execution process” is started when the execution node 200 receives the instruction information. More specifically, the communication control unit 220 of the execution node 200 receives command information from the supervising node 100 via the communication network 10 and starts when the received command information is input to the control unit 210.

  The control unit 210 extracts a “transfer command” from the received “command information” (step S201). The control unit 210 determines whether or not the execution node 200 is designated as a transmission node in the extracted transfer instruction (step S202). In the example of the transfer command described above, the determination can be made based on whether or not the identification information of the execution node 200 is set in the variable “sNode” indicating the transmission node.

  When the execution node 200 is designated as the transmission node (step S202: Yes), the control unit 210 acquires the data designated in the transfer command (hereinafter referred to as “transfer target data”) from the storage unit 260. (Step S203). That is, the table data set in the variable “Data” of the transfer instruction is acquired from the storage unit 260. For example, when “Data = TB1” is described, the control unit 210 acquires the table TB1 from the storage unit 260 as transfer target data. In the example shown in FIG. 5, the execution node 200 having the identification number “1” storing the table TB1 that is the specific table ST out of the table TB1 and the table TB2 that are target data performs this processing. Become.

  The control unit 210 further controls the communication control unit 220 to transmit the table data (transfer target data) acquired in step S203 to the execution node 200 designated as “receiving node” by the transfer command (step S204). ). In the example of the transfer instruction, the execution node 200 set in the variable “rNode” is specified, and the table data is transmitted to the execution node 200. In this case, the control unit 210 acquires address information corresponding to the identification information set in “rNode” from the storage unit 260, and transmits the table data to the address. When the identification information of each node is address information such as an IP address, the table data is transmitted to the address set as the identification information in the transfer command.

  When the table data is transmitted, the control unit 210 extracts the “execution instruction” from the received instruction information (step S205), and uses the data (table data) specified in the extracted execution instruction to perform the specified process. (A join operation or the like) is executed (step S206). Here, the process is executed using the table data stored in the storage unit 260 of the execution node 200. If the node is a transmission node, the target data is stored in advance, so the process is executed using the table data stored in the storage unit 260. In the example illustrated in FIG. 5, the execution node 200 with the identification number “1” corresponds, and therefore, for example, a join operation is executed using the tables TB1 and TB2 stored in the storage unit 260.

  When the execution of the designated processing is completed, the control unit 210 stores information indicating the execution result (hereinafter referred to as “individual result information”) in the storage unit 260 or the work area, and also from the communication control unit 220 to the individual The result information is transmitted to the supervising node 100 via the communication network 10 (step S207). The individual result information transmitted by the execution node 200 is added with the instruction ID added to the instruction information received from the supervising node 100 and the identification information of the execution node 200. When the individual result information is distributed to the supervising node 100, the “execution process” is terminated and the process returns to the main flow (FIG. 6) of the “parallel distributed process”.

  On the other hand, when the execution node 200 is not designated as the transmission node (step S202: No), the control unit 210 determines whether or not the execution node 200 is set in the transfer command as the reception node (step S208). ). In the example of the transfer instruction, the determination is made based on whether or not the identification information indicating the execution node 200 is set in the variable “rNode”.

  When the execution node 200 is designated as the reception node (step S208: Yes), the control unit 210 waits for the target data to be transmitted from the execution node 200 set as the transmission node.

  When the target data is received from the transmission node (step S209), the control unit 210 stores the received target data in the storage unit 260 (step S210).

  When the target data transferred from another node is stored in the storage unit 260, the control unit 210 extracts an “execution instruction” from the received instruction information (step S205), and is specified in the extracted execution instruction. Using the data (table data), a designated process (such as a join operation) is executed (step S206). When the node is a receiving node, the data previously stored as the division table PT and the data transferred from other nodes are the target data. In the example illustrated in FIG. 5, the execution nodes 200 with the identification numbers “2”, “3”, and “4” correspond to the table TB2 stored in the storage unit 260 from the beginning, and the identification number “1”. Using the table TB1 transferred from the execution node 200, for example, a join operation is executed.

