JP3172793B1 - Database management method - Google Patents

Abstract

Abstract: PROBLEM TO BE SOLVED: To provide a database division management method and a parallel database system capable of obtaining an expected degree of parallelism and realizing a high-speed inquiry. SOLUTION: FES75, BES73, IOS70,
The parallel database system 1 is configured by connecting the disks 80. The number of processors of the FES 75, the BES 73, and the IOS 70, the number of disks of the disk 80, and the number of divisions thereof are determined according to the load pattern. For example, FE
S: BES: IOS: Disk = 1: 4: 1: 8. In addition, the number of BESs is increased or decreased from one at a maximum to four at a maximum in accordance with a load change, thereby providing a scalable system configuration. When the BES is increased or decreased, only the management information is moved without moving the data. [Effect] It is possible to realize a high-speed query processing in which an expected degree of parallelism can be obtained. System scalability can be achieved.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] The present invention relates to database management.
It relates to a method, and more particularly, this to obtain the degree of parallelism to expect
And can realize high-speed inquiries.
Regarding the coming database management methods .

[0002]

2. Description of the Related Art For example, "Devid DeWitt and Jim Gra
y: Parallel Database Systems: TheFuture of High P
erformance Database Systems, CACM, Vol.35, No.6, 1
992], a parallel database system is proposed. In this parallel database system, a plurality of processors are connected tightly or loosely, and database processing is distributed to the plurality of processors.

[0003]

The system configuration of the conventional parallel database system is left to the user and is fixed. For this reason, the system configuration may be incompatible with the load from the beginning or may be incompatible in the middle, and there has been a problem that an expected degree of parallelism cannot be obtained and a high-speed inquiry cannot be realized. Therefore, an object of the present invention is to obtain an expected degree of parallelism,
Database tube that can realize high-speed inquiries
It is to provide a management method .

[0004]

According to a first aspect of the present invention, a plurality of set key ranges and a storage device are provided.
Associated data storage areas and store the data
When storing in the database, the key range containing the data
The above data is stored in the data storage area corresponding to
If you enter a request to divide the key range,
The key range is divided into data storage areas.
And a database management method characterized by associating with a database . In addition, multiple set key ranges and storage
Associating with a plurality of data storage areas provided in the device,
If the above key range needs to be divided,
Divide the key range and store it in the data storage area.
There is provided a database management method characterized by the following. In the database management method according to the first aspect ,
In, the system configuration is adapted to the load, the expected degree of parallelism can be obtained, and a high-speed inquiry can be realized.

[0005] In a second aspect, the present invention provides a method for setting a set
Key range of numbers and multiple data stored in storage device
Associate data with storage area and store data in database
The data corresponding to the key range containing the data
Store the above data in the storage area and add a key range
If the request is accepted, the information indicating the key range
Include in the request and associate the key range with the data storage area
To provide a database management method characterized by
You .

[0006] In a third aspect, the present invention provides a method for setting a set
Key range of numbers and multiple data stored in storage device
Associate data with storage area and store data in database
The data corresponding to the key range containing the data
Store the above data in the storage area and divide the key range
If the request is accepted, the original key range
Information indicating a first key range,
The value to be split and the data corresponding to the split key range
Data storage area for storing data and second data storage area
The request includes information indicating an area and the first key word.
The second value in the range below the value to be divided
A key range and the first key range
To the third key range whose range is greater than
Divide the first key range and divide the second key range
The third keylen is associated with the first data storage area.
Wherein the data is associated with the second data storage area.
And provide a database management method .

[0007] In a fourth aspect, the present invention relates to a method for setting a set multiplicity.
Key range of numbers and multiple data stored in storage device
Associate data with storage area and store data in database
The data corresponding to the key range containing the data
Store the above data in the storage area and merge the key range
If a request is accepted, information indicating multiple key ranges
Included in the request, the plurality of key ranges
Key range and data storage area
A database management method characterized by matching
Provide .

[0008] In a fifth aspect, the present invention provides a method for setting a set
Key range of numbers and multiple data stored in storage device
Associate data with storage area and store data in database
The data corresponding to the key range containing the data
Store the above data in the storage area and delete the key range
Indicates the key range to be deleted when a request is accepted
Include information in the request and associate it with the key range to be deleted
And the key range to be deleted.
A database characterized by deleting information to be associated
Provide a resource management method .

[0009] In a sixth aspect, the present invention provides a method for setting a set
Key range of numbers and multiple data stored in storage device
Associates a storage area and receives a request to divide the key range.
The first key range, which is the original key range to be split
Information indicating a key range, dividing the first key range
Stores values and data corresponding to divided key ranges
The first data storage area and the second data storage area
Information in the first key range.
The second keylen whose range is equal to or less than the value to be divided.
From the value to be divided in the first key range
The first key and the third key range
Divide the range and add the second key range to the first
Data storage area, and the third key range
Data corresponding to the second data storage area.
Provide database management methods .

[0010] In a seventh aspect, the present invention provides a method for setting a set
Key range of numbers and multiple data stored in storage device
Receives a request to associate the key range with the storage area.
Information, indicating information on multiple key ranges in the request.
Includes and merges multiple key ranges into one key range
And associates the merged key range with the data storage area.
To provide a database management method characterized by
You .

[0011] In an eighth aspect, the present invention relates to a method for setting a plurality of sets.
Key range of numbers and multiple data stored in storage device
Receives a request to delete the key range by associating it with the storage area.
Information that indicates the key range to be deleted.
Included in the request and associated with the key range to be deleted
Associating the data storage area with the key range to be deleted
Database management method characterized by deleting information
Provide the law .

