Updating large tables nora zehetner dating
It is a minimally logged operation in simple and Bulk-logged recovery model., the PL/SQL compiler translated your source code to system code without applying many changes to improve performance.The best approach I've imagined is to create a HEAP table and for each cycle, fill it with the next5000 primary keys from the source table, SELECT using a join against the HEAP table, the UPDATE onthe same join when the Lucene indexing is successful. I looked at using LOCK IN SHARE MODE, but I don't see how to be surethat a SELECT ... statement will select the same messages as UPDATE... unless Ilock the whole table, which seems needless.The large update has to be broken down to small batches, like 10,000, at a time. It is also easy to restart in case of interruption.As callout A in Listing 1 shows, you can trick the WHILE loop into initially executing by including a meaningless SET statement right before the WHILE condition.After that, the WHILE condition is dependent on the UPDATE statement’s row count.Disabling After delete triggers will considerably increase the query performance. Replacing Update statement with a Bulk-Insert operation An update statement is a fully logged operation and thus it will certainly take considerable amount of time if millions of rows are to be updated.The fastest way to speed up the update query is to replace it with a bulk-insert operation.
Updating a large table in Postgres is not as straightforward as it seems.
After a group is added to the Lucene index, I want to update a column that is a flag to show thatthe record is done (TINYINT(1) UNSIGNED NOT NULL).
This is to support incremental indexing (and sothat if an indexing process fails or is interrupted, it will resume with minimal redundancy).
Now, PL/SQL uses an optimizer that can rearrange code for better performance. In rare cases, if the overhead of the optimizer makes compilation of very large applications too slow, you can lower the optimization by setting the compilation parameter , the PL/SQL compiler seeks opportunities to inline subprograms beyond those that you specify.
If a particular subprogram is inlined, performance almost always improves.
When you are faced with updating most or all rows in a large table and you want to avoid locking out users, you can use the TOP clause to limit the transaction size.