Re: [PERFORM] Hash join on int takes 8..114 seconds
Tomas, Let's suppose you set a reasonable value (say 8096) instead of 2GB. That gives about 160MB. Anyway this depends - if you have a lot of slow queries caused by on-disk sorts / hash tables, use a higher value. Otherwise leave it as it is. Probably product orders table is frequently joined which product table. currently there was work_memory = 512 in conf file. I changed it to work_memory = 8096 If it is all cached in memory, you may want to ensure that your shared_buffers is a reasonalbe size so that there is less shuffling of data from the kernel to postgres and back. Generally, shared_buffers works best between 5% and 25% of system memory. currently shared_buffers = 15000 That's 120MB, i.e. about 6% of the memory. Might be a little bit higher, but seems reasonable. I changed it to 2 Given the fact that the performance issues are caused by bloated tables and / or slow I/O subsystem, moving to a similar system won't help I guess. I have ran VACUUM FULL ANALYZE VERBOSE and set MAX_FSM_PAGES = 15 So there is no any bloat except pg_shdepend indexes which should not affect to query speed. Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Given the fact that the performance issues are caused by bloated tables and / or slow I/O subsystem, moving to a similar system won't help I guess. I have ran VACUUM FULL ANALYZE VERBOSE and set MAX_FSM_PAGES = 15 So there is no any bloat except pg_shdepend indexes which should not affect to query speed. OK, what was the number of unused pointer items in the VACUUM output? The query performance is still the same as when the tables were bloated? What are the outputs of iostat/vmstat/dstat/top when running the query? regards Tomas -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Tomas,
OK, what was the number of unused pointer items in the VACUUM output?
I posted it in this thread:
VACUUM FULL ANALYZE VERBOSE;
...
INFO: free space map contains 14353 pages in 314 relations
DETAIL: A total of 2 page slots are in use (including overhead).
89664 page slots are required to track all free space.
Current limits are: 2 page slots, 1000 relations, using 182 KB.
NOTICE: number of page slots needed (89664) exceeds max_fsm_pages (2)
HINT: Consider increasing the configuration parameter max_fsm_pages to a
value over 89664.
Query returned successfully with no result in 10513335 ms.
The query performance is still the same as when the tables were bloated?
Seems to be the same.
However I improved yesterday after previous message other queries not to
scan whole
product orders (rid) table.
Now there is only few disk activity after 5-300 seconds which seems not to
affect to those query results. So issue in this thread has been gone away.
Now this query runs using constant time 8 seconds:
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode = 'X05' AND dok.kuupaev='2008-09-01'
Aggregate (cost=182210.77..182210.78 rows=1 width=0) (actual
time=8031.600..8031.604 rows=1 loops=1)
- Nested Loop (cost=74226.74..182149.27 rows=24598 width=0) (actual
time=2602.474..7948.121 rows=21711 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01 rows=1
width=24) (actual time=0.077..0.089 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=74226.74..181897.28 rows=24598 width=24)
(actual time=2602.378..7785.315 rows=21711 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4084.54..101951.60
rows=270725 width=28) (actual time=1129.925..4686.601 rows=278417 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4084.54 rows=270725 width=0) (actual time=1123.202..1123.202
rows=278426 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=69419.29..69419.29 rows=112766 width=4)
(actual time=1251.496..1251.496 rows=111088 loops=1)
- Bitmap Heap Scan on dok (cost=1492.68..69419.29
rows=112766 width=4) (actual time=70.837..776.249 rows=111088 loops=1)
Recheck Cond: (kuupaev = '2008-09-01'::date)
- Bitmap Index Scan on dok_kuupaev_idx
(cost=0.00..1492.68 rows=112766 width=0) (actual time=64.177..64.177
rows=111343 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
Total runtime: 8031.905 ms
Interestingly using like is 80 times faster:
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode like 'X05' AND dok.kuupaev='2008-09-01'
Aggregate (cost=88178.69..88178.70 rows=1 width=0) (actual
time=115.335..115.339 rows=1 loops=1)
- Hash Join (cost=71136.22..88117.36 rows=24532 width=0) (actual
time=115.322..115.322 rows=0 loops=1)
Hash Cond: (outer.toode = inner.toode)
- Hash Join (cost=70163.36..86253.20 rows=24598 width=24)
(actual time=0.046..0.046 rows=0 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=21.16..6307.52 rows=270725
width=28) (actual time=0.037..0.037 rows=0 loops=1)
Filter: (toode ~~ 'X05'::text)
- Bitmap Index Scan on rid_toode_pattern_idx
(cost=0.00..21.16 rows=1760 width=0) (actual time=0.028..0.028 rows=0
loops=1)
Index Cond: (toode ~=~ 'X05'::bpchar)
- Hash (cost=69419.29..69419.29 rows=112766 width=4)
(never executed)
- Bitmap Heap Scan on dok (cost=1492.68..69419.29
rows=112766 width=4) (never executed)
Recheck Cond: (kuupaev = '2008-09-01'::date)
- Bitmap Index Scan on dok_kuupaev_idx
(cost=0.00..1492.68 rows=112766 width=0) (never executed)
Index Cond: (kuupaev =
'2008-09-01'::date)
- Hash (cost=853.29..853.29 rows=13429 width=24) (actual
time=114.757..114.757 rows=13412 loops=1)
- Seq Scan on toode (cost=0.00..853.29 rows=13429
width=24) (actual time=0.014..58.319 rows=13412 loops=1)
Total runtime: 115.505 ms
I posted also a test script in other thread which shows also that like is
magitude faster than equality check.
rid.toode = 'X05'
and
rid.toode like 'X05'
are exactly the same conditions, there are indexes for both conditions.
