Method and apparatus for implementing parallel operations in a database management system

a database management system and parallel operation technology, applied in the field of parallel processing, can solve the problems of limiting the use of the location of the data as a means of partitioning, the inability to dynamically adjust the type and degree of parallelism, and the difficulty of mixing parallel queries and sequential updates in one transaction without requiring a two-phase commi

Inactive Publication Date: 2011-08-30
ORACLE INT CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0011]The present invention implements parallel processing in a Database Management System. The present invention does not rely on physical partitioning to determine the degree of parallelism. Further, the present invention does not need to use read lock, or require a two-phased commit in transaction processing because transaction and recovery information is located on multiple disks.

Problems solved by technology

However, using the location of the data as a means for partitioning is limiting.
Thus, there is no ability to dynamically adjust the type and degree of parallelism based on changing factors (e.g., data load or system resource availability).
Further, using physical partitioning makes it difficult to mix parallel queries and sequential updates in one transaction without requiring a two phase commit.
However a shared everything hardware architecture cannot scale.
This bus has limited bandwidth and the current state of the art of shared everything systems does not provide for a means of increasing the bandwidth of the shared bus as more processors and memory are added.

Method used

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  • Method and apparatus for implementing parallel operations in a database management system
  • Method and apparatus for implementing parallel operations in a database management system
  • Method and apparatus for implementing parallel operations in a database management system

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[0154]Referring to FIG. 3C, each dataflow scheduler starts executing the deepest, leftmost leaf in the DFO tree. Thus, the employee scan DFO directs its underlying nodes to produce rows. Eventually, the employee table scan DFO is told to begin execution. The employee table scan begins in the ready state because it is not consuming any rows. Each table scan slave DFO SQL statement, when parsed, generates a table scan row source in each slave.

[0155]When executed, the table scan row source proceeds to access the employee table scan in the DBMS (e.g., performs the underlying operations required by the DBMS to read rows from a table), gets a first row, and is ready to transmit the row to its output table queue. The slaves implementing the table scan replies to the data flow scheduler that they are ready. The data flow scheduler monitors the count to determine when all of the slaves implementing the table scan have reached the ready state.

[0156]At this point, the data flow scheduler deter...

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Abstract

The present invention implements parallel processing in a Database Management System. The present invention provides the ability to locate transaction and recovery information at one location and eliminates the need for read locks and two-phased commits. The present invention provides the ability to dynamically partition row sources for parallel processing. Parallelism is based on the ability to parallelize a row source, the partitioning requirements of consecutive row sources and the entire row source tree, and any specification in the SQL statement. A Query Coordinator assumes control of the processing of a entire query and can execute serial row sources. Additional threads of control, Query Server, execute a parallel operators. Parallel operators are called data flow operators (DFOs). A DFO is represented as structured query language (SQL) statements and can be executed concurrently by multiple processes, or query slaves. A central scheduling mechanism, a data flow scheduler, controls a parallelized portion of an execution plan, and can become invisible for serial execution. Table queues are used to partition and transport rows between sets of processes. Node linkages provide the ability to divide the plan into independent lists that can each be executed by a set of query slaves. The present invention maintains a bit vector that is used by a subsequent producer to determine whether any rows need to be produced to its consumers. The present uses states and a count of the slaves that have reached these states to perform its scheduling tasks.

Description

[0001]This application is one of two reissue patent applications that are based on U.S. Pat. No. 5,857,180. This reissue patent application and reissue patent application Ser. No. 10 / 153,983 are both divisional reissue patent applications based on U.S. Pat. No. 5,857,180. U.S. Pat. No. 5,857,180 is a continuation of application Ser. No. 08 / 441,527, filed May 15, 1995, now abandoned, which is a continuation of application Ser. No. 08 / 127,585, filed Sep. 27, 1993 now abandoned.BACKGROUND OF THE INVENTION[0002]1. Field of the Invention[0003]This invention relates to the field of parallel processing in a database environment.[0004]2. Background Art[0005]Sequential query execution uses one processor and one storage device at a time. Parallel query execution uses multiple processes to execute in parallel suboperations of a query. For example, virtually every query execution includes some form of manipulation of rows in a relation, or table of the DBMS. Before any manipulation can be done,...

Claims

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Application Information

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Patent Type & Authority Patents(United States)
IPC IPC(8): G06F17/00G06F15/16G06F9/46
CPCG06F9/466Y10S707/99934Y10S707/99935Y10S707/99932Y10S707/99933
Inventor HALLMARK, GARYLEARY, DANIEL
Owner ORACLE INT CORP
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