From: | David Rowley <david(dot)rowley(at)2ndquadrant(dot)com> |
---|---|
To: | Amit Langote <amitlangote09(at)gmail(dot)com> |
Cc: | Alvaro Herrera <alvherre(at)alvh(dot)no-ip(dot)org>, Amit Langote <Langote_Amit_f8(at)lab(dot)ntt(dot)co(dot)jp>, "pgsql-hackers(at)postgresql(dot)org" <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: [HACKERS] path toward faster partition pruning |
Date: | 2018-04-07 01:31:51 |
Message-ID: | CAKJS1f-SON_hAekqoV4_WQwJBtJ_rvvSe68jRNhuYcXqQ8PoQg@mail.gmail.com |
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On 7 April 2018 at 12:43, David Rowley <david(dot)rowley(at)2ndquadrant(dot)com> wrote:
> On 7 April 2018 at 12:35, Amit Langote <amitlangote09(at)gmail(dot)com> wrote:
>> So this same failure occurs on (noting the architecture):
>>
>> Seems to be due to that the hashing function used in partitioning
>> gives different answer for a given set of partition key values than
>> others.
>
> They all look like bigendian CPUs.
I looked at all the regression test diffs for each of the servers you
mentioned and I verified that the diffs match on each of the 7
servers.
Maybe the best solution is to pull those tests out of
partition_prune.sql then create partition_prune_hash and just have an
alternative .out file with the partitions which match on bigendian
machines.
We could also keep them in the same file, but that's a much bigger
alternative file to maintain and more likely to get broken if someone
forgets to update it.
What do you think?
--
David Rowley http://www.2ndQuadrant.com/
PostgreSQL Development, 24x7 Support, Training & Services
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