So I do'nt understand why results are so different.
In other sample which I posted in thread Increasing pattern index query
speed like is 4 times slower:
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode = '9910' AND
Re: [PERFORM] Hash join on int takes 8..114 seconds
You could try writing a plpgsql function which would generate the data
set.
Or you could use your existing data set.
Creating 3.5 mln rows using stored proc is probably slow.
Probably it would be better and faster to use some random() and
generate_series() trick.
In this case others can try it and dataset generation is faster.
By the way, a simple way to de-bloat your big table without blocking
would be this :
- stop all inserts and updates
- begin
- create table new like old table
- insert into new select * from old (order by perhaps)
- create indexes
- rename new into old
- commit
If this is just a reporting database where you insert a batch of new data
every day, for instance, that's very easy to do. If it's OLTP, then, no.
Those are orders and order_products tables.
I ran vacuum full analyze verbose last night.
Now database has 4832 MB size, including 1 GB
pg_shdepend bloated indexes.
I added max_fsm_pages=15 and re-booted.
Query below and other queries are still too slow
set search_path to firma2,public;
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
Aggregate (cost=181795.13..181795.14 rows=1 width=0) (actual
time=23678.265..23678.268 rows=1 loops=1)
- Nested Loop (cost=73999.44..181733.74 rows=24555 width=0) (actual
time=18459.230..23598.956 rows=21476 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01 rows=1
width=24) (actual time=0.134..0.145 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=73999.44..181482.18 rows=24555 width=24)
(actual time=18459.076..23441.098 rows=21476 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4082.88..101779.03
rows=270252 width=28) (actual time=9337.782..12720.365 rows=278182 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4082.88 rows=270252 width=0) (actual time=9330.634..9330.634
rows=278183 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=69195.13..69195.13 rows=112573 width=4)
(actual time=8894.465..8894.465 rows=109890 loops=1)
- Bitmap Heap Scan on dok (cost=1492.00..69195.13
rows=112573 width=4) (actual time=1618.763..8404.847 rows=109890 loops=1)
Recheck Cond: (kuupaev = '2008-09-01'::date)
- Bitmap Index Scan on dok_kuupaev_idx
(cost=0.00..1492.00 rows=112573 width=0) (actual time=1612.177..1612.177
rows=110484 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
Total runtime: 23678.790 ms
Here is a list of untried recommendations from this thread:
1. CLUSTER rid ON rid_toode_pkey ; CLUSTER dok ON dok_kuupaev_idx
- In 8.1.4 provided form of CLUSTER causes syntax error, no idea what
syntax to use.
Risky to try in prod server. Requires creating randomly distributed
product_id testcase to measure
difference.
2. Change CHAR(20) product index to int index by adding update trigger.
Risky to try in prod server. Requires creating randomly distributed
product_id testcase to measure
difference.
3. Denormalization of sale date to order_producs table by adding update
trigger.
Risky to try in prod server. Requires creating randomly distributed
product_id testcase to measure
difference.
4. Check on the performance of the RAID: Does it leverage NCQ appropriately
when running queries in parallel ?
No idea how.
5. Materialized views. I need date granularity so it is possible to sum only
one days sales.
http://www.pgcon.org/2008/schedule/events/69.en.html
Seems to be major appl re-write, no idea how.
Appoaches which probably does not change perfomance:
6. Upgrade to 8.4 or to 8.3.5
7. run server on standalone mode and recover 1 GB pg_shdepend bloated index.
8. tune some conf file parameters:
work_mem = 512
I'd consider increasing this value a little - 0.5 MB seems too low to me
(but not necessarily).
effective_cache_size= 7
Well, your server has 2GB of RAM and usually it's recommended to set
this value to about 60-70% of your RAM, so using 540MB (25%) seems quite
low.
Data size is nearly the same as RAM size. It is unpleasant surprise that
queries take so long time.
What should I do next?
Andrus.
