Re: How batch processing works

On Thu, Sep 19, 2024 at 5:24 AM Lok P <loknath(dot)73(at)gmail(dot)com> wrote:

>
> On Thu, Sep 19, 2024 at 11:31 AM Ron Johnson <ronljohnsonjr(at)gmail(dot)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;
>>>
>>
>> If I knew that I had to load a structured input data file (even if it had
>> parent and child records), this is how I'd do it (but probably first try
>> and see if "in-memory COPY INTO" is such a thing).
>>
>>
>
> I was trying to reproduce this behaviour using row by row commit vs just
> batch commit vs true batch insert as you mentioned, i am not able to see
> any difference between "batch commit" and "true batch insert" response. Am
> I missing anything?
>
> [snip]

> DO $$
> DECLARE
> num_inserts INTEGER := 100000;
> batch_size INTEGER := 50;
> start_time TIMESTAMP;
> end_time TIMESTAMP;
> elapsed_time INTERVAL;
> i INTEGER;
> BEGIN
> -- Method 1: Individual Inserts with Commit after every Row
> start_time := clock_timestamp();
>
> FOR i IN 1..num_inserts LOOP
> INSERT INTO parent_table VALUES (i, 'a');
> COMMIT;
> END LOOP;
>
> end_time := clock_timestamp();
> elapsed_time := end_time - start_time;
> INSERT INTO debug_log (method1, start_time, end_time, elapsed_time)
> VALUES ('Method 1: Individual Inserts with Commit after every Row',
> start_time, end_time, elapsed_time);
>
> -- Method 2: Individual Inserts with Commit after 100 Rows
> start_time := clock_timestamp();
>
> FOR i IN 1..num_inserts LOOP
> INSERT INTO parent_table2 VALUES (i, 'a');
> -- Commit after every 100 rows
> IF i % batch_size = 0 THEN
> COMMIT;
> END IF;
> END LOOP;
>
> -- Final commit if not already committed
> commit;
>
> end_time := clock_timestamp();
> elapsed_time := end_time - start_time;
> INSERT INTO debug_log (method1, start_time, end_time, elapsed_time)
> VALUES ('Method 2: Individual Inserts with Commit after 100 Rows',
> start_time, end_time, elapsed_time);
>
> -- Method 3: Batch Inserts with Commit after all
> start_time := clock_timestamp();
>
> FOR i IN 1..(num_inserts / batch_size) LOOP
> INSERT INTO parent_table3 VALUES
> (1 + (i - 1) * batch_size, 'a'),
>
[snip]

> (49 + (i - 1) * batch_size, 'a'),
> (50 + (i - 1) * batch_size, 'a'));
> COMMIT;
> END LOOP;
>
> COMMIT; -- Final commit for all
> end_time := clock_timestamp();
> elapsed_time := end_time - start_time;
> INSERT INTO debug_log (method1, start_time, end_time, elapsed_time)
> VALUES ('Method 3: Batch Inserts with Commit after All', start_time,
> end_time, elapsed_time);
>
> END $$;
>

Reproduce what behavior?

Anyway, plpgsql functions (including anonymous DO statements) are -- to
Postgresql -- single statements. Thus, they'll be faster than
individual calls..

An untrusted language like plpython3u might speed things up even more, if
you have to read a heterogeneous external file and insert all the records
into the db.

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