[0012]

Embodiments of the present invention will be described below in detail with reference to the drawings. Note that the present invention is not limited by this. FIG. 1 is a configuration diagram illustrating a parallel database system 1 according to an embodiment of the present invention. The parallel database system 1 includes an FES (front end server) node, a BES (back end server) node, an IOS (input output server) node,
In this configuration, a DS (dictionary server) node and a JS (journal server) node are connected by a network 90. Each node is also connected to other systems. The FES node is a node composed of at least one FES 75 having no disk and having at least one processor.
It has the function of a front-end server that executes processing procedure creation. The BES node is a node composed of at least one BES 73 having no disk and having a function of accessing a database based on the processing procedure created by the FES 75. The IOS node is a node including an IOS 70 composed of at least one processor and at least one disk 80, and has a function of storing and managing a database on the disk 80. In addition, IOS
If the node function is provided to the BES node, the IOS node can be omitted. In this case, a disk is connected to the BES 73, and the BES 73 has a function of storing and managing a database on the disk 80.

The database is composed of a plurality of tables. The table is in a two-dimensional table format and includes a plurality of rows. One row is composed of one or more columns (attributes). This table is physically divided into fixed-length pages each consisting of a predetermined number of rows and stored on the disk 80. The storage position of each page on the disk 80 can be known using directory information.

The DS node is a node comprising a DS 71 composed of at least one processor and at least one disk 81, and has a function of collectively managing database definition information. The JS node is a node including a JS 72 configured with at least one processor and at least one disk 82, and has a function of storing and managing database update history information executed by each node.

FIG. 2 shows the parallel database system 1 described above.
1 is a conceptual diagram of a database division management method of the present invention for determining the number of processors, the number of disks, and the number of divisions of disks of FES 75, BES 73, and IOS 70 in FIG.
First, the load pattern of the database processing is determined based on the workload specified by the user. The load pattern includes a single search process, a single update process, a data retrieval process, and the like. In accordance with the load pattern, the IOS 70 determines how many partitions the disk 80 should be managed (if the BES has the function of the IOS node, the BES 73 determines how many partitions the disk will manage). That is, when defining the schema, the number of disks required for storage is determined from the table partitioning method (key value range, number of rows per range (converting the number of pages), etc.), and if the unit of blockage and reorganization is determined, BES73
(The unit of blockage or reorganization depends on the disk, IOS, and BES). Thereby, BES73, IOS70, disk 8
0 is determined. That is, it becomes as follows. Number of divisions: Database division unit that can be accessed in parallel managed by all BESs (Dynamic BES addition and deletion are performed in this division unit) Number of disks in each division: Number of disks allocated in each division FIG. This is the case where the number is “8”, the number of divisions is “4”, and the number of disks for each division is “2”. If the processor performance is increased by n times, the number of volumes used in each division is increased by n times without changing the number of divisions (however, the IOS 70
There is a limit on the total data transfer rate between the disk and the disk 80, so the number of disks is also limited.) Here, the disk corresponds to one disk device. In the present invention, the “disk” does not necessarily have to correspond one-to-one with one disk device. For example, when one disk device includes a plurality of disk devices (disk array device), the number of input / output units that can be accessed in parallel may be applied as “disk device”.

As shown in FIG. 2, FES: BES: IOS: disk = 1: 4: 1: 8. At the time of initial data loading, only one FES and BES is required.
S: IOS: disk = 1: 1: 1: 8.
For this reason, the BES 731 has directory information of a database stored in the disks 811 to 842 of the divisions # 1 to # 4. The load of BES73 is light, and BES73
IOS 7 and 8 disks 8 with only one 731
When 11 to 842 can be processed, only one BES 731 accesses the database stored in the eight disks 811 to 842. Therefore, FES: BES: IO
S: disk = 1: 1: 1: 8 remains.

The load on the BES731 increases and the utilization rate becomes 10
When the state of 0% continues and load imbalance is detected, B
ES732 is added. Since the number of divisions is “4”, two divisions are respectively associated with the two BESs 731 and 732. Therefore, the BES 731 has directory information of a database stored in the disks 811 to 822 of the divisions # 1 and # 2. Also, BES7
32, disks 831 to 842 of divisions # 3 to # 4
Contains the directory information of the database stored in.
FES: BES: IOS: disk = 1: 2: 1: 8.

Further, when the load on the BESs 731 and 732 increases and the utilization rate continues to be 100% and a load imbalance is detected, the BES
33, 734 are added. Since the number of divisions is “4”, one division is associated with each of the four BESs 731, 732, 733, and 734. Therefore, BES
731 has directory information of a database stored in the disks 811 to 812 of the division # 1. Also, in the BES 732, the disks 821 to
822 has the directory information of the database stored. In addition, the BES 733 has directory information of a database stored in the disks 831 to 832 of the division # 3. Further, the BES 734 has directory information of a database stored in the disks 841 to 842 of the division # 4. FES: BES: IOS: disk = 1: 4: 1: 8.

When the load is reduced and the utilization rate of the BES 733 and 734 continues to be, for example, less than 50%, the BES 73
It is more effective to use the node assigned to 3,734 for other processing. Therefore, BES 733 and 734 whose utilization is less than 50% are combined. Then FES:
BES: IOS: Disk = 1: 2: 1: 8

As described above, if the BES is increased or decreased according to the load, FES: BES: IOS: disk = 1: 1:
A scalable system between 1: 8 and 1: 4: 1: 8 can be realized.

The IOS 70 includes the BES 73 and the disk 80
Irrespective of the correspondence, it is sufficient that there are parallel tasks for the number of disks that can be accessed in parallel. Therefore, by moving directory information between BESs without moving data, the correspondence between the BES 73 and the disk 80 can be changed, and access separation and integration can be easily performed.

Next, the number of processors, the number of processors,
The number of disks and the number of disk divisions will be described using numerical examples.
Assumptions are made as follows. FES processing (reception processing) ... 30 [K steps] BES processing (one update processing) ... 60 [K steps] (data extraction processing) ... 220 [K steps] Transmission processing ... 6 [K steps] Reception processing ... 6 + 4 * Number of pages [K step] I / O issue processing ... 4 + 4 * Number of pages [K step] Processor performance ... 10 [M steps / second] Input / output performance (1 page access) ... 20 [msec] (10 pages access) ... 30 [Msec] In the case of single update processing (1 page access) (1) In the case of a system configuration with an IOS node When 30 [K steps] of the FES processing is divided by 10 [M steps / second], the reception is up to 333 times / second. Processing is possible. Also, an execution request reception process 6 from the FES [K step] + a data extraction request transmission process 6 from the BES
[K step] + Receive processing of data retrieval result from IOS 10 [K step] + one-item update processing 60 [K step] + FE
Since the transmission processing of the execution request result to S 6 [K step] = 88 [K step] is necessary for the single update processing in the BES, the processor performance 10 [M step / sec] is divided by 11
Up to four times / sec. One-item update processing is possible. In addition, BE
Input / output request reception processing 6 [K step] + I / O issue processing 8 [K step] + Transmission processing of input / output request result to BES 6 [K step] = 20 [K step] to the disk of IOS Therefore, if the processor performance is divided by 10 [M steps / second], the disk can be accessed up to 500 times / second. In addition, since random input / output of one page requires 20 [msec], one disk can be accessed up to 50 times / sec. With this I
When the number of times that the OS can access the disk is less than 500 times / second, up to ten disks can be mounted on the IOS. In addition, the number of times one case can be updated by the BES 11
When the number of times that the disk can be accessed by the IOS at 500 times / second is divided by 4 times / second, 4.3 Bs per IOS can be obtained.
Supports ES. Further, when the number of times that one case can be updated by the BES is divided by 114 times / second by which the reception processing by the FES can be performed by 333 times / second, three BEs can be processed by one FES.
S can be supported. From the above, FES: BES = 1:
3, BES: IOS = 4.3: 1, IOS: disk =
1:10. Therefore, comprehensively, as shown in FIG. 3, FES: BES: IOS: disk = 1: 4: 1:
8 makes the implementation almost balanced (FES
And some imbalance in the disc).

(2) In the case of a system configuration in which the function of the IOS node is provided in the BES node When the processor performance 10 [M steps / sec] is divided by 30 [K steps] of the FES processing, the reception processing is performed up to 333 times / sec. Is possible. In addition, processing 6 for receiving an execution request from the FES [K step] + input / output issuing processing 8 [K step] + one-item update processing 6
0 [K step] + Transmission processing 6 of execution request result to FES
[K step] = 80 [K step] is necessary for one case update processing in BES, so when processor performance is divided by 10 [M step / second], one case update processing can be performed up to 125 times / second. It is. In addition, 20 [m] for random input / output of one page
Seconds], one disk can be accessed up to 50 times / second. Thus, if the number of times that the single update process can be performed in the BES is divided by 125 times / second, up to 2.5 disks can be mounted in the BES. Further, the BES
By dividing 333 times / sec of reception processing possible by the FES by 125 times / second of the number of times that one case can be updated, one FES can cope with 2.6 BESs. From the above, FE
S: BES = 1: 2.6, BES: disk = 1: 2.
It becomes 5. Therefore, comprehensively, as shown in FIG.
Assuming that ES: BES: disk = 1: 4: 8, the mounting is almost balanced (some unbalance occurs in the FES).

B. Data retrieval processing (10-page access)
In the case of (1) System Configuration with an IOS Node If the processor performance is divided by 10 [M steps / sec] by 30 [K steps] of the FES processing, reception processing can be performed up to 333 times / sec. Also, an execution request reception process 6 from the FES [K step] + a data extraction request transmission process 6 from the BES
[K step] + Receive processing 46 of data fetch result from IOS [K step] + Data fetch processing 220 [K step] + Transmission processing of execution request result to FES 6 [K step]
= 284 [K steps] is necessary for the data fetch processing in the BES, so that the processor performance is 10 [M steps /
[Sec], data extraction processing can be performed up to 35 times / sec. Furthermore, input / output request reception processing 6 [K step] from BES + input / output issue processing 44 [K step] + BES
6 [K step] = 56 [K step] necessary for transmitting the I / O request result to the disk of the IOS, the processor performance is divided by 10 [M step / sec] to 179 times / Sec access to the disk. Also, since batch input / output of 10 pages requires 30 [msec], one disk can be accessed up to 33 times / sec. By dividing the number of times that the disk can be accessed by the IOS by 179 times / second, up to 5.4 disks can be mounted. Further, if the number of times that data can be retrieved by the BES is 35 times / second, the number of times that the disk can be accessed by the IOS is 179 times / second, one IOS can support 5.1 BESs. . further,
By dividing 333 times / sec of reception processing at the FES by 35 times / sec of data retrieval processing possible number at the BES,
One FES can support 9.5 BESs. From the above, FES: BES = 1: 9.5, BES: IOS
= 5.1: 1, IOS: disk = 1: 5.4.
Therefore, as a whole, if FES: BES: IOS: disk = 1: 10: 2: 10, the mounting is almost balanced (some unbalance occurs in the disk).

(2) In the case of a system configuration in which the function of the IOS node is provided in the BES node When the processor performance 10 [M steps / sec] is divided by 30 [K steps] of the FES processing, the reception processing is performed up to 333 times / sec. Is possible. In addition, reception processing 6 [K step] of the execution request from the FES + input / output issue processing 44 [K step] + data extraction processing 220 [K step] + transmission processing of the execution request result to the FES 6 [K step] = 276 Since [K step] is necessary for the data extraction processing in the BES, if the processor performance is divided by 10 [M steps / second], the data extraction processing can be performed up to 36 times / second. Also, since batch input / output of 10 pages requires 30 [msec], one disk can be accessed up to 33 times / sec. With this BE
When the number of times the data can be retrieved in S is less than 36 times / second, only one disk can be mounted. Further, when 333 times / sec of reception processing by the FES is divided by 36 times / sec of data extraction processing possible number by the BES, 1
One FES can support 9.2 BESs. From the above, FES: BES = 1: 9.2 and BES: disk = 1: 1. So, overall, FES: BE
Assuming that S: disk = 1: 10: 10, mounting is almost balanced.

FIG. 5 is a configuration diagram of the FES 75. FE
In step S75, the application programs 10 to 11 created by the user, the parallel database management system 20 that manages the entire database system such as query processing and resource management, and the operating system 3 that manages the entire computer system such as reading and writing data.
0. The parallel database management system 20 includes a system control unit 21, a logical processing unit 22,
A physical processing unit 23 and a database / dictionary 24 for temporarily storing data to be processed are provided. In addition, the parallel database management system 20
Is connected to the network 90 and other systems.