140926 firma2.rid1737 MB
240595 firma2.dok1632 MB
3 1214 pg_catalog.pg_shdepend1235 MB
4 1232 pg_catalog.pg_shdepend_depender_index 795 MB
7 1233 pg_catalog.pg_shdepend_reference_index439 MB
844299 firma2.rid_toode_idx 298 MB
944286 firma2.dok_tasudok_idx245 MB
10 19103791 firma2.rid_toode_pattern_idx
Re: [PERFORM] Hash join on int takes 8..114 seconds
Risky to try in prod server. Requires creating randomly distributed product_id testcase to measure difference. What should I do next? I guess you have backups - take them, restore the database on a different machine (preferably with the same / similar hw config) and tune the queries on it. After restoring all the tables / indexes will be 'clean' (not bloated), so you'll see if performing VACUUM FULL / CLUSTER is the right solution or if you have to change the application internals. Sure, the times will be slightly different but the performance problems should remain the same. regards Tomas -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Appoaches which probably does not change perfomance: 6. Upgrade to 8.4 or to 8.3.5 Both of these will improve performance a little, even with the same query plan and same data. I would expect about a 10% improvement for 8.3.x on most memory bound select queries. 8.4 won't be out for a few months. 7. run server on standalone mode and recover 1 GB pg_shdepend bloated index. 8. tune some conf file parameters: work_mem = 512 I'd consider increasing this value a little - 0.5 MB seems too low to me (but not necessarily). This is very easy to try. You can change work_mem for just a single session, and this can in some cases help performance quite a bit, and in others not at all. I would not recommend having it lower than at least 4MB on a server like that unless you have a lot of concurrently active queries / connections. To try it, simply use the SET command. To try out 32MB, just do: SET work_mem = '32MB'; and the value will be changed locally for that session only. See if it affects your test query or not. http://www.postgresql.org/docs/8.3/interactive/sql-set.html effective_cache_size= 7 Well, your server has 2GB of RAM and usually it's recommended to set this value to about 60-70% of your RAM, so using 540MB (25%) seems quite low. Data size is nearly the same as RAM size. It is unpleasant surprise that queries take so long time. What should I do next? First, demonstrate that it is all or mostly in memory -- use iostat or other tools to ensure that there is not much disk activity during the query. If your system doesn't have iostat installed, it should be installed. It is a very useful tool. If it is all cached in memory, you may want to ensure that your shared_buffers is a reasonalbe size so that there is less shuffling of data from the kernel to postgres and back. Generally, shared_buffers works best between 5% and 25% of system memory. If it is completely CPU bound then the work done for the query has to be reduced by altering the plan to a more optimal one or making the work it has to do at each step easier. Most of the ideas in this thread revolve around those things. Based on the time it took to do the vacuum, I suspect your disk subsystem is a bit slow. If it can be determined that there is much disk I/O in your use cases, there are generally several things that can be done to tune Linux I/O. The main ones in my experience are the 'readahead' value for each disk which helps sequential reads significantly, and trying out the linux 'deadline' scheduler and comparing it to the more commonly used 'cfq' scheduler. If the system is configured with the anticipatory scheduler, absolutely switch to cfq or deadline as the anticipatory scheduler will perform horribly poorly for a database. Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
I guess you have backups - take them, restore the database on a different machine (preferably with the same / similar hw config) and tune the queries on it. After restoring all the tables / indexes will be 'clean' (not bloated), so you'll see if performing VACUUM FULL / CLUSTER is the right solution or if you have to change the application internals. Sure, the times will be slightly different but the performance problems should remain the same. VACUUM FULL has My test computer has PostgreSql 8.3, 4 GB RAM, SSD disks, Intel X2Extreme CPU So it is much faster than this prod server. No idea how to emulate this environment. I can create new db in prod server as old copy but this can be used in late night only. Where to find script which clones some database in server? Something like CREATE DATABASE newdb AS SELECT * FROM olddb; It would be more convenient to run db cloning script from pgadmin command window. Only way I found is to use SSH with pg_dup/pg_restore. This requires SSH access to server and SSH port opening to public internet. Or probably try to run CLUSTER command in prod server. Hopefully clustering by product id cannot make things slow too much. Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Scott,
thank you.
work_mem = 512
This is very easy to try. You can change work_mem for just a single
session, and this can in some cases help performance quite a bit, and in
others not at all.
I would not recommend having it lower than at least 4MB on a server like
that unless you have a lot of concurrently active queries / connections.
To try it, simply use the SET command. To try out 32MB, just do:
SET work_mem = '32MB';
8.1.4 requires int value.
SET work_mem = 33554432;
causes:
ERROR: 33554432 is outside the valid range for parameter work_mem (64 ..
2097151)
So max allowed value seems to be 2 MB
I tested it when this server was idle by running both queries several times
after VACUUM FULL was running
SET work_mem = 2097151;
set search_path to firma2,public;
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
Aggregate (cost=177291.36..177291.37 rows=1 width=0) (actual
time=5153.856..5153.859 rows=1 loops=1)
- Nested Loop (cost=73607.45..177229.96 rows=24561 width=0) (actual
time=1395.935..5071.247 rows=21541 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01 rows=1
width=24) (actual time=0.078..0.087 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=73607.45..176978.33 rows=24561 width=24)
(actual time=1395.836..4911.425 rows=21541 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4083.10..101802.05
rows=270316 width=28) (actual time=238.578..2367.189 rows=278247 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4083.10 rows=270316 width=0) (actual time=150.868..150.868
rows=278248 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=69242.72..69242.72 rows=112651 width=4)
(actual time=1146.081..1146.081 rows=110170 loops=1)
- Bitmap Heap Scan on dok (cost=1492.28..69242.72
rows=112651 width=4) (actual time=46.210..696.803 rows=110170 loops=1)
Recheck Cond: (kuupaev = '2008-09-01'::date)
- Bitmap Index Scan on dok_kuupaev_idx
(cost=0.00..1492.28 rows=112651 width=0) (actual time=33.938..33.938
rows=110232 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
Total runtime: 5154.911 ms
SET work_mem to default;
set search_path to firma2,public;
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
Aggregate (cost=181869.36..181869.37 rows=1 width=0) (actual
time=7807.867..7807.871 rows=1 loops=1)
- Nested Loop (cost=74048.45..181807.96 rows=24561 width=0) (actual
time=2607.429..7728.138 rows=21541 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01 rows=1
width=24) (actual time=0.079..0.091 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=74048.45..181556.33 rows=24561 width=24)
(actual time=2607.332..7569.612 rows=21541 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4083.10..101802.05
rows=270316 width=28) (actual time=1147.071..4528.845 rows=278247 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4083.10 rows=270316 width=0) (actual time=1140.337..1140.337
rows=278248 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=69242.72..69242.72 rows=112651 width=4)
(actual time=1240.988..1240.988 rows=110170 loops=1)
- Bitmap Heap Scan on dok (cost=1492.28..69242.72
rows=112651 width=4) (actual time=68.053..769.448 rows=110170 loops=1)
Recheck Cond: (kuupaev = '2008-09-01'::date)
- Bitmap Index Scan on dok_kuupaev_idx
(cost=0.00..1492.28 rows=112651 width=0) (actual time=61.358..61.358
rows=110232 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
Total runtime: 7808.174 ms
In both cases vmstat 2 shows only cpu activity when queries are running:
procs ---memory-- ---swap-- -io --system-- cpu
r b swpd free buff cache si sobibo incs us sy id
wa
...
