Horton

Re: PATCH: logical_work_mem and logical streaming of large in-progress transactions

Dilip Kumar <dilipbalaut@gmail.com>

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From: Dilip Kumar <dilipbalaut@gmail.com>
To: Kuntal Ghosh <kuntalghosh.2007@gmail.com>
Cc: vignesh C <vignesh21@gmail.com>, Tomas Vondra <tomas.vondra@2ndquadrant.com>, Amit Kapila <amit.kapila16@gmail.com>, a.kondratov@postgrespro.ru, Peter Eisentraut <peter.eisentraut@2ndquadrant.com>, PostgreSQL Hackers <pgsql-hackers@postgresql.org>
Date: 2019-11-04T10:02:33Z
Lists: pgsql-hackers

Commits

Same data as JSON: GET /api/v1/messages/:b64id/commits the thread's linked commits as JSON, with link sources. API reference →

  1. Tighten the concurrent abort check during decoding.

  2. Improve hash_create()'s API for some added robustness.

  3. Use HASH_BLOBS for xidhash.

  4. Fix initialization of RelationSyncEntry for streaming transactions.

  5. Remove unused function declaration in logicalproto.h.

  6. Add additional tests to test streaming of in-progress transactions.

  7. Fix inline marking introduced in commit 464824323e.

  8. Add support for streaming to built-in logical replication.

  9. Fix the SharedFileSetUnregister API.

  10. Fix comment in procarray.c

  11. Suppress compiler warning in non-cassert builds.

  12. Extend the BufFile interface.

  13. Mark a few logical decoding related variables with PGDLLIMPORT.

  14. Implement streaming mode in ReorderBuffer.

  15. Extend the logical decoding output plugin API with stream methods.

  16. WAL Log invalidations at command end with wal_level=logical.

  17. Immediately WAL-log subtransaction and top-level XID association.

  18. Allow logical replication to transfer data in binary format.

  19. Only superuser can set sslcert/sslkey in postgres_fdw user mappings

  20. Track statistics for spilling of changes from ReorderBuffer.

  21. Add logical_decoding_work_mem to limit ReorderBuffer memory usage.

  22. logical decoding: process ASSIGNMENT during snapshot build

  23. Emit invalidations to standby for transactions without xid.

On Mon, Nov 4, 2019 at 2:43 PM Kuntal Ghosh <kuntalghosh.2007@gmail.com> wrote:
>
> Hello hackers,
>
> I've done some performance testing of this feature. Following is my
> test case (taken from an earlier thread):
>
> postgres=# CREATE TABLE large_test (num1 bigint, num2 double
> precision, num3 double precision);
> postgres=# \timing on
> postgres=# EXPLAIN (ANALYZE, BUFFERS) INSERT INTO large_test (num1,
> num2, num3) SELECT round(random()*10), random(), random()*142 FROM
> generate_series(1, 1000000) s(i);
>
> I've kept the publisher and subscriber in two different system.
>
> HEAD:
> With 1000000 tuples,
> Execution Time: 2576.821 ms, Time: 9.632.158 ms (00:09.632), Spill count: 245
> With 10000000 tuples (10 times more),
> Execution Time: 30359.509 ms, Time: 95261.024 ms (01:35.261), Spill count: 2442
>
> With the memory accounting patch, following are the performance results:
> With 100000 tuples,
> logical_decoding_work_mem=64kB, Execution Time: 2414.371 ms, Time:
> 9648.223 ms (00:09.648), Spill count: 2315
> logical_decoding_work_mem=64MB, Execution Time: 2477.830 ms, Time:
> 9895.161 ms (00:09.895), Spill count 3
> With 1000000 tuples (10 times more),
> logical_decoding_work_mem=64kB, Execution Time: 38259.227 ms, Time:
> 105761.978 ms (01:45.762), Spill count: 23149
> logical_decoding_work_mem=64MB, Execution Time: 24624.639 ms, Time:
> 89985.342 ms (01:29.985), Spill count: 23
>
> With logical decoding of in-progress transactions patch and with
> streaming on, following are the performance results:
> With 100000 tuples,
> logical_decoding_work_mem=64kB, Execution Time: 2674.034 ms, Time:
> 20779.601 ms (00:20.780)
> logical_decoding_work_mem=64MB, Execution Time: 2062.404 ms, Time:
> 9559.953 ms (00:09.560)
> With 1000000 tuples (10 times more),
> logical_decoding_work_mem=64kB, Execution Time: 26949.588 ms, Time:
> 196261.892 ms (03:16.262)
> logical_decoding_work_mem=64MB, Execution Time: 27084.403 ms, Time:
> 90079.286 ms (01:30.079)
So your result shows that with "streaming on", performance is
degrading?  By any chance did you try to see where is the bottleneck?

-- 
Regards,
Dilip Kumar
EnterpriseDB: http://www.enterprisedb.com