Re: Performance difference in accessing differrent columns in aPostgres Table

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От Pavel Stehule
Тема Re: Performance difference in accessing differrent columns in aPostgres Table
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Msg-id CAFj8pRBjFfZqF7CuC6PSpqG4u6OD66Kb65UG4je_pJS7TZPTyA@mail.gmail.com
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Ответ на Re: Performance difference in accessing differrent columns in aPostgres Table  (Jeff Janes <jeff.janes@gmail.com>)
Ответы Re: Performance difference in accessing differrent columns in aPostgres Table  (Jeff Janes <jeff.janes@gmail.com>)
Re: Performance difference in accessing differrent columns in aPostgres Table  (Andres Freund <andres@anarazel.de>)
Список pgsql-performance


2018-07-30 13:19 GMT+02:00 Jeff Janes <jeff.janes@gmail.com>:
On Mon, Jul 30, 2018 at 12:11 AM, Pavel Stehule <pavel.stehule@gmail.com> wrote:
2018-07-30 1:00 GMT+02:00 Tom Lane <tgl@sss.pgh.pa.us>:
David Rowley <david.rowley@2ndquadrant.com> writes:
> On 29 July 2018 at 17:38, Dinesh Kumar <dns98944@gmail.com> wrote:
>> I found performance variance between accessing int1 and int200 column which
>> is quite large.

> Have a look at slot_deform_tuple and heap_deform_tuple. You'll see
> that tuples are deformed starting at the first attribute. If you ask
> for attribute 200 then it must deform 1-199 first.

Note that that can be optimized away in some cases, though evidently
not the one the OP is testing.  From memory, you need a tuple that
contains no nulls, and all the columns to the left of the target
column have to be fixed-width datatypes.  Otherwise, the offset to
the target column is uncertain, and we have to search for it.

JIT decrease a overhead of this.

The bottleneck here is such a simple construct, I don't see how JIT could improve it by much.

And indeed, in my hands JIT makes it almost 3 times worse.

Run against ab87b8fedce3fa77ca0d6, I get 12669.619 ms for the 2nd JIT execution and 4594.994 ms for the JIT=off.


Regards

Pavel

 
Cheers,

Jeff

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