Re: Parallel copy

Bharath Rupireddy <bharath.rupireddyforpostgres@gmail.com>

From: Bharath Rupireddy <bharath.rupireddyforpostgres@gmail.com>
To: vignesh C <vignesh21@gmail.com>
Cc: Ashutosh Sharma <ashu.coek88@gmail.com>, Amit Kapila <amit.kapila16@gmail.com>, Rafia Sabih <rafia.pghackers@gmail.com>, Andres Freund <andres@anarazel.de>, Robert Haas <robertmhaas@gmail.com>, Ants Aasma <ants@cybertec.at>, Tomas Vondra <tomas.vondra@2ndquadrant.com>, Alastair Turner <minion@decodable.me>, Thomas Munro <thomas.munro@gmail.com>, PostgreSQL Hackers <pgsql-hackers@lists.postgresql.org>
Date: 2020-07-23T03:20:51Z
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. Allow WaitLatch() to be used without a latch.

  2. Add %P to log_line_prefix for parallel group leader

  3. Include replication origins in SQL functions for commit timestamp

  4. Avoid useless buffer allocations during binary COPY FROM.

On Wed, Jul 22, 2020 at 7:56 PM vignesh C <vignesh21@gmail.com> wrote:
>
> Thanks for reviewing and providing the comments Ashutosh.
> Please find my thoughts below:
>
> On Fri, Jul 17, 2020 at 7:18 PM Ashutosh Sharma <ashu.coek88@gmail.com>
wrote:
> >
> > Some review comments (mostly) from the leader side code changes:
> >
> > 3) Should we allow Parallel Copy when the insert method is
CIM_MULTI_CONDITIONAL?
> >
> > +   /* Check if the insertion mode is single. */
> > +   if (FindInsertMethod(cstate) == CIM_SINGLE)
> > +       return false;
> >
> > I know we have added checks in CopyFrom() to ensure that if any trigger
(before row or instead of) is found on any of partition being loaded with
data, then COPY FROM operation would fail, but does it mean that we are
okay to perform parallel copy on partitioned table. Have we done some
performance testing with the partitioned table where the data in the input
file needs to be routed to the different partitions?
> >
>
> Partition data is handled like what Amit had told in one of earlier mails
[1].  My colleague Bharath has run performance test with partition table,
he will be sharing the results.
>

I ran tests for partitioned use cases - results are similar to that of non
partitioned cases[1].

parallel workers test case 1(exec time in sec): copy from csv file, 5.1GB,
10million tuples, 4 range partitions, 3 indexes on integer columns unique
data test case 2(exec time in sec): copy from csv file, 5.1GB, 10million
tuples, 4 range partitions, unique data
0 205.403(1X) 135(1X)
2 114.724(1.79X) 59.388(2.27X)
4 99.017(2.07X) 56.742(2.34X)
8 99.722(2.06X) 66.323(2.03X)
16 98.147(2.09X) 66.054(2.04X)
20 97.723(2.1X) 66.389(2.03X)
30 97.048(2.11X) 70.568(1.91X)

With Regards,
Bharath Rupireddy.
EnterpriseDB: http://www.enterprisedb.com