  When the execution of the designated process is completed, the control unit 210 stores the individual result information indicating the execution result in the storage unit 260 or the work area, and transmits the individual result information from the communication control unit 220 via the communication network 10. The data is transmitted to the central node 100 (step S207), and the process returns to the main flow (FIG. 6) of “parallel distributed processing”.

  On the other hand, when the execution node 200 is not designated as either the transmission node or the reception node (step S208: No), the control unit 210 performs the main flow of “parallel distributed processing” without performing any processing (FIG. Return to 6). That is, the “execution process” is terminated without transmitting or receiving data. In the example shown in FIG. 5, the execution node 200 with the identification number “5” corresponds to this. Since the execution node 200 stores only the table TB3, it is not necessary to participate in the current parallel distributed processing in which the table TB1 and the table TB2 are target data. Therefore, the “execution process” ends without performing data transfer or calculation.

  As described above, in the “execution process”, data necessary for execution of the process is transferred between the nodes based on the “transfer instruction” distributed from the supervising node 100. That is, when the target data is the specific table ST and the partition table PT, the specific table ST stored only in the specific node is transferred to another node. As a result, all nodes that execute parallel distributed processing hold necessary data. Thus, when the target data required by the target node is held without excess or deficiency, processing using the target data is executed at each target node. As described above, since the divided table PT divides the contents of one table and is distributed to a plurality of execution nodes 200, each execution node 200 stores table data having a size smaller than the entire table. Since processing such as a join operation is performed on the target, processing can be performed efficiently.

  Further, data transfer is not performed in a node that does not have target data. That is, since data transfer is performed only between the minimum necessary nodes among the plurality of execution nodes 200, the network load of the communication network 10 does not increase excessively.

  When the processing is executed by each execution node 200 and the processing result is acquired by the “execution processing”, the integrated node 100 executes the “integration processing” for integrating the processing results from the execution nodes 200. (FIG. 6, step S300). Details of the “integration processing” will be described with reference to the flowchart shown in FIG. The “integration process” is started when the supervising node 100 receives the individual result information from any of the target nodes. More specifically, the communication control unit 120 of the supervising node 100 receives the individual result information transmitted from the execution node 200 that is the target node, and the received individual result information is input to the control unit 110. To begin.

  When the individual result information is received from any of the execution nodes 200 that are the target nodes, the control unit 110 stores the “process result management table” in the storage unit 160 based on the instruction ID added to the individual result information. Then, it is searched whether there is a record in which the command ID is recorded (step S301).

  When there is no record including the instruction ID (step S301: No), the control unit 110 assigns a processing result ID, and newly creates a record with the processing result ID as a key in the “processing result management table” (step S302), the received individual result information is stored in the item “individual processing result” of the record (step S303). That is, when the processing result for the issued instruction comes first, a new record is created and individual result information is stored.

  Regarding the processing results that have arrived after the second, since records have already been created (step S301: Yes), the received individual result information is stored in the records (step S303).

  Based on the identification information of the execution node 200 added to the received individual result information and the identification information indicating the target node recorded in the “command management table” of the storage unit 160, the control unit 110 It is determined whether or not individual result information has been received from the target node (step S304).

  When the individual result information has not been received from all the target nodes (step S304: No), the process returns to step S301, and the individual result information is accumulated in the “processing result management table” until the individual result information is received from all the target nodes. To do.

  When the individual result information is received from all the target nodes (step S304: Yes), the control unit 110 integrates the individual result information accumulated in the “processing result management table” and generates final processing result information (step S305). ). That is, the processing results obtained at each execution node 200 are combined into one by parallel distributed processing, thereby obtaining the processing result for the original input instruction. The generated final process result information is recorded in the “process result management table” of the storage unit 160.

  The control unit 110 outputs the generated final process result information from the output device 14 via the output control unit 140 (step S306), and ends the process.

