Yes, the rowcount estimates are real, however, it has been a long
time since the last VACUUM FULL (there is never a good time).
I have clustered the tables, reindexed, analyzed, vacuumed and the
plan now looks like this:
no_people=# explain SELECT r.id AS r_id, r.firstname || ' ' ||
r.lastname AS r_name, ad.id AS ad_id, ad.type AS ad_type, ad.address
AS ad_address, ad.postalcode AS ad_postalcode, ad.postalsite AS
ad_postalsite, ad.priority AS ad_priority, ad.position[0] AS ad_lat,
ad.position[1] AS ad_lon, ad.uncertainty AS ad_uncertainty, ad.extra
AS ad_extra, ad.deleted AS ad_deleted, co.id AS co_id, co.type AS
co_type, co.value AS co_value, co.description AS co_description,
co.priority AS co_priority, co.visible AS co_visible, co.searchable
AS co_searchable, co.deleted AS co_deleted FROM people r LEFT OUTER
JOIN addresses ad ON(r.id = ad.record) LEFT OUTER JOIN contacts co ON
(r.id = co.record) WHERE NOT r.deleted AND r.original IS NULL ORDER
BY r.id;
QUERY PLAN
---------------------------------------------------------------------
---
--------------------------------------------------
Sort (cost=182866.49..182943.12 rows=30655 width=587)
Sort Key: r.id
-> Nested Loop Left Join (cost=0.00..170552.10 rows=30655
width=587)
-> Nested Loop Left Join (cost=0.00..75054.96 rows=26325
width=160)
-> Index Scan using people_deleted_original_is_null
on people r (cost=0.00..1045.47 rows=23861 width=27)
Filter: ((NOT deleted) AND (original IS NULL))
-> Index Scan using addresses_record_idx on
addresses ad (cost=0.00..3.05 rows=4 width=137)
Index Cond: ("outer".id = ad.record)
-> Index Scan using contacts_record_idx on contacts co
(cost=0.00..3.32 rows=24 width=431)
Index Cond: ("outer".id = co.record)
(10 rows)
Looks faster, but still very slow. I added limit 1000 and it has been
running for about 25 minutes now with no output. top shows:
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
29994 postgres 18 0 95768 78m 68m R 17.0 7.7 0:53.27
postmaster
which is unusual, I usually get 99.9 %cpu for just about any query,
which leads me to believe this is disk related.
postgresql.conf:
shared_buffers = 8192
work_mem = 8192
maintenance_work_mem = 524288
Hardware 2x2.8GHz cpu
1GB ram
Could this be an issue related to lack of VACUUM FULL? The tables get
a lot of updates.
Thank you very much so far!
On Jan 11, 2006, at 4:45 PM, Tom Lane wrote:
Bendik Rognlien Johansen <bendik.johansen@xxxxxxxxx> writes:
Has anyone got any tips for speeding up this query? It currently
takes hours to start.
Are the rowcount estimates close to reality? The plan doesn't look
unreasonable to me if they are. It might help to increase work_mem
to ensure that the hash tables don't spill to disk.
Indexes:
"people_original_is_null" btree (original) WHERE original IS
NULL
This index seems poorly designed: the actual index entries are dead
weight since all of them are necessarily NULL. You might as well
make
the index carry something that you frequently test in conjunction
with
"original IS NULL". For instance, if this particular query is a
common
case, you could replace this index with
CREATE INDEX people_deleted_original_is_null ON people(deleted)
WHERE original IS NULL;
This index is still perfectly usable for queries that only say
"original
IS NULL", but it can also filter out rows with the wrong value of
deleted. Now, if there are hardly any rows with deleted = true,
maybe
this won't help much for your problem. But in any case you ought to
consider whether you can make the index entries do something useful.
regards, tom lane
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