From: | yudhi s <learnerdatabase99(at)gmail(dot)com> |
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To: | pgsql-general <pgsql-general(at)lists(dot)postgresql(dot)org> |
Subject: | update faster way |
Date: | 2024-09-14 03:13:34 |
Message-ID: | CAEzWdqd-22B-bpVdT3yzegiOig9zvJnfJvi=GOMFfHT-Jg8CgQ@mail.gmail.com |
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Lists: | pgsql-general |
Hello,
We have to update a column value(from numbers like '123' to codes like
'abc' by looking into a reference table data) in a partitioned table with
billions of rows in it, with each partition having 100's millions rows. As
we tested for ~30million rows it's taking ~20minutes to update. So if we go
by this calculation, it's going to take days for updating all the values.
So my question is
1) If there is any inbuilt way of running the update query in parallel
(e.g. using parallel hints etc) to make it run faster?
2) should we run each individual partition in a separate session (e.g. five
partitions will have the updates done at same time from 5 different
sessions)? And will it have any locking effect or we can just start the
sessions and let them run without impacting our live transactions?
UPDATE tab_part1
SET column1 = reftab.code
FROM reference_tab reftab
WHERE tab_part1.column1 = subquery.column1;
Regards
Yudhi
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