  As described above, according to the above embodiment, in the database system 1 that performs parallel and distributed processing, the information amount of instructions issued to a plurality of execution nodes 200 can be reduced. A command can be issued to a plurality of execution nodes 200 without imposing a load on the communication network 10 that transmits 100 or the command.

  Further, since the configuration of the instruction information can be made extremely simple and can be made common to all the execution nodes 200, the general node 100 that generates the instruction information, and the instruction information The processing load of the execution node 200 that recognizes is reduced.

  Furthermore, since only one command information obtained by combining an execution command for instructing the processing content to be executed and a transfer command for instructing data transfer to be executed before the processing execution needs to be transmitted, the number of command transmissions is 1. Only once. As a result, it is possible to issue a command to a plurality of execution nodes 200 without imposing a load on the central node 100 that transmits the command information and the communication network 10 that transmits the command information.

  Further, according to the distribution method of data stored in the database system 1, data necessary for the processing is transferred between the execution nodes 200, thereby acquiring the data required by the execution node 200 executing the processing. Therefore, there is no need to provide a specific node for acquiring and distributing all data. That is, since it is not necessary to process large data such as table data only by a specific node, overall processing efficiency can be increased. In addition, since data is not transferred in a node that does not execute processing, data can be transferred without imposing a load more than necessary on the communication network 10 that mediates data transfer. Further, such data transfer can be realized by a transfer command having a very simple configuration as described above.

(Second Embodiment)
In the first embodiment, for ease of understanding, the system configuration (number of nodes), the configuration of target data, the processing contents, etc. have been described in a simplified manner, but in an actual database system, the number of nodes and the amount of data are described. May be enormous, and the data distribution may be complicated. In many cases, the process is not simply a process of joining two pieces of table data as exemplified in the first embodiment. In such a case, a plurality of execution instructions and transfer instructions are required, and the instruction information may be complicated. A technique for efficiently performing processing even when the instructions become complicated will be described below as a second embodiment. The configuration of the database system 1 in the present embodiment is the same as that in the first embodiment.

  In the first embodiment, the specific table ST and the partition table PT are exemplified as the data distribution form, but in this embodiment, a “distribution table AT” is assumed in addition to these. The distributed table AT is a form in which one table data is arranged in a plurality of execution nodes 200 without being divided. That is, the same table data is arranged in a plurality of execution nodes 200. In the present embodiment, two types of division tables (PT1 and PT2) are assumed.

That is, as shown in FIG. 10, in the present embodiment, the following four types of table data are assumed.
Table TB1: Specific table ST arranged only in the execution node 200 with the identification number “1”
Table TB2: a divided table PT1 that is divided and arranged in the execution nodes 200 with the identification numbers “1” to “4”
Table TB3: a division table PT2 arranged by being divided into execution nodes 200 with identification numbers “2” to “5”
Table TB4: Distributed table AT arranged in the execution nodes 200 with identification numbers “1” to “5”

  In this embodiment, the instruction information obtained by combining the execution instruction and the transfer instruction is made into a tree structure (tree structure), and each execution node 200 recursively executes such a tree structure instruction. That is, when the supervising node 100 generates instruction information in step S105 of “instruction processing” (FIG. 7), tree structure (hierarchical structure) instruction information as shown in FIG. 11 is generated. The example of FIG. 11 has a four-layer structure from the first layer to the fourth layer. In the present embodiment, the first hierarchy is the highest hierarchy.

  In FIG. 11, an “execution plan tag” in the first hierarchy of the tree structure indicates that it is one instruction information (plan) including a plurality of execution instructions and transfer instructions. That is, a plurality of execution instructions and transfer instructions follow the execution plan tag in a tree-like hierarchical structure.

  “Execution instruction 1” in the first hierarchy is an execution instruction that instructs execution of processing (join operation) using the execution results of “execution instruction 2” and “execution instruction 5” in the second hierarchy immediately below.

