--- Simon Riggs <simon@2ndquadrant.com> skrev:
>
> The distribution of rows with those values also makes a difference to
> the results. ANALYZE assumes that all values are randomly distributed
> within the table, so if the values are clumped together for whatever
> reason the ndistinct calc is less likely to take that into account.
This is an important factor.
As a summary, one table is defined like this:
Table "public.step_result_subset"
Column | Type | Modifiers
-------------+---------+-----------
id | integer | not null
uut_result | integer |
step_parent | integer |
Indexes:
"step_result_subset_pkey" PRIMARY KEY, btree (id)
"step_result_subset_parent_key" btree (step_parent)
"step_result_uut_result_idx" btree (uut_result)
The values in step_result_subset.uut_result is clumped together (between 10 and 1000 of same
value, and also increasing through the table).
The rows where step_result_subset.step_parent is 0 (a special case) is distributed within the
table.
Even when i set statistics on test_result_subset.uut_result to 1000 7.4.14 picks a better plan
than 8.2.0 for some returned datasets. The best results for both 7.4.14 and 8.2.0 is if i remove
the index step_result_subset_parent_key.
I will have to check if other queries which uses step_result_subset.step_parent will be "broken"
by removing the index but i think it should be ok.
I have gotten some ideas from this thread , read some more documentation, read the archives, and
tested other queries and will try to speed up some more advance queries.
Thanks everyone.
best regards
Rolf Østvik
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