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Revise GEQO planner to make use of some heuristic knowledge about SQL, namely

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that it's good to join where there are join clauses rather than where there
are not.  Also enable it to generate bushy plans at need, so that it doesn't
fail in the presence of multiple IN clauses containing sub-joins.  These
changes appear to improve the behavior enough that we can substantially reduce
the default pool size and generations count, thereby decreasing the runtime,
and yet get as good or better plans as we were getting in 7.4.  Consequently,
adjust the default GEQO parameters.  I also modified the way geqo_effort is
used so that it affects both population size and number of generations;
it's now useful as a single control to adjust the GEQO runtime-vs-plan-quality
tradeoff.  Bump geqo_threshold to 12, since even with these changes GEQO
seems to be slower than the regular planner at 11 relations.
This commit is contained in:
Tom Lane
2004-01-23 23:54:21 +00:00
parent 81c554bbe8
commit 3969f2924b
9 changed files with 332 additions and 174 deletions
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32
doc/src/sgml/runtime.sgml
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@ -1,5 +1,5 @@
<!--
$PostgreSQL: pgsql/doc/src/sgml/runtime.sgml,v 1.231 2004/01/21 23:33:34 tgl Exp $
$PostgreSQL: pgsql/doc/src/sgml/runtime.sgml,v 1.232 2004/01/23 23:54:20 tgl Exp $
-->
<Chapter Id="runtime">
@ -1396,7 +1396,7 @@ SET ENABLE_SEQSCAN TO OFF;
Use genetic query optimization to plan queries with at least
this many <literal>FROM</> items involved. (Note that an outer
<literal>JOIN</> construct counts as only one <literal>FROM</>
item.) The default is 11. For simpler queries it is usually best
item.) The default is 12. For simpler queries it is usually best
to use the deterministic, exhaustive planner, but for queries with
many tables the deterministic planner takes too long.
</para>
@ -1404,25 +1404,33 @@ SET ENABLE_SEQSCAN TO OFF;
</varlistentry>
<varlistentry>
<term><varname>geqo_effort</varname> (<type>integer</type>)</term>
<term><varname>geqo_pool_size</varname> (<type>integer</type>)</term>
<term><varname>geqo_generations</varname> (<type>integer</type>)</term>
<term><varname>geqo_effort</varname> (<type>integer</type>)</term>
<term><varname>geqo_selection_bias</varname> (<type>floating point</type>)</term>
<listitem>
<para>
Various tuning parameters for the genetic query optimization
algorithm. The pool size is the number of individuals in one
population. Valid values are between 128 and 1024. If it is set
to 0 (the default) a pool size of 2^(QS+1), where QS is the
number of <literal>FROM</> items in the query, is used.
algorithm. The recommended one to modify is
<varname>geqo_effort</varname>, which can range from 1 to 10 with
a default of 5. Larger values increase the time spent in planning
but make it more likely that a good plan will be found.
<varname>geqo_effort</varname> doesn't actually do anything directly,
it is just used to compute the default values for the other
parameters. If you prefer, you can set the other parameters by hand
instead.
The pool size is the number of individuals in the genetic population.
It must be at least two, and useful values are typically 100 to 1000.
If it is set to zero (the default setting) then a suitable default
is chosen based on <varname>geqo_effort</varname> and the number of
tables in the query.
Generations specifies the number of iterations of the algorithm.
The value must be a positive integer. If 0 is specified then
<literal>Effort * Log2(PoolSize)</literal> is used.
It must be at least one, and useful values are in the same range
as the pool size.
If it is set to zero (the default setting) then a suitable default
is chosen based on the pool size.
The run time of the algorithm is roughly proportional to the sum of
pool size and generations.
<varname>geqo_effort</varname> is only used in computing the default
generations setting, as just described. The default value is 40,
and the allowed range 1 to 100.
The selection bias is the selective pressure within the
population. Values can be from 1.50 to 2.00; the latter is the
default.