On Sat, Sep 14, 2024 at 4:55 PM Peter J. Holzer <hjp-pgsql@xxxxxx> wrote:
Which in turn means that you want as little overhead as possible per
batch which means finding those 5000 rows should be quick. Which brings
us back to Igor's question: Do you have any indexes in place which speed
up finding those 5000 rows (the primary key almost certainly won't help
with that). EXPLAIN (ANALYZE) (as suggested by Laurenz) will certainly
help answering that question.
> And also those rows will not collide with each other. So do you think
> that approach can anyway cause locking issues?
No, I don't think so. With a batch size that small I wouldn't expect
problems even on the live partition. But of course many busy parallel
sessions will put additional load on the system which may or may not be
noticeable by users (you might saturate the disks writing WAL entries
for example, which would slow down other sessions trying to commit).
> Regarding batch update with batch size of 1000, do we have any method exists in
> postgres (say like forall statement in Oracle) which will do the batch dml. Can
> you please guide me here, how we can do it in postgres.
Postgres offers several server side languages. As an Oracle admin you
will probably find PL/pgSQL most familiar. But you could also use Perl
or Python or several others. And of course you could use any
programming/scripting language you like on the client side.
When you said "(the primary key almost certainly won't help with that)", I am trying to understand why it is so ?
I was thinking of using that column as an incrementing filter and driving the eligible rows based on that filter. And if it would have been a sequence. I think it would have helped but in this case it's UUID , so I may not be able to do the batch DML using that as filter criteria. but in that case will it be fine to drive the update based on ctid something as below? Each session will have the range of 5 days of data or five partition data and will execute a query something as below which will update in the batches of 10K and then commit. Is this fine? Or is there some better way of doing the batch DML in postgres plpgsql?
DO $$
DECLARE
l_rowid_array ctid[];
l_ctid ctid;
l_array_size INT := 10000;
l_processed INT := 0;
BEGIN
FOR l_cnt IN 0..(SELECT COUNT(*) FROM part_tab WHERE part_date > '1-sep-2024' and part_date < '5-sep-2024'
) / l_array_size LOOP
l_rowid_array := ARRAY(
SELECT ctid
FROM part_tab
WHERE part_date > '1-sep-2024' and part_date < '5-sep-2024'
LIMIT l_array_size OFFSET l_cnt * l_array_size
);
FOREACH l_ctid IN ARRAY l_rowid_array LOOP
update part_tab
SET column1 = reftab.code
FROM reference_tab reftab
WHERE tab_part1.column1 = reftab.column1
and ctid = l_ctid;
l_processed := l_processed + 1;
END LOOP;
COMMIT;
END LOOP;
END $$;
DECLARE
l_rowid_array ctid[];
l_ctid ctid;
l_array_size INT := 10000;
l_processed INT := 0;
BEGIN
FOR l_cnt IN 0..(SELECT COUNT(*) FROM part_tab WHERE part_date > '1-sep-2024' and part_date < '5-sep-2024'
) / l_array_size LOOP
l_rowid_array := ARRAY(
SELECT ctid
FROM part_tab
WHERE part_date > '1-sep-2024' and part_date < '5-sep-2024'
LIMIT l_array_size OFFSET l_cnt * l_array_size
);
FOREACH l_ctid IN ARRAY l_rowid_array LOOP
update part_tab
SET column1 = reftab.code
FROM reference_tab reftab
WHERE tab_part1.column1 = reftab.column1
and ctid = l_ctid;
l_processed := l_processed + 1;
END LOOP;
COMMIT;
END LOOP;
END $$;