The system control unit 21 performs input / output management and the like. Further, it includes a data load process 210 and a dynamic load control process 211.

The logic processing unit 22 performs a query analysis 220 for performing syntax analysis and semantic analysis of a query, a static optimization process 221 for generating appropriate processing procedure candidates, and a code corresponding to the processing procedure candidates. Code generation 222 to be performed. It also includes a dynamic optimization process 223 for selecting the most suitable processing procedure candidate, and a code interpretation execution 224 for interpreting and executing the code of the selected processing procedure candidate.

The physical processing unit 23 is shared by the system with the data access processing 230 for determining the conditions of the accessed data, editing and adding records, and the database / dictionary buffer control 231 for controlling reading and writing of database records. And exclusive control 233 for implementing exclusive control of resources to be performed.

FIG. 6 is a block diagram of the BES 73. BE
S73 includes a parallel database management system 20 that manages the entire database system, and an operating system 30 that manages the entire computer system. When the device has the function of the IOS node, it has a disk, and stores and manages the database 40 on the disk. The parallel database management system 20 includes a system control unit 21 and a logical processing unit 2
2, a physical processing unit 23, and a database buffer 24 for temporarily storing data to be processed. Further, the parallel database management system 20 includes:
It is connected to the network 90 and other systems.

The system control unit 21 manages input / output and the like. In addition, a data load process 210 for performing data load in consideration of load distribution is provided. The logic processing unit 22 includes a code interpretation and execution 224 for interpreting and executing a code. The physical processing unit 23 includes a data access process 230 that performs condition determination, editing, and record addition of accessed data, a database buffer control 231 that controls reading and writing of database records, and storage of data to be input / output. The system includes a mapping process 232 for managing a position and an exclusive control 233 for implementing exclusive control of resources shared by the system.

FIG. 7 is a configuration diagram of the IOS 70 and the disk 80. The IOS 70 includes a parallel database management system 20 that manages the entire database system, and an operating system 30 that manages the entire computer system. The database 80 is stored on the disk 80.

The parallel database management system 20
Is a system control unit 21, a physical processing unit 23, and an input / output buffer 24 for temporarily storing data to be processed.
Is provided. The parallel database management system 20 is connected to the network 90 and other systems.

The system controller 21 manages input and output. In addition, a data load process 210 for performing data load in consideration of load distribution is provided. The physical processing unit 23 performs data access processing 2 that implements condition determination, editing, record addition, and the like of the accessed data.
30 and an input / output buffer control 231 for controlling reading and writing of database records.

FIG. 8 is a configuration diagram of the DS 71 and the disk 81. The DS 71 includes a parallel database management system 20 that manages the entire database system, and an operating system 30 that manages the entire computer system. The disk 81 stores a dictionary 50.

The parallel database management system 20
Has a system control unit 21, a logical processing unit 22, a physical processing unit 23, and a dictionary buffer 24. In addition, the parallel database management system 20
Is connected to the network 90 and other systems. The logic processing unit 22 includes a code interpretation and execution 224 for interpreting and executing a code. The physical processing unit 23 includes a data access process 230 that implements condition determination, editing, record addition, and the like of the accessed data, a dictionary buffer control 231 that controls reading and writing of dictionary records, and an exclusive control of resources shared by the system. And an exclusive control 233 for realizing the following.

FIG. 9 is a configuration diagram of the JS 72 and the disk 82. The JS 72 includes a parallel database management system 20 that manages the entire database system, and an operating system 30 that manages the entire computer system. On disk 82,
The journal 60 is stored.

The parallel database management system 20
Has a system control unit 21, a physical processing unit 23, and a journal buffer 24. The parallel database management system 20 is connected to the network 90 and other systems. The physical processing unit 23
Has a data access process 230 for realizing condition determination, editing, record addition, and the like of accessed data, and a journal buffer control 231 for controlling reading and writing of journal records.

FIG. 10 is a flowchart showing the processing of the database management system 20 in the FES 75. The system control unit 21 checks whether or not it is an inquiry analysis process (212). If it is a query analysis process, the query analysis process 400 is called, executed, and then terminated. If it is not a query analysis process, it is checked whether it is a query execution process (213). If it is a query execution process, the query execution process 410 is called, executed, and then terminated. If it is not a query execution process, it is checked whether it is a data load process (214). In the case of the data load process, the data load process 210 is called, executed, and the process ends. If it is not a data load process, it is checked whether it is a dynamic load control process (214). In the case of the dynamic load control processing, the dynamic load control processing 210 is called, executed, and then terminated. If it is not a dynamic load control process, the process ends.

The flowchart of the processing of the database management system 20 in the BES 73 is such that steps 212, 215, 400, and 211 are omitted from FIG. In addition, the flowchart of the process of the database management system 20 in the IOS 70 is described in steps 212, 213, 215, 400, 410, 211 from FIG.
Is omitted.

FIG. 11 is a flowchart of the inquiry analysis processing 400. First, the query analysis 220 executes syntax analysis and semantic analysis of an input query sentence. Next, the static optimization processing 221 estimates the ratio of data satisfying the condition from the conditional expression appearing in the query, and selects a valid access path candidate (particularly an index) based on a preset rule. ) To create a candidate for the processing procedure. Next, by the code generation 222, the candidates of the processing procedure are developed into codes in an executable format. Then, the process ends.

FIG. 12 is a flowchart of the query analysis 220. In step 2200, syntax analysis and semantic analysis of the input query sentence are executed. Then, the process ends.

FIG. 13 is a flowchart of the static optimization processing 221. First, the predicate selectivity estimation 2210 estimates the selectivity of the predicate of the conditional expression appearing in the query. Next, an access path composed of an index or the like is pruned by the access path pruning 2212. Next, the processing procedure candidate generation unit 2213 generates a processing procedure candidate combining the access paths. Then, the process ends.

