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We can see that MERGE performed less well than our two-part SQL solution; with it taking over twice as long. We can repeat the test against a typical PL/SQL-coded merge (common in older applications).We will replace the two-part SQL solution with a PL/SQL loop that will attempt an update first and insert only if the update affects no rows.In addition, we can achieve some minor gains by ordering the WHEN clauses in a MERGE according to which event is the most likely (i.e.most frequent first), although at our sample data volume, the effects of this are not generally noticeable.In versions prior to 9i, we would have to code this scenario either in separate bulk SQL statements or in PL/SQL.We will compare MERGE to these methods later in this article.The alternative to this would be to insert first and only update when a DUP_VAL_ON_INDEX exception was raised (a primary or unique key is required for this to work).

The update is written as an updateable in-line view which is often the fastest technique for bulk updating one table from another.We could speed up the latter by using bulk processing, but we wouldn't be able to achieve a reduction of two-thirds required to match the MERGE. This means that for each source row, Oracle needs to be able to identify a single target record for update.The simplest method of ensuring that the MERGE is key-preserved is to join source and target according to the primary key of the target.Cached Commit SCN refere 286 56,854 56,568 STAT..table scan blocks gotten 951 86,889 85,938 STAT..buffer is not pinned cou 975 86,924 85,949 STAT.block changes 175,740 262,562 86,822 STAT..index fetch by key 0 86,891 86,891 STAT.work - consistent rea 967 129,991 129,024 STAT..execute count 13 130,338 130,325 STAT..calls to get snapshot sc 28 130,355 130,327 STAT..consistent gets - examin 230 130,962 130,732 STAT..recursive calls 567 218,074 217,507 STAT..consistent gets 1,469 260,988 259,519 LATCH.library cache pin 119 261,164 261,045 LATCH.library cache 166 261,675 261,509 STAT..session logical reads 134,411 438,136 303,725 LATCH.cache buffers chains 579,034 1,190,456 611,422 STAT.size 23,372,796 32,740,676 9,367,880 Run1 latches total versus run2 -- difference and pct Run1 Run2 Diff Pct 687,702 1,889,744 1,202,042 36.39% PL/SQL procedure successfully completed.It is probably no surprise that the MERGE was significantly faster than the PL/SQL solution.

Updating multiple rows oracle