0 0232 123692 0 189104400 0 0 25217 0 0
100 0
0 0232 123692 0 189104400 0 0 25217 0 0
100 0
0 0232 123684 0 189104400 0 162 25422 0 0
100 0
0 0232 123684 0 189104400 0 0 25218 0 0
100 0
1 0232 123056 0 189144400 013 25421 62 5 34
0 start of slower query
1 0232 102968 0 191106000
Re: [PERFORM] Hash join on int takes 8..114 seconds
My test computer has PostgreSql 8.3, 4 GB RAM, SSD disks, Intel X2Extreme CPU So it is much faster than this prod server. No idea how to emulate this environment. I can create new db in prod server as old copy but this can be used in late night only. Well, a faster but comparable system may not be a problem - the query might run 10 times faster, but it still will be slow (say 40 seconds instead of 8 minutes). What is a problem is a different I/O system - SSD instead of traditional drives in this case. I have no direct experience with with SSD yet, but AFAIK the seek time is much better compared to regular drives (say 0.1ms instead of 10ms, that is 100-times faster). So you can't just put on old SATA drive into the test machine? Where to find script which clones some database in server? Something like CREATE DATABASE newdb AS SELECT * FROM olddb; It would be more convenient to run db cloning script from pgadmin command window. Only way I found is to use SSH with pg_dup/pg_restore. This requires SSH access to server and SSH port opening to public internet. Yes, using pg_dump | pg_restore is probably the way to clone database. But it will slow down the system, as it has to do a lot of I/O (and as it seems to be a bottleneck already, I don't think this is a good idea). Or probably try to run CLUSTER command in prod server. Hopefully clustering by product id cannot make things slow too much. As already noted, CLUSTER command causes exclusive lock on the database. So this is an operation you'd like to do on production server ... Tomas -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Scott,
thank you.
work_mem = 512
This is very easy to try. You can change work_mem for just a single
session, and this can in some cases help performance quite a bit, and in
others not at all.
I would not recommend having it lower than at least 4MB on a server like
that unless you have a lot of concurrently active queries / connections.
To try it, simply use the SET command. To try out 32MB, just do:
SET work_mem = '32MB';
8.1.4 requires int value.
SET work_mem = 33554432;
causes:
ERROR: 33554432 is outside the valid range for parameter work_mem (64 ..
2097151)
So max allowed value seems to be 2 MB
I tested it when this server was idle by running both queries several times
after VACUUM FULL was running
SET work_mem = 2097151;
No, not really. The work_mem value is specified in kilobytes, so you've
set it to 2GB :-)
set search_path to firma2,public;
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
Aggregate (cost=177291.36..177291.37 rows=1 width=0) (actual
time=5153.856..5153.859 rows=1 loops=1)
- Nested Loop (cost=73607.45..177229.96 rows=24561 width=0) (actual
time=1395.935..5071.247 rows=21541 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01 rows=1
width=24) (actual time=0.078..0.087 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=73607.45..176978.33 rows=24561 width=24)
(actual time=1395.836..4911.425 rows=21541 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4083.10..101802.05
rows=270316 width=28) (actual time=238.578..2367.189 rows=278247 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4083.10 rows=270316 width=0) (actual time=150.868..150.868
rows=278248 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=69242.72..69242.72 rows=112651 width=4)
(actual time=1146.081..1146.081 rows=110170 loops=1)
- Bitmap Heap Scan on dok (cost=1492.28..69242.72
rows=112651 width=4) (actual time=46.210..696.803 rows=110170 loops=1)
Recheck Cond: (kuupaev = '2008-09-01'::date)
- Bitmap Index Scan on dok_kuupaev_idx
(cost=0.00..1492.28 rows=112651 width=0) (actual time=33.938..33.938
rows=110232 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
Total runtime: 5154.911 ms
SET work_mem to default;
set search_path to firma2,public;
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
Aggregate (cost=181869.36..181869.37 rows=1 width=0) (actual
time=7807.867..7807.871 rows=1 loops=1)
- Nested Loop (cost=74048.45..181807.96 rows=24561 width=0) (actual
time=2607.429..7728.138 rows=21541 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01 rows=1
width=24) (actual time=0.079..0.091 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=74048.45..181556.33 rows=24561 width=24)
(actual time=2607.332..7569.612 rows=21541 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4083.10..101802.05
rows=270316 width=28) (actual time=1147.071..4528.845 rows=278247 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4083.10 rows=270316 width=0) (actual time=1140.337..1140.337
rows=278248 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=69242.72..69242.72 rows=112651 width=4)
(actual time=1240.988..1240.988 rows=110170 loops=1)
- Bitmap Heap Scan on dok (cost=1492.28..69242.72
rows=112651 width=4) (actual time=68.053..769.448 rows=110170 loops=1)
Recheck Cond: (kuupaev = '2008-09-01'::date)
- Bitmap Index Scan on dok_kuupaev_idx
(cost=0.00..1492.28 rows=112651 width=0) (actual time=61.358..61.358
rows=110232 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
Total runtime: 7808.174 ms
In both cases vmstat 2 shows only cpu activity when queries are running:
procs ---memory-- ---swap-- -io --system--
cpu
r b swpd free buff cache si sobibo incs us sy id
wa
...