FIG. 14 is a flowchart of the predicate selection rate estimation 2210. In step 22101, it is checked whether a variable appears in the query conditional expression (2210).
1). If the variable does not appear, the process proceeds to step 22102. If the variable appears, the process proceeds to step 22104. In step 22102, it is checked whether the conditional expression includes column value distribution information. If there is column value distribution information, the process proceeds to step 22103. If there is no column value distribution information, the process proceeds to step 22105. In step 22103, the selectivity is calculated using the column value distribution information, and the processing ends. In step 22104, it is checked whether or not there is column value distribution information in the conditional expression. If there is column value distribution information, the process ends. If there is no column value distribution information, step 2210
Go to 5. In step 22105, a default value is set according to the type of the conditional expression (22105), and the process ends.

FIG. 15 is a flowchart of the access path pruning 2212. In step 22120, the index of the column appearing in the query conditional expression is registered as an access path candidate. In step 22121, it is checked whether the table to be accessed by the query is divided and stored in a plurality of nodes. If it is not divided and stored, the process proceeds to step 22122. If it is divided and stored, the process proceeds to step 22122.
Go to 123. In step 22122, the sequential scan is registered as an access path candidate. In step 22123, the parallel scan is registered as an access path candidate. In step 22124, it is checked whether the selectivity of each conditional expression has already been set. If the setting has been completed, the process proceeds to step 22125, and if not, the process proceeds to step 22126. In step 22125, the index of the conditional expression that minimizes the selectivity for each table is set as the highest priority of the access path. Step 2212
In step 6, the maximum value and the minimum value of the selectivity of each conditional expression are acquired. In step 22127, the processor performance, IO
A selection criterion for each access path is calculated from system characteristics such as performance. In step 22128, only those access paths in which the selectivity of an access path obtained by combining a single index or a plurality of indexes is lower than the above selection criteria are registered as access path candidates.

FIG. 16 is a flowchart of processing procedure candidate generation 2213. In step 22130, it is checked whether the table to be accessed by the query is divided and stored in a plurality of nodes. If it is not divided and stored, the process proceeds to step 22131. If it is divided and stored, step 2131 is performed.
Proceed to 2135. In step 22131, it is checked whether or not the sorting procedure is included in the processing procedure candidate.
If not included, the process proceeds to step 22132, and if included, the process proceeds to step 22135. Step 2213
In step 2, it is checked whether the access path of the table to be accessed in the inquiry is unique. Step 2 if unique
Proceed to 2133; if not unique, proceed to step 22134. In step 22133, a single processing procedure is created, and the processing ends. In step 22134, a plurality of processing procedures are created, and the processing ends.

In step 22135, the query is decomposed into two-way joins that can be joined. In step 22136, the data reading / data distribution processing procedure and the slot sorting processing procedure are registered as candidates in accordance with the storage node group of the table to be divided and stored. In step 22137,
A slot sort processing procedure, an N-way merge processing procedure, and a matching processing procedure are registered as candidates corresponding to the combination processing node group. Note that the slot sort process is a process in which each row in a page is managed by a slot positioned at an offset from the top of the page, and refers to a sort process in a page for a page in which data is stored. Row is accessible in ascending order. The N-way merge process is a process of using a N-way buffer, inputting N sort runs at each merge stage, and finally creating one sort run by the tournament method. In step 22138, the request data output procedure is registered in the request data output node. Step 2
In 2139, it is checked whether or not the evaluation has been completed for the decomposition result. If all the evaluations have not been completed, the process returns to step 22136, and if all the evaluations have been completed, the process is terminated.

FIG. 17 is a flowchart of the code generation 222. In step 2220, it is checked whether or not the processing procedure candidate is unique. If not unique, step 22
Then, the process proceeds to step 2223 if it is unique. In step 2221, optimization information including column value distribution information and the like is embedded in the processing procedure. In step 2222, a data structure for selecting a processing procedure based on the constant assigned at the time of executing the query is created. In step 2223, the processing procedure is developed into an executable form. Then, the process ends.

FIG. 18 is a flowchart of the inquiry execution process 410. First, a processing procedure to be executed in each node group is determined by the dynamic runtime optimization 223 based on the assigned constant. Next, this processing procedure is interpreted and executed by code interpretation execution 224. Then, the process ends.

FIG. 19 is a flowchart of the dynamic optimization process 223. In step 22300, a dynamic load control process is executed (22300). Step 22301
Then, it is checked whether the created processing procedure is single. If single, the process ends. If not, go to step 22302. In step 22302, a selectivity is calculated based on the substituted constant. In step 22303, it is checked whether or not the processing procedure candidate includes a parallel processing procedure. Step 22 if included
Proceed to 304, if not included, step 22308
Proceed to. In step 22304, optimization information (column value distribution information of a join column, the number of rows of a table to be accessed, the number of pages, and the like) is input from the dictionary. In step 22305, a processing time for data extraction / data distribution is calculated in consideration of each system characteristic. In step 22306, the number p of nodes to be assigned to the combining process is determined from the processing time. In step 22307,
Create data distribution information based on optimization information. In step 22308, a processing procedure is selected according to the access path selection criteria, and the process ends.

FIG. 20 is a flowchart of the code interpretation execution 224. In step 22400, it is checked whether or not the data is to be fetched / distributed. If it is a data extraction / data distribution process, the process proceeds to step 22401; otherwise, the process proceeds to step 22405. In step 22401, the database is accessed and the conditional expression is evaluated. Step 224
In 02, data is set in a buffer for each node based on the data distribution information. In step 22403, it is checked whether or not the buffer of the node is full. If it is full, go to step 22404; if not, go to step 22420. In step 22404, the data is transferred to the corresponding node in a page format,
Proceed to 420.

In step 22405, it is checked whether or not slot sort processing is being performed. If it is a slot sort process, the process proceeds to step 22406; if not, the process proceeds to step 22409. In step 22406, page format data is received from another node. In step 22407, a slot sort process is executed. In step 22408, the slot sort processing result is temporarily stored, and the flow advances to step 22420.