  The “execution instruction 2” in the second hierarchy is an execution instruction that instructs execution of a join operation between the table TB1 and the table TB2, for example. Here, since the table TB1 is the specific table ST and the table TB2 is the division table PT1, both of them need to be transferred between the execution nodes 200. Therefore, “execution instruction 2” is followed by “transfer instruction 1” and “transfer instruction 2” in the third hierarchy.

  The “transfer instruction 1” is a transfer instruction for instructing transfer of the table TB1, and the “transfer instruction 2” is a transfer instruction for instructing transfer of the table TB2. The description format of the transfer instruction is the same as that in the first embodiment. That is, data to be transferred, a transfer source node, a transfer destination node, and the like are described. The execution instruction following the transfer instruction is an instruction to access (table scan) the table data acquired by executing the transfer instruction. In the example of FIG. 11, execution of table scan for the table TB1 is instructed by “execution instruction 3” following “transfer instruction 1”, and table scan for table TB2 is executed by “execution instruction 4” following “transfer instruction 2”. Execution is instructed.

  In other words, a transfer instruction for instructing the transfer of the table data is inserted in the hierarchy immediately before the execution instruction for instructing an operation on the table data that needs to be transferred between the execution nodes 200.

  On the other hand, for “execution instruction 5” parallel to “execution instruction 2” in the second hierarchy, appropriate execution instructions and transfer instructions follow in a hierarchical structure. In the example of FIG. 11, the execution instruction 5 is an execution instruction for instructing execution of a join operation between the table TB4 and the table TB3, for example. Here, since the table TB4 is a distributed table AT arranged in all the execution nodes 200, it is not necessary to transfer the table TB4 between the execution nodes 200. Therefore, “execution instruction 6” instructing the table scan for the table TB4 follows immediately below the execution instruction 5.

  Further, since the table TB3 targeted by the execution instruction 5 is the partition table PT2, transfer between the execution nodes 200 is required. Therefore, “transfer instruction 3” instructing transfer of the table TB3 follows the third hierarchy, which is a lower hierarchy of the execution instruction 5. Immediately below the transfer instruction 3, an “execution instruction 7” instructing execution of a table scan for the table TB3 acquired by the transfer instruction 3 follows.

  The operation of the execution node 200 having received such tree structure instruction information will be described below.

  In the execution node 200, when the communication control unit 220 receives the command information from the supervising node 100, the control unit 210 sequentially goes around from the highest hierarchy of the command information to execute the transfer command. As described above, also in this embodiment, since it is a transfer command similar to the transfer command illustrated in the first embodiment, the control unit 210 transmits and receives target data according to the description of the transfer command. That is, when the node itself is designated as a transmission node, the target data stored in the storage unit 260 is transferred to another execution node 200, and when the node itself is designated as a reception node, The target data transferred from the execution node 200 is received.

  Taking “execution instruction 2” and the like in FIG. 11 as an example, each execution node 200 executes “transfer instruction 1” immediately below, whereby the table TB1 is transferred between the execution nodes 200. Similarly, each execution node 200 executes “transfer instruction 2” immediately below “execution instruction 2”, whereby the table TB2 is transferred between the execution nodes 200. In execution of the transfer instruction, as in the first embodiment, the execution node 200 specified as the transmission node transmits the target data to the execution node 200 specified as the transfer destination, and the execution specified as the reception node. The node 200 waits for transfer of the target data.

  When the transfer of the target data is completed by executing the transfer instruction, each execution node 200 executes the execution instruction immediately below the transfer instruction. When the execution command directly instructing the table scan is directly below the transfer command, the control unit 210 acquires the data by performing a table scan on the table data specified in the transfer command. After execution of the execution instruction immediately below the transfer instruction, the control unit 210 executes the execution instruction immediately above the transfer instruction. That is, the control unit 210 of the execution node 200 recursively executes the received tree structure instruction.

  Taking “execution instruction 2” and the like in FIG. 11 as an example, the control unit 210 performs table scan (table 4 “execution instruction 3” on the table TB1 transferred by execution of “transfer instruction 1” (third hierarchy). ) And the table scan (table 4 “execution command 4”) transferred to the table TB2 transferred by the execution of “transfer command 2” (third layer), are executed in parallel from the tables TB1 and TB2. When such information is acquired, the “execution instruction 2” of the second hierarchy is executed, and a join operation between the acquired table TB1 and the table TB2 is executed. That is, for each branch of the tree structure, the transfer instruction is executed prior to the execution instruction.

  The same applies to “execution instruction 5” and thereafter in FIG. 11, and when a transfer instruction exists, the transfer instruction is executed first. That is, when executing the “transfer instruction 3” immediately below the execution instruction 5 and transferring the table TB3, the control unit 210 performs a table scan on the transferred table TB3 to acquire the contents (“execution instruction 7 "). In parallel with this, the controller 210 scans the table TB4, which is the distributed table AT, and acquires the contents (“execution instruction 6”). When the table TB3 and the table TB4 are acquired, the control unit 210 performs a join operation between the table TB3 and the table TB4 by recursively executing the “execution instruction 5”.

  Further, the control unit 210 recursively executes “execution instruction 1”, thereby performing a join operation using the result of the join operation by “execution instruction 2” and the result of the join operation by “execution instruction 5”. By performing this, the final individual processing result is calculated and transmitted to the overall node 100.

  As described above, the instruction information is made into a tree structure and is recursively executed by each execution node 200, so that the number of nodes and the amount of data are large, the data distribution form is complicated, and the contents of the processing to be executed are complicated. Even in such a case, parallel distributed processing can be executed with one instruction information.

  That is, by applying the present invention as in the above embodiments, the processing efficiency of the database system that performs parallel distributed processing can be improved.

  In the above embodiment, the specific table ST stored only in a specific node, the divided table PT divided and arranged in a plurality of nodes, or the same table data is distributed in a plurality of execution nodes 200. Although the case of performing a join operation using the distributed table AT as target data has been illustrated, target data, processing to be executed, and the like are arbitrary. For example, the same processing can be performed for a join operation between specific tables ST or a join operation between divided tables PT. The type of data stored in the database system 1 or data used for arithmetic processing is not limited to the exemplified table data (table data), and arbitrary data can be handled.

  In addition, it is desirable that the transfer path when generating the transfer command is determined according to the processing capability of each node, the type and size of each data, and the like. That is, in the determination of the transfer route in the first embodiment, the transfer route is such that the specific table ST arranged only in one execution node 200 is transferred to another execution node 200. The partition table PT stored in the execution node 200 may be transferred to the execution node 200 holding the specific table ST. That is, the control unit 110 of the supervising node 100 may determine the most efficient transfer route by calculating the cost based on, for example, statistical information. In this case, for example, information indicating the processing capability of each execution node 200 may be recorded in “data arrangement information” stored in the storage unit 160 of the supervising node 100.

  In the above embodiment, the instruction information is broadcast to all the execution nodes 200. However, the instruction information may be distributed only to the specified target node. In this case, an address may be specified based on the identification information of the specified target node, and command information may be transmitted to the specified address. Thereby, the network load at the time of command distribution can be further reduced.

  The supervising node 100 and the execution node 200 according to the above embodiment can be configured by using a general-purpose computer device or the like as well as being configured by a dedicated device. That is, by installing and executing the above-described program in such a general-purpose device, the general node 100 and the execution node 200 according to the embodiment can be functioned.

  Such a program providing method is arbitrary. For example, the program data can be stored and distributed in a storage medium such as a CD-ROM, and the program data can be superposed on a carrier wave so that a predetermined communication medium (for example, It can also be distributed via the Internet).