0 0232 123692 0 189104400 0 0 25217 0 0
100 0
0 0232 123692 0 189104400 0 0 25217 0 0
100 0
0 0232 123684 0 189104400 0 162 25422 0 0
100 0
0 0232 123684 0 189104400 0 0 25218 0 0
100 0
1 0232 123056 0 189144400 0
Re: [PERFORM] Hash join on int takes 8..114 seconds
On Fri, 21 Nov 2008 21:07:02 +0100, Tom Lane [EMAIL PROTECTED] wrote: PFC [EMAIL PROTECTED] writes: Index on orders_products( product_id ) and orders_products( order_id ): = Same plan Note that in this case, a smarter planner would use the new index to perform a BitmapAnd before hitting the heap to get the rows. Considering that the query has no constraint on orders_products.order_id, I'm not sure what you think the extra index is supposed to be used *for*. (Well, we could put orders as the outside of a nestloop and then we'd have such a constraint, but with 3 orders rows to process that plan would lose big.) (And yes, the planner did consider such a plan along the way. See choose_bitmap_and.) regards, tom lane I think I didn't express myself correctly... Here the indexes are small (therefore well cached) but the orders_products table is large (and not cached). To reproduce this, I put this table on a crummy slow external USB drive. Between each of the following queries, pg was stopped, the USB drive unmounted, remounted, and pg restarted, to purge orders_products table out of all caches. I also modified the statistical distribution (see init script at bottom of message). EXPLAIN ANALYZE SELECT count(*) FROM orders JOIN orders_products USING (order_id) WHERE orders.order_date BETWEEN '2000-01-01' AND '2000-02-01' AND orders_products.product_id = 2345; QUERY PLAN - Aggregate (cost=5431.93..5431.94 rows=1 width=0) (actual time=5176.382..5176.382 rows=1 loops=1) - Hash Join (cost=1575.13..5431.84 rows=35 width=0) (actual time=62.634..5176.332 rows=36 loops=1) Hash Cond: (orders_products.order_id = orders.order_id) - Bitmap Heap Scan on orders_products (cost=21.27..3864.85 rows=1023 width=4) (actual time=7.041..5118.512 rows=1004 loops=1) Recheck Cond: (product_id = 2345) - Bitmap Index Scan on orders_products_product_order (cost=0.00..21.02 rows=1023 width=0) (actual time=0.531..0.531 rows=1004 loops=1) Index Cond: (product_id = 2345) - Hash (cost=1130.58..1130.58 rows=33862 width=4) (actual time=55.526..55.526 rows=31999 loops=1) - Index Scan using orders_date on orders (cost=0.00..1130.58 rows=33862 width=4) (actual time=0.139..33.466 rows=31999 loops=1) Index Cond: ((order_date = '2000-01-01'::date) AND (order_date = '2000-02-01'::date)) Total runtime: 5176.659 ms This is the original query ; what I don't like about it is that it bitmapscans orders_products way too much, because it reads all orders for the specified product, not just orders in the date period we want. However, since Postgres scanned all order_id's corresponding to the date range already, to build the hash, the list of order_ids of interest is known at no extra cost. In this case, additionnally, correlation is 100% between order_id and date, so I can do : test= SELECT max(order_id), min(order_id) FROM orders WHERE order_date BETWEEN '2000-01-01' AND '2000-02-01'; max | min ---+- 31999 | 1 And I can add an extra condition to the query, like this : EXPLAIN ANALYZE SELECT count(*) FROM orders JOIN orders_products USING (order_id) WHERE orders.order_date BETWEEN '2000-01-01' AND '2000-02-01' AND orders_products.order_id BETWEEN 1 AND 31999 AND orders_products.product_id = 2345; QUERY PLAN - Aggregate (cost=426.80..426.81 rows=1 width=0) (actual time=179.233..179.233 rows=1 loops=1) - Nested Loop (cost=0.00..426.79 rows=1 width=0) (actual time=6.667..179.190 rows=36 loops=1) - Index Scan using orders_products_product_order on orders_products (cost=0.00..142.11 rows=34 width=4) (actual time=6.559..177.597 rows=36 loops=1) Index Cond: ((product_id = 2345) AND (order_id = 1) AND (order_id = 31999)) - Index Scan using orders_pkey on orders (cost=0.00..8.36 rows=1 width=4) (actual time=0.039..0.041 rows=1 loops=36) Index Cond: (orders.order_id = orders_products.order_id) Filter: ((orders.order_date = '2000-01-01'::date) AND (orders.order_date = '2000-02-01'::date)) Total runtime: 179.392 ms This is with no cache on orders_products table. About 30X faster. Interestingly, when everything is cached, it's even faster (about 100X)... The plan I was thinking about was not a nested loop with 30K loops...