In step 22409, it is checked whether or not the process is an N-way merge process. If the process is an N-way merge process, the process proceeds to step 22410. If the process is not an N-way merge process, the process proceeds to step 22412. In step 22410, an N-way merge process is performed. Step 2241
In step 1, the N-way merge processing result is temporarily stored, and the process proceeds to step 22420.

In step 22412, it is checked whether or not the matching process is performed. If it is the matching process, the process proceeds to step 22413; if not, the process proceeds to step 22416. In step 22413, both sort lists are matched, and data is set in the output buffer. In step 22414, it is checked whether the output buffer is full. If full, step 22415
Proceed to. If it is not full, go to step 22420.
In step 22415, the data is transferred to the request data output node in a page format, and the flow advances to step 22420.

In step 22416, it is checked whether or not the requested data output processing has been performed. If it is the requested data output process, the process proceeds to step 22417; if not, the process proceeds to step 22420. In step 22417, it is checked whether or not page format data is transferred from another node. If there is a transfer, the process proceeds to step 22418; otherwise, the process proceeds to step 22419. In step 22418, page format data is received from another node. In step 22419, the result of the inquiry processing is output to the application program.

In step 22420, it is checked whether the BES is being executed. Step 22 if running in BES
Proceed to 421, and end if not executing in BES. In step 22421, information for estimating the processing load such as the number of access pages, the number of hit rows, the number of times of communication, etc.
Notify S and terminate.

FIG. 21 is a flowchart of the data loading process 210. Before describing each step, the concept will be described. The data loading method includes a data placement that emphasizes the target response time that keeps the time required to scan the entire table within a certain time, a data placement that emphasizes the expected parallelism that is optimized for m-page access, and a complete volume division by the user. There is a user-designated data arrangement by designated user control. In the target response time emphasis data arrangement, first, the number of pages required to store the rows of the entire table is obtained. Next, the upper limit of the number of pages to be stored in the disk of each division that can be accessed in parallel is determined. The access is premised on batch input (for example, 10 pages) if necessary. Number of disks, IOS
The load distribution is determined according to the combination of the number of units and the number of BES units. If there is a key range division, the key range division section is re-divided by the upper limit number of pages, and the divided sections are stored in the respective divided disks. This key range division will be described later in detail with reference to FIG.

In the arrangement of data with an emphasis on expected parallelism, it depends on the size of m. When there is a key range division, the number of sub-key range storage pages s for each key range division unit is s based on the size of m and the expected parallelism p.
(= M / p) is determined, and is stored in each divided disk in units of s pages. The method of calculating the expected parallelism p is calculated by the square root of the ratio obtained by dividing the response time by the overhead of each node. When the ratio is 10, the expected degree of parallelism is 3, 100, the expected degree of parallelism is 10, 1000, the expected degree of parallelism is 32, and 10,000, the expected degree of parallelism is 100. When the calculated expected parallelism p exceeds the number of divisions, the number of divisions is adopted (since the maximum number of disks that can be processed is determined by the number of divisions). In the opposite case, the expected parallelism p is adopted as the number of divisions with the number of divisions as the upper limit. Specifically, a trial calculation of a data arrangement optimized for 100 page access is performed. As a premise, batch input is assumed to be 10 pages. Since one I / O time (10 page access) is 300 ms and one I / O overhead is 5.6 ms (56 ksec is required for 10 MIPS performance), the expected parallelism p is about 7 (= √). {300 / 5.6}).
Therefore, sub-key range division is performed for each s = 14 (= 100/7) pages.

The user-specified data arrangement is the same as that of the conventional database management system, and is managed according to the set parameters.

In step 21000, it is checked whether or not the target response time-oriented data arrangement is performed. If not, the process proceeds to step 21001. If the target response time-oriented data is arranged, step 21 is executed.
Proceed to 003. In step 21001, it is checked whether or not the expected parallelism-oriented data arrangement is performed. If it is not the expected parallelism-oriented data arrangement, the process proceeds to step 21002, and if it is the expected parallelism-oriented data arrangement, the process proceeds to step 21010.
In step 21002, it is checked whether or not there is a user designation. If there is a user designation, the process proceeds to step 21016, and if there is no user designation, the process ends.

In step 21003, the number of pages required to store the rows of the entire table is obtained. Step 210
In step 04, the upper limit of the number of pages to be stored in a disk that can be accessed in parallel with a fixed time required for scanning the table is determined. In step 21005, BEs satisfying the above requirements
S, IOS, and disk group are determined. Step 2100
At 6, it is checked whether or not there is a key range division. If there is a key range division, the process proceeds to step 21007, and if there is no key range division, the process proceeds to step 21009. In step 21007, the key range division section is re-divided by a certain upper limit page number. In step 21008, data insertion is performed corresponding to the key range division section, and the processing ends. In step 21009, data insertion is performed by dividing by the upper limit number of pages, and the process ends.

In step 21010, the optimum page access number m is calculated based on the estimated workload. In step 21011, the expected parallelism p is calculated, and the BES, the IOS, and the disk group are determined according to the expected parallelism p. In step 21012, it is checked whether there is a key range division. If there is a key range division, the process proceeds to step 21013. If there is no key range division, the process proceeds to step 21015. In step 21013, the number of stored pages s (= m / p) in sub-key range units is calculated.
In step 21014, the sub-key range is divided in units of s pages, data is inserted into each disk, and the process ends.

In step 21015, data is inserted by dividing by the number of s pages, and the process ends.

In step 21016, the user-specified I
Data is inserted into the disk managed by the OS, and the process ends.

FIG. 22 is a flowchart of the dynamic load control process 211. In step 21100, the presence or absence of load imbalance (access concentration / discretization) is detected. That is, the D executed per unit time per node
A bottleneck from the distribution of the B processing load (the number of processing steps (DB processing, I / O processing, communication processing), processor performance (converted to processing time), and I / O count (converted to input / output time)) Resources (processors (BES, IOS),
Disk) is detected, the DB process is expanded into an SQL statement, and the access status to each resource is classified in table units. If a load imbalance is detected, the process proceeds to step 21101. If no load imbalance is detected, the process ends. In step 21101, the BES is obtained from the access distribution information.
Is to be added or deleted, or the IOS / disk pair is to be added or deleted. If addition or deletion is necessary, the process proceeds to step 21102; otherwise, the process ends. In step 21102, it is checked whether or not to add. If it is added, the process proceeds to step 21103. If not, the process proceeds to step 2112.

