Hi All,
I have a big table (200G with 728 million records), the table slows down lots
of things. It's time to clean the data up. The requirement is when I delete I
must summarise few columns to a new table for backup purpose. So that mean I
need to go through each row and add the columns' value to the summary table
(the corresponding category).
The table has indexes (multicoumn indexes) before, I removed the indexes
because I read on forum says the indexes heavily reduce the speed of deleting.
That's true if I only delete from the table, but my case is I first SELECT this
row, then add few values to the summary table and then DELETE the row according
to its multiple primary key. This seems to be a bad idea now as it takes very
long time to DELETE the row (as delete needs to find the row first).
Here are the two version of the delete functions, please help to point out how
can I speed it up.
1.
CREATE OR REPLACE FUNCTION summary_delete_table()
RETURNS integer AS
$BODY$
DECLARE
rec
RECORD;
subrec
RECORD;
BEGIN
FOR rec IN
SELECT * FROM tableA limit 100 LOOP
BEGIN
UPDATE
summaryTable set count1 = rec.count1 + rec.count1, count2 =... where category
match;
delete from
tableA where tableA.primaryKeyA=rec.primaryKeyA and
tableA.primaryKeyB=rec.primaryKeyB;
END;
END LOOP;
return 1;
END;
$BODY$
LANGUAGE plpgsql VOLATILE
COST 100;
And then I have a .bat script to loop the above function million times.
2.
CREATE OR REPLACE FUNCTION summary_delete_table()
RETURNS integer AS
$BODY$
DECLARE
rec
RECORD;
td_cursor
CURSOR FOR SELECT * FROM tableA limit 100;
BEGIN
FOR rec IN
td_cursor LOOP
BEGIN
UPDATE summaryTable set count1 = rec.count1 +
rec.count1, count2 =... where category match;
delete from tableA WHERE CURRENT OF td_cursor;
END;
END LOOP;
return 1;
END;
$BODY$
LANGUAGE plpgsql VOLATILE
COST 100;
Method 2 is bit faster but not much, the delete speed is 2478 rows/s for method
2 and 2008 rows/s for method 1.
Any suggestions are welcomed.
BTW, I guess if reindex, it may take few days to finish.
Also, I tried change delete 100 rows at a time and 1000, 2000. The result
showed 1000 is faster than 100 and 2000 a time.
Thanks and Regards,
Haiming
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Haiming Zhang | Engineer | Redflex Group
T +61 3 9674 1868 | F +61 3 9699 3566 | E haiming.zh...@redflex.com.au
31 Market Street, (PO Box 720), South Melbourne VIC 3205, Australia
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