It is a figure which shows typically the structure of the "database system" concerning embodiment of this invention. FIG. 2 is a block diagram illustrating a configuration of a “general node” illustrated in FIG. 1. FIG. 3 is a diagram illustrating an example of information recorded in a “storage unit” illustrated in FIG. 2, where (a) illustrates an example of “data arrangement information”, (b) illustrates an example of an “instruction management table”, ( c) shows an example of a “processing result management table”. FIG. 2 is a block diagram illustrating a configuration of an “execution node” illustrated in FIG. 1. It is a figure for demonstrating the distribution system of the data arrange | positioned at the "execution node" shown in FIG. It is a flowchart for demonstrating embodiment "parallel distributed processing" of this invention. 7 is a flowchart for explaining “instruction processing” executed in “parallel distributed processing” shown in FIG. 6. It is a flowchart for demonstrating the "execution process" performed by the "parallel distributed process" shown in FIG. It is a flowchart for demonstrating the "integration process" performed by the "parallel distributed process" shown in FIG. It is a figure for demonstrating the data distribution system concerning the 2nd Embodiment of this invention. It is a figure for demonstrating the command information of the tree structure concerning the 2nd Embodiment of this invention.

Explanation of symbols

1 Database system 10 Communication network 100 Supervising node 200 Execution node

Claims (6)

In a database system that performs parallel distributed processing on multiple nodes,
The plurality of nodes are composed of a central node that controls the parallel and distributed processing and a plurality of execution nodes that perform data accumulation and arithmetic processing, which are interconnected via a communication network.
The supervising node is
Execution instruction generation means for generating a common execution instruction for instructing execution of arithmetic processing in each execution node;
Transfer instruction generation means for generating a transfer instruction for instructing transfer of data used in the arithmetic processing instructed by the execution instruction;
Instruction distribution means for broadcasting instruction information obtained by combining the execution instruction generated by the execution instruction generation means and the transfer instruction generated by the transfer instruction generation means to the plurality of execution nodes via the communication network; ,
With
The execution node is
Command receiving means for receiving command information distributed from the command distributing means of the supervising node via the communication network;
Data transfer means for transmitting and receiving data to and from other execution nodes via the communication network based on the transfer command received by the command receiving means;
Based on the execution command received by the command receiving means, arithmetic means for performing arithmetic processing using the stored data and the data received by the data transfer means;
A database system comprising: The transfer command generating means generates a transfer command specifying an execution node to which data is to be transmitted and an execution node to be receiving data.
The database system according to claim 1. The supervising node is
It further comprises arrangement information acquisition means for acquiring and storing arrangement information indicating which data is stored in which execution node,
The transfer command generation unit generates the transfer command based on the arrangement information stored in the arrangement information acquisition unit.
The database system according to claim 1 or 2, wherein The instruction distribution means distributes the instruction information of a tree structure in which the execution instruction generated by the execution instruction generation means and the transfer instruction generated by the transfer instruction generation means are combined to the plurality of execution nodes,
The arithmetic means recursively executes the instruction information of the tree structure received by the instruction receiving means, thereby executing arithmetic processing indicated by the execution instruction included in the instruction information.
The database system according to any one of claims 1 to 3, wherein: To the computer that supervises the database system that performs parallel and distributed processing,
Obtaining and storing arrangement information indicating which data is stored in which of the plurality of computers constituting the database system;
Generating an execution instruction including information indicating contents of arithmetic processing to be executed by each of the plurality of computers, and information specifying data used in the arithmetic processing;
Generating, based on the arrangement information, a transfer instruction including information indicating a computer that should transmit data to another computer and information indicating a computer that should receive data from the other computer;
Broadcasting instruction information obtained by combining the generated execution instruction and transfer instruction to the plurality of computers via a communication network;
A program characterized by having executed. In the computer that constitutes the database system that performs parallel and distributed processing,
Storing data used for arithmetic processing;
Receiving an execution instruction and a transfer instruction distributed from a computer controlling the database system via a communication network;
Transmitting and receiving data to and from another computer via the communication network based on the received transfer command;
A step of performing arithmetic processing using the stored data and data received from another computer based on the received execution instruction;
A program characterized by having executed.

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