In step 21103, it is checked whether the system is online. If online, step 21104
Proceed to. If not online, step 21105
Proceed to. In step 21104, the key range of the table managed by the target BES group is closed. In step 21105, a new BES is allocated. Step 2
At 1106, the lock information and the directory information are taken over. In step 21107, rewriting of dictionary information necessary for node distribution control is performed by DS7.
Instruct 1 In step 21108, it is checked whether an IOS exists. If not, step 2
Proceed to 1109, and if present, proceed to step 21110. This step is inserted in order to cope with both the system configuration where the IOS exists and the system configuration where the IOS does not exist with the same software. In step 21109, a new BES is obtained from the target BES group.
Move data to groups. In step 21110, it is checked whether it is online. If online, the process proceeds to step 21111. If not online, the process ends. In step 21111, the block of the key range of the table managed by the target BES group is released, and the process ends.

In step 21112, it is checked whether or not online. If online, step 21113
Proceed to. If not online, step 21114
Proceed to. In step 21113, the key range of the table managed by the target BES group is closed. In step 21114, the BES to be degenerated is determined. In step 21115, the lock information and the directory information are taken over. In step 21116, rewriting of dictionary information necessary for node
Instruct 71. In step 21117, it is checked whether or not the IOS exists. If it does not exist, the process proceeds to step 21118, and if it does exist, the process proceeds to step 21119. In step 21118, data is evicted from the degenerate BES group. In step 21119, it is checked whether the user is online. If online, step 211
Proceed to 20. If not online, the process ends. In step 21120, the block of the key range of the table managed by the target BES group is released, and the process ends.

FIG. 23 is a conceptual diagram of a data loading process using key range division. The already divided number is “4”.
Also, the column values v1 to v6 of the database take the appearance frequency as shown in FIG. At the time of initial data loading, only one BES 731 is required. If the number of pages to be stored is associated with the disk of each of the partitions 810 to 840 up to the upper limit of the number of pages, the column values v1 to v
2 are stored in the disk of the division 810, and the column values v2 to
v3 is stored on the disks of partitions 820 and 830,
The column values v3 to v5 are stored in the disks of the division 840, and the column values v5 to v6 are stored in another disk group. At the time of initial data loading, directory information for each disk is created in order to manage pages stored in each disk. When using the BESs 732 to 734 according to the load at the time of accessing the database, the database is accessed using the directory information of each disk corresponding to each BES.

The above-described processing may be implemented in combination with the following embodiments. In order to facilitate the movement of rows between nodes, the row identifier does not include position information such as BES.
In the BES, a physical position of a row is specified by combining directory information for specifying a table division position and a row identifier. Row movement is dealt with by rewriting directory information. A structure corresponding to reorganization or row movement is provided, and even if a BES is dynamically added, processing can be divided by taking over directory information and lock information. In addition, when replica management of a database is required, a double storage area is required. Regardless of whether the primary copy and the backup copy are managed by the same IOS and BES, the access load to the disk is almost doubled. And it is sufficient. In addition, disk, IOS, B
In the event of a failure such as ES, disconnect from online processing and connect to online after recovery. The blockage management method differs depending on each node. When a disk failure occurs, the key range stored on this disk is closed. If a backup copy exists (if the same IOS (mirror disk), a backup copy needs to be acquired under the control of another IOS (data replica)), the process is distributed. When an IOS failure occurs, the key range stored in the IOS is closed. If a backup copy exists (it is necessary to obtain a backup copy under the management of another IOS (data replica)), the process is distributed. When a BES failure occurs, the key range managed by the BES is closed. If the IOS exists, a new BES is allocated, the lock information is taken over,
After rewriting the dictionary information necessary for the node distribution control, the processing is continued.

The present invention is not limited to the combined use of the rule using the statistical information and the cost evaluation. If a processing procedure for giving appropriate database reference characteristic information can be obtained, for example, only the cost evaluation, only the rule use, The present invention can also be applied to a database management system that performs optimization processing such as simultaneous use of cost evaluation and rule use.

The present invention can be realized through a tightly coupled / loosely coupled multiprocessor system software system of a large computer, or a tightly coupled / loosely coupled multiprocessor system in which a dedicated processor is prepared for each processing unit. It is also possible to realize through. Further, the present invention is applicable to a uniprocessor system as long as parallel processes are allocated for each processing procedure. Further, the present invention is also applicable to a configuration in which a plurality of processors share a plurality of disks with each other.

[0072]

According to the database management method of the present invention, the system configuration can be adapted to the load, an expected degree of parallelism can be obtained, and a high-speed inquiry can be realized.

[Brief description of the drawings]

FIG. 1 is a configuration diagram showing a parallel database system according to an embodiment of the present invention.

FIG. 2 is a conceptual diagram illustrating a database division management method according to the present invention.

FIG. 3 is a conceptual diagram of an optimal node distribution (when there is an IOS) according to the database division management method of the present invention.

FIG. 4 is a conceptual diagram of optimal node distribution (when there is no IOS) according to the database division management method of the present invention.

FIG. 5 is a configuration diagram of an FES.

FIG. 6 is a configuration diagram of a BES.

FIG. 7 is a configuration diagram of an IOS.

FIG. 8 is a configuration diagram of a DS.

FIG. 9 is a configuration diagram of a JS.

FIG. 10 is a flowchart of a process of a system control unit.

FIG. 11 is a flowchart of an inquiry analysis process.

FIG. 12 is a flowchart of a query analysis process.

FIG. 13 is a flowchart of a static optimization process.

FIG. 14 is a flowchart of a predicate selection rate estimation process.

FIG. 15 is a flowchart of an access path pruning process.

