parallel_clause

Purpose

The parallel_clause lets you parallelize the creation of a database object and set the default degree of parallelism for subsequent queries of and DML operations on the object.

You can specify the parallel_clause in the following statements:

CREATE VECTOR INDEX: (see CREATE VECTOR INDEX).

See Also: Oracle Database PL/SQL Packages and Types Reference for information on the DBMS_PARALLEL_EXECUTE package, which provides methods to apply table changes in chunks of rows. Changes to each chunk are independently committed when there are no errors.

Syntax

parallel_clause::=

Description of the illustration parallel_clause.gif

Semantics

This section describes the semantics of the parallel_clause. For additional information, refer to the SQL statement in which you set or reset parallelism for a particular database object or operation.

Note: The syntax of the parallel_clause supersedes syntax appearing in earlier releases. The superseded syntax is still supported for backward compatibility, but may result in slightly different behavior from that documented.

The database interprets the parallel_clause based on the setting of the PARALLEL_DEGREE_POLICY initialization parameter. When that parameter is set to AUTO, the parallel_clause is ignored entirely, and the optimizer determines the best degree of parallelism for all statements. When PARALLEL_DEGREE_POLICY is set to either MANUAL or LIMITED, the parallel_clause is interpreted as follows:

NOPARALLEL

Specify NOPARALLEL for serial execution. This is the default.

PARALLEL

Specify PARALLEL for parallel execution.

PARALLEL integer

integer is optional and specifies the degree of parallelism you require (number of parallel threads) in the parallel operation. Each parallel thread may use one or two parallel execution servers. If you do not specify integer, the database calculates the optimum degree of parallelism.

Notes on the parallel_clause

The following notes apply to the parallel_clause:

See Also: Oracle Database VLDB and Partitioning Guide for more information on parallelized operations, and “Creating a Table: Parallelism Examples