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This article will explain in detail how to achieve a large number of data in the database fast insertion method, Xiaobian feel quite practical, so share to everyone for a reference, I hope you can read this article after harvest.

1 Environmental construction

Build a source table of tens of millions and insert operations into an empty table.

Reference metric: actual time to insert action completion.

SQL> drop table test_emp cascadeconstraints purge;Table dropped.SQL> create table test_emp as select *from emp;Table created.SQL> begin 2 for i in 1.. 10 loop 3 insert into test_emp select *from test_emp; --batch quantity dml, Suggestion forall 4 end loop; 5 end; 6 /PL/SQL procedure successfully completed.SQL> select count(*) from test_emp; COUNT(*)------- 14336SQL> begin 2 for i in 1.. 10 loop 3 insert into test_emp select *from test_emp; 4 end loop 5 ; 6 end; 7 /PL/SQL procedure successfully completed.SQL> select count(*) from test_emp; COUNT(*)---------- 14680064 2 only appendSQL> set timing onSQL> show timing ONSQL> insert /*+ append */ into test_goalselect * from test_emp;14680064 rows created.

Elapsed: 00:00:20.72

There is no closed log, so the time is the longest.

3 append+nologgingSQL> truncate table test_goal;Table truncated.Elapsed: 00:00:00.11SQL> insert /*+ append */ into test_goalselect * from test_emp nologging;14680064 rows created.

Elapsed: 00:00:04.82

It is found that the log has a great impact on insertion, and the time of adding nlogging is significantly shortened; of course, this table has no index, constraint, etc., so it is not studied here.

4 append+nologging+parallelSQL> truncate table test_goal;Table truncated. Elapsed: 00:00:00.09SQL> insert /*+ parallel(2) append */into test_goal select * from test_emp nologging;14680064 rows created.

Elapsed: 00:00:02.86

Here on the basis of 3 plus parallel, performance basically reached the limit, 150 million data insertion time control in about 3S. Parallel In the case of server performance support, you can increase the parallel parameter.

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