FIG. 16 is a flowchart of processing for generating a processing procedure candidate.

FIG. 17 is a flowchart of a code generation process.

FIG. 18 is a flowchart of an inquiry execution process.

FIG. 19 is a flowchart of a dynamic optimization process.

FIG. 20 is a flowchart of a code interpretation execution process.

FIG. 21 is a flowchart of a data load process.

FIG. 22 is a flowchart of a dynamic load control process.

FIG. 23 is a conceptual diagram of dynamic load control.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Parallel database system 10, 11 ... Application program, 20 ... Database management system 21 ... System control part, 210 ... Data load processing,
210: Dynamic load control processing 22: Logical processing unit, 220: Query analysis, 221: Static optimization processing, 222: Code generation, 223: Dynamic optimization processing, 224: Code interpretation execution 30: Operating system, 40 ... Database 70 IOS, 71 JS 72 DS 73 BES 75 FES 80, 81, 82 Disk 90 Interconnection network

──────────────────────────────────────────────────続 き Continuing from the front page (72) Inventor Shunichi Torii 1099 Ozenji Temple, Aso-ku, Kawasaki City, Kanagawa Prefecture Hitachi, Ltd. System Development Laboratory (56) References JP-A-63-318628 (JP, A) Asano, Outside 3 “High-speed Database Machine HDM Architecture” Information Processing Society of Japan Research Report (89-ARC-781), Vol. 89, No. 74, 1989 (Heisei 1-9-19) “Special Feature DBMS Technology for Parallel Machines Aiming for Practical Use in the Mid-90s”, Nikkei Electronics, 586, pp. 91-106 (Heisei 5-7-19) (58) Field surveyed (Int. Cl. ⁷ , DB name) G06F 17/30 JICST file (JOIS)

Claims (15)

(57) [Claims] A plurality of key ranges that are set and a storage device;
When storing data in a database by associating the data with a plurality of data storage areas provided in the
The above data is stored in the data storage area corresponding to the key range
If stored, and enter a request for division of the key range, the key
Divides the range and stores the above divided key range as data
Database management method characterized by associating with an area
Law . 2. The database management method according to claim 1, wherein
And select at least one of the divided key ranges
-Supports data storage areas not associated with ranges
A database management method characterized by attaching . 3. The database management method according to claim 2, wherein
The data corresponding to the divided key range
In the data storage area associated with the divided key range
A database management method characterized by storing . 4. The database management method according to claim 2, wherein
The data corresponding to the divided key range
Data storage area associated with the key range that needs to be split
Database management method characterized by deletion from the domain
Law . 5. A storage device comprising: a plurality of set key ranges;
When the key range needs to be divided , a plurality of data storage areas
Divide the key range and store it in the data storage area.
A database management method characterized by applying . 6. The database management method according to claim 5, wherein
And select at least one of the divided key ranges
-Supports data storage areas not associated with ranges
A database management method characterized by attaching . 7. A plurality of set key ranges and storage.
When a request to divide the key range is input by associating with a plurality of data storage areas provided in the device,
Divides the range and stores the above divided key range as data
Database management side, characterized in that associated to the area
Law . 8. The database management method according to claim 7, wherein
And select at least one of the divided key ranges
-Supports data storage areas not associated with ranges
A database management method characterized by attaching . 9. A storage device comprising: a plurality of set key ranges;
When storing data in a database by associating the data with a plurality of data storage areas provided in the
The above data is stored in the data storage area corresponding to the key range
When a request to store and add a key range is received,
Information indicating the range is included in the request, and the key range and
Data storage areas are associated with each other.
Source management method . 10. A plurality of set key ranges and storage.
When storing data in a database by associating the data with a plurality of data storage areas provided in the device,
The above data is stored in the data storage area corresponding to the key range
If a request to store and split the key range is received,
Information indicating the first key range, which is the original key range
A value dividing the first key range and a divided key
First data storage area for storing data corresponding to a range
Information indicating the data area and the second data storage area is included in the request.
, Not more than the value to be divided in the first key range
The second key range and the first key range
The third range that is greater than or equal to the value to be divided
The first key range is divided into a key range of
Associating the second key range with the first data storage area
The third key range is stored in the second data storage area.
A database management method, characterized by associating with a database . 11. A plurality of set key ranges and storage.
When storing data in a database by associating the data with a plurality of data storage areas provided in the device,
The above data is stored in the data storage area corresponding to the key range
If a request to store and merge key ranges is received,
The request includes information indicating the key range, and the
Merged into one key range and the merged key
Characterized in that the image and the data storage area are associated with each other.
Database management method . 12. A plurality of set key ranges and storage.
When storing data in a database by associating the data with a plurality of data storage areas provided in the device,
The above data is stored in the data storage area corresponding to the key range
Storing, when receiving a request to delete the key range, to the deleted
Information indicating the key range to be deleted should be included in the request,
Data storage area associated with the key range and the deletion
Delete the information that associates the key range with
Characteristic database management method . 13. A plurality of set key ranges and storage.
When a request to divide a key range is received and associated with a plurality of data storage areas provided in the device,
Information indicating the first key range, which is the original key range
A value dividing the first key range and a divided key
First data storage area for storing data corresponding to a range
Information indicating the data area and the second data storage area is included in the request.
, Not more than the value to be divided in the first key range
The second key range and the first key range
The third range that is greater than or equal to the value to be divided
The first key range is divided into a key range of
Associating the second key range with the first data storage area
The third key range is stored in the second data storage area.
A database management method, characterized by associating with a database . 14. A plurality of set key ranges and storage.
When a request for associating a key range with a plurality of data storage areas provided in the device and receiving a
The request includes information indicating the key range, and the
Merged into one key range and the merged key
Characterized in that the image and the data storage area are associated with each other.
Database management method . 15. A plurality of set key ranges and storage.
Associating the multiple data storage area provided in the device, when receiving a request to delete the key range, to the deleted
Information indicating the key range to be deleted should be included in the request,
Data storage area associated with the key range and the deletion
Delete the information that associates the key range with
Characteristic database management method .