Re: How batch processing works
| От | Lok P |
|---|---|
| Тема | Re: How batch processing works |
| Дата | |
| Msg-id | CAKna9Vbt1VJu7Oa8FTWasgby+-kJn7omOhbfmWzkdpVwBiqNzQ@mail.gmail.com обсуждение исходный текст |
| Ответ на | Re: How batch processing works (Michał Kłeczek <michal@kleczek.org>) |
| Список | pgsql-general |
On Sat, Sep 21, 2024 at 9:51 AM Michał Kłeczek <michal@kleczek.org> wrote:
Hi,
> On 19 Sep 2024, at 07:30, Lok P <loknath.73@gmail.com> wrote:
>
[snip]
>
> Method-4
>
> INSERT INTO parent_table VALUES (1, 'a'), (2, 'a');
> INSERT INTO child_table VALUES (1,1, 'a'), (1,2, 'a');
> commit;
I’ve done some batch processing of JSON messages from Kafka in Java.
By far the most performant way was to:
1. Use prepared statements
2. Parse JSON messages in Postgres
3. Process messages in batches
All three can be achieved by using arrays to pass batches:
WITH parsed AS (
SELECT msg::json FROM unnest(?)
),
parents AS (
INSERT INTO parent SELECT … FROM parsed RETURNING ...
)
INSERT INTO child SELECT … FROM parsed…
Not the single parameter that you can bind to String[]
Hope that helps.
Got your point.
But wondering why we don't see any difference in performance between method-2 and method-3 above. So does it mean that,I am testing this in a wrong way or it's the expected behaviour and thus there is no meaning in converting the row by row inserts into a bulk insert, but just changing the commit frequency will do the same job in a row by row insert approach?
В списке pgsql-general по дате отправления: