Horton

Re: Parallel Append implementation

Robert Haas <robertmhaas@gmail.com>

View thread View on postgr.es
From: Robert Haas <robertmhaas@gmail.com>
To: Amit Khandekar <amitdkhan.pg@gmail.com>
Cc: Ashutosh Bapat <ashutosh.bapat@enterprisedb.com>, pgsql-hackers <pgsql-hackers@postgresql.org>
Date: 2017-03-13T14:18:10Z
Lists: pgsql-hackers 
On Mon, Mar 13, 2017 at 7:46 AM, Robert Haas <robertmhaas@gmail.com> wrote:
> On Mon, Mar 13, 2017 at 4:59 AM, Amit Khandekar <amitdkhan.pg@gmail.com> wrote:
>> I agree that we should preferably have the non-partial plans started
>> first. But I am not sure if it is really worth ordering the partial
>> plans by cost. The reason we ended up not keeping track of the
>> per-subplan parallel_worker, is because it would not matter  much ,
>> and we would just equally distribute the workers among all regardless
>> of how big the subplans are. Even if smaller plans get more worker,
>> they will finish faster, and workers would be available to larger
>> subplans sooner.
>
> Imagine that the plan costs are 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, and 10
> and you have 2 workers.
>
> If you move that 10 to the front, this will finish in 10 time units.
> If you leave it at the end, it will take 15 time units.

Oh, never mind.  You were only asking whether we should sort partial
plans.  That's a lot less important, and maybe not important at all.
The only consideration there is whether we might try to avoid having
the leader start in on a plan with a large startup cost.

-- 
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company

Commits

  1. Update parallel.sgml for Parallel Append

  2. Support Parallel Append plan nodes.

  3. Remove BufFile's isTemp flag.

  4. Improve comments for parallel executor estimation functions.

  5. Separate reinitialization of shared parallel-scan state from ExecReScan.

  6. Eat XIDs more efficiently in recovery TAP test.

  7. Avoid syntax error on platforms that have neither LOCALE_T nor ICU.

  8. Preparatory refactoring for parallel merge join support.