Re: [PERFORM] Hash join on int takes 8..114 seconds
You could perhaps run a little check on the performance of the RAID, is it better than linux software RAID ? Does it leverage NCQ appropriately when running queries in parallel ? I was told that this RAID is software RAID. I have no experience what to check. This HP server was installed 3 years ago and in this time it was not high perfomance server. explain analyze SELECT sum(1) FROM dok JOIN rid USING (dokumnr) JOIN toode USING (toode) LEFT JOIN artliik using(grupp,liik) WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01' By the way, note that the presence of the toode table in the query above is not required at all, unless you use columns of toode in your aggregates. In real query, SELECT column list contains data form sales table dok (sale date and time) and sales detail table rid (quantity, price) WHERE clause may contain additional filters from product table (product category, supplier). Let's play with that, after all, it's friday night. Thank you very much for great sample. I tried to create testcase from this to match production db: 1.2 million orders 3.5 million order details 13400 products with char(20) as primary keys containing ean-13 codes mostly 3 last year data every order has usually 1..3 detail lines same product can appear multiple times in order products are queried by start of code This sample does not distribute products randomly between orders. How to change this so that every order contains 3 (or 1..6 ) random products? I tried to use random row sample from http://www.pgsql.cz/index.php/PostgreSQL_SQL_Tricks-i but in this case constant product is returned always. It seems than query containing randon() is executed only once. Andrus. begin; CREATE TEMP TABLE orders (order_id INTEGER NOT NULL, order_date DATE NOT NULL); CREATE TEMP TABLE products (product_id CHAR(20) NOT NULL, product_name char(70) NOT NULL, quantity numeric(12,2) default 1); CREATE TEMP TABLE orders_products (order_id INTEGER NOT NULL, product_id CHAR(20),padding1 char(70), id serial, price numeric(12,2) default 1 ); INSERT INTO products SELECT (n*power( 10,13))::INT8::CHAR(20), 'product number ' || n::TEXT FROM generate_series(0,13410) AS n; INSERT INTO orders SELECT n,'2005-01-01'::date + (4000.0 * n/350.0 * '1 DAY'::interval) FROM generate_series(0,350/3) AS n; SET work_mem TO 2097151; -- 1048576; INSERT INTO orders_products SELECT generate_series/3 as order_id, ( ((generate_series/350.0)*13410.0)::int*power( 10,13))::INT8::CHAR(20) FROM generate_series(1,350) where generate_series/30; ALTER TABLE orders ADD PRIMARY KEY (order_id); ALTER TABLE products ADD PRIMARY KEY (product_id); ALTER TABLE orders_products ADD PRIMARY KEY (id); ALTER TABLE orders_products ADD FOREIGN KEY (product_id) REFERENCES products(product_id); ALTER TABLE orders_products ADD FOREIGN KEY (order_id) REFERENCES orders(order_id) ON DELETE CASCADE; CREATE INDEX orders_date ON orders( order_date ); CREATE INDEX order_product_pattern_idx ON orders_products( product_id bpchar_pattern_ops ); COMMIT; SET work_mem TO DEFAULT; ANALYZE; SELECT sum(quantity*price) FROM orders JOIN orders_products USING (order_id) JOIN products USING (product_id) WHERE orders.order_date='2008-01-17' and orders_products.product_id like '130%' -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Thank you very much for great sample. I tried to create testcase from this to match production db: 1.2 million orders 3.5 million order details 13400 products with char(20) as primary keys containing ean-13 codes mostly 3 last year data every order has usually 1..3 detail lines same product can appear multiple times in order products are queried by start of code This sample does not distribute products randomly between orders. How to change this so that every order contains 3 (or 1..6 ) random products? I tried to use random row sample from http://www.pgsql.cz/index.php/PostgreSQL_SQL_Tricks-i but in this case constant product is returned always. It seems than query containing randon() is executed only once. You could try writing a plpgsql function which would generate the data set. Or you could use your existing data set. By the way, a simple way to de-bloat your big table without blocking would be this : - stop all inserts and updates - begin - create table new like old table - insert into new select * from old (order by perhaps) - create indexes - rename new into old - commit If this is just a reporting database where you insert a batch of new data every day, for instance, that's very easy to do. If it's OLTP, then, no. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Richard, In addition to top below, you'll probably find vmstat 5 useful. Thank you. During this query run (65 sec), vmstat 5 shows big values in bi,cs and wa columns: procs ---memory-- ---swap-- -io --system-- cpu r b swpd free buff cache si sobibo incs us sy id wa 1 1 88 51444 0 18544040017 6 1513 5 1 83 10 0 1 88 52140 0 185430400 362695 562 784 15 38 0 47 0 1 92 51608 0 185566800 14116 103 1382 2294 4 8 0 88 0 1 92 51620 0 185725601 1525831 1210 1975 4 8 0 88 0 2 92 50448 0 185918800 1311819 1227 1982 3 7 0 90 0 1 92 51272 0 185908800 769153 828 1284 14 4 0 82 0 1 92 52472 0 185879200 10691 9 758 968 3 7 0 89 0 2 92 51240 0 185859600 8204 7407 717 1063 2 5 0 93 0 1 92 51648 0 186038800 20622 121 1118 2229 12 9 0 79 2 1 92 50564 0 186139600 20994 3277 969 1681 15 8 0 76 1 0 92 52180 0 186019200 1854236 802 1276 36 12 0 51 0 0 92 91872 0 182094801 1528547 588 774 9 12 32 47 0 0 92 91904 0 182094800 0 4 25118 0 0 100 0 0 0 92 92044 0 182094800 0 0 25017 0 0 100 0 0 0 92 91668 0 1821156002793 27266 5 0 92 3 0 0 92 91668 0 182115600 064 26038 0 0 100 0 0 0 92 91636 0 182115600 0 226 27771 0 0 100 0 0 0 92 91676 0 182115600 026 25523 0 0 100 0 Here you're stuck waiting for disks (91.0% wa). Check out vmstat and iostat to see what's happening. typing iostat returns bash: iostat: command not found It seems that this is not installed in this gentoo. Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
PFC, thank you. OK so vmstat says you are IO-bound, this seems logical if the same plan has widely varying timings... Let's look at the usual suspects : - how many dead rows in your tables ? are your tables data, or bloat ? (check vacuum verbose, etc) set search_path to firma2,public; vacuum verbose dok; vacuum verbose rid INFO: vacuuming firma2.dok INFO: index dok_pkey now contains 1235086 row versions in 9454 pages DETAIL: 100 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.16s/0.38u sec elapsed 0.77 sec. INFO: index dok_dokumnr_idx now contains 1235086 row versions in 9454 pages DETAIL: 100 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.14s/0.40u sec elapsed 0.78 sec. INFO: index dok_klient_idx now contains 1235086 row versions in 18147 pages DETAIL: 887 index row versions were removed. 3265 index pages have been deleted, 3033 are currently reusable. CPU 0.36s/0.46u sec elapsed 31.87 sec. INFO: index dok_krdokumnr_idx now contains 1235086 row versions in 11387 pages DETAIL: 119436 index row versions were removed. 1716 index pages have been deleted, 1582 are currently reusable. CPU 0.47s/0.55u sec elapsed 63.38 sec. INFO: index dok_kuupaev_idx now contains 1235101 row versions in 10766 pages DETAIL: 119436 index row versions were removed. 659 index pages have been deleted, 625 are currently reusable. CPU 0.62s/0.53u sec elapsed 40.20 sec. INFO: index dok_tasudok_idx now contains 1235104 row versions in 31348 pages DETAIL: 119436 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 1.18s/1.08u sec elapsed 118.97 sec. INFO: index dok_tasudok_unique_idx now contains 99 row versions in 97 pages DETAIL: 98 index row versions were removed. 80 index pages have been deleted, 80 are currently reusable. CPU 0.00s/0.00u sec elapsed 0.48 sec. INFO: index dok_tasumata_idx now contains 1235116 row versions in 11663 pages DETAIL: 119436 index row versions were removed. 5340 index pages have been deleted, 5131 are currently reusable. CPU 0.43s/0.56u sec elapsed 53.96 sec. INFO: index dok_tellimus_idx now contains 1235122 row versions in 11442 pages DETAIL: 119436 index row versions were removed. 1704 index pages have been deleted, 1569 are currently reusable. CPU 0.45s/0.59u sec elapsed 76.91 sec. INFO: index dok_yksus_pattern_idx now contains 1235143 row versions in 5549 pages DETAIL: 119436 index row versions were removed. 529 index pages have been deleted, 129 are currently reusable. CPU 0.19s/0.46u sec elapsed 2.72 sec. INFO: index dok_doktyyp now contains 1235143 row versions in 3899 pages DETAIL: 119436 index row versions were removed. 188 index pages have been deleted, 13 are currently reusable. CPU 0.14s/0.44u sec elapsed 1.40 sec. INFO: index dok_sihtyksus_pattern_idx now contains 1235143 row versions in 5353 pages DETAIL: 119436 index row versions were removed. 286 index pages have been deleted, 5 are currently reusable. CPU 0.13s/0.45u sec elapsed 3.01 sec. INFO: dok: removed 119436 row versions in 13707 pages DETAIL: CPU 0.80s/0.37u sec elapsed 14.15 sec. INFO: dok: found 119436 removable, 1235085 nonremovable row versions in 171641 pages DETAIL: 2 dead row versions cannot be removed yet. There were 1834279 unused item pointers. 0 pages are entirely empty. CPU 6.56s/6.88u sec elapsed 450.54 sec. INFO: vacuuming pg_toast.pg_toast_40595 INFO: index pg_toast_40595_index now contains 0 row versions in 1 pages DETAIL: 0 index pages have been deleted, 0 are currently reusable. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: pg_toast_40595: found 0 removable, 0 nonremovable row versions in 0 pages DETAIL: 0 dead row versions cannot be removed yet. There were 0 unused item pointers. 0 pages are entirely empty. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: vacuuming firma2.rid INFO: index rid_pkey now contains 3275197 row versions in 13959 pages DETAIL: 38331 index row versions were removed. 262 index pages have been deleted, 262 are currently reusable. CPU 0.42s/1.05u sec elapsed 58.56 sec. INFO: index rid_dokumnr_idx now contains 3275200 row versions in 14125 pages DETAIL: 38331 index row versions were removed. 572 index pages have been deleted, 571 are currently reusable. CPU 0.49s/1.14u sec elapsed 71.57 sec. INFO: index rid_inpdokumnr_idx now contains 3275200 row versions in 15103 pages DETAIL: 38331 index row versions were removed. 579 index pages have been deleted, 579 are currently reusable. CPU 0.66s/1.03u sec elapsed 68.38 sec. INFO: index rid_toode_idx now contains 3275224 row versions in 31094 pages DETAIL: 38331 index row versions were removed. 2290 index pages have been deleted, 2290 are currently reusable. CPU 1.39s/1.58u sec elapsed 333.82 sec. INFO: index rid_rtellimus_idx now contains 3275230 row versions in 7390 pages DETAIL: 18591 index row versions were removed. 0 index pages
Re: [PERFORM] Hash join on int takes 8..114 seconds
Just the most important points: 1) dok table contains 1235086 row versions in 171641 pages (with 8kB pages this means 1.4GB MB of data), but there are 1834279 unused item pointers (i.e. about 60% of the space is wasted) 2) rid table contains 3275189 roiws in 165282 (with 8kB pages this means about 1.3GB of data), but there are 1878923 unused item pointers (i.e. about 30% of the space is wasted) 3) don't forget to execute analyze after vacuuming (or vacuum analyze) 4) I'm not sure why the sizes reported by you (for example 2.3GB vs 1.5GB for doc table) - the difference seems too large for me. Anyway the amount of wasted rows seems significant to me - I'd try to solve this first. Either by VACUUM FULL or by CLUSTER. The CLUSTER will lock the table exclusively, but the results may be better (when sorting by a well chosen index). Don't forget to run ANALYZE afterwards. Several other things to consider: 1) Regarding the toode column - why are you using CHAR(20) when the values are actually shorter? This may significantly increase the amount of space required. 2) I've noticed the CPU used is Celeron, which may negatively affect the speed of hash computation. I'd try to replace it by something faster - say INTEGER as an artificial primary key of the toode table and using it as a FK in other tables. This might improve the Bitmap Heap Scan on rid part, but yes - it's just a minor improvement compared to the Hash Join part of the query. Materialized views seem like a good idea to me, but maybe I'm not seeing something. What do you mean by reports are different? If there is a lot of rows for a given product / day, then creating an aggregated table with (product code / day) as a primary key is quite simple. It may require a lot of disk space, but it'll remove the hash join overhead. But if the queries are very different, then it may be difficult to build such materialized view(s). regards Tomas PFC, thank you. OK so vmstat says you are IO-bound, this seems logical if the same plan has widely varying timings... Let's look at the usual suspects : - how many dead rows in your tables ? are your tables data, or bloat ? (check vacuum verbose, etc) set search_path to firma2,public; vacuum verbose dok; vacuum verbose rid INFO: vacuuming firma2.dok INFO: index dok_pkey now contains 1235086 row versions in 9454 pages DETAIL: 100 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.16s/0.38u sec elapsed 0.77 sec. INFO: index dok_dokumnr_idx now contains 1235086 row versions in 9454 pages DETAIL: 100 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.14s/0.40u sec elapsed 0.78 sec. INFO: index dok_klient_idx now contains 1235086 row versions in 18147 pages DETAIL: 887 index row versions were removed. 3265 index pages have been deleted, 3033 are currently reusable. CPU 0.36s/0.46u sec elapsed 31.87 sec. INFO: index dok_krdokumnr_idx now contains 1235086 row versions in 11387 pages DETAIL: 119436 index row versions were removed. 1716 index pages have been deleted, 1582 are currently reusable. CPU 0.47s/0.55u sec elapsed 63.38 sec. INFO: index dok_kuupaev_idx now contains 1235101 row versions in 10766 pages DETAIL: 119436 index row versions were removed. 659 index pages have been deleted, 625 are currently reusable. CPU 0.62s/0.53u sec elapsed 40.20 sec. INFO: index dok_tasudok_idx now contains 1235104 row versions in 31348 pages DETAIL: 119436 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 1.18s/1.08u sec elapsed 118.97 sec. INFO: index dok_tasudok_unique_idx now contains 99 row versions in 97 pages DETAIL: 98 index row versions were removed. 80 index pages have been deleted, 80 are currently reusable. CPU 0.00s/0.00u sec elapsed 0.48 sec. INFO: index dok_tasumata_idx now contains 1235116 row versions in 11663 pages DETAIL: 119436 index row versions were removed. 5340 index pages have been deleted, 5131 are currently reusable. CPU 0.43s/0.56u sec elapsed 53.96 sec. INFO: index dok_tellimus_idx now contains 1235122 row versions in 11442 pages DETAIL: 119436 index row versions were removed. 1704 index pages have been deleted, 1569 are currently reusable. CPU 0.45s/0.59u sec elapsed 76.91 sec. INFO: index dok_yksus_pattern_idx now contains 1235143 row versions in