It achieves this by introducing sleep statements after each chunk is updated.
The duration of the sleep statement is proportional to the runtime of the update statement.
Assuming that you are updating a large portion of the rows in bigtable, the most efficient join is a merge join.
To make this as efficient as possible you need the following indexes: clustered index on bigtable(id) - extremely important nonclustered on littletable(id,a) nonclustered on smalltable(id,b) Make sure that bigtable.c is not part of any index, drop indexes if necessary To avoid filling up the transaction log you should perform the update in batches. Also make sure that you have truncate log on chkpt turned ON.
The executes after each chunk and outputs a running total of how many rows have been updated: ``` set @script := " split( : update ad_parameter set scope = -1 where ( name in ( 'parameter_name_a', 'parameter_name_b', 'parameter_name_c' ) or name like 'parameter_prefix_x_%' or name like 'parameter_prefix_y_%' or name like 'parameter_prefix_z_%' ) and scope !
In production, I would estimate it to be from 30 millions to 300 millions.
We cannot use the same code as above with just replacing the DELETE statement with an INSERT statement. --Source table CREATE TABLE source Table ( col A varchar(10) ); --Target table CREATE TABLE target Table ( col A varchar(10) ); INSERT INTO source Table(col A) VALUES('Red'); GO 1000000 declare @rc int; set @rc = 1; --WRONG!
The idea is basically that either this update succeeds or it succeeds or - there is no "not". If I just do an UPDATE table SET flag=0; then Pg will make a copy of every row which must be cleaned up by vaccuum.I sometimes need to do a simple update to ALL rows that resets a status-flag to zero.I don't need to have transactional integrity (but of course if the system crashes, there should be no data corruption.Let’s say you have a table in which you want to delete millions of records.If the goal was to remove all then we could simply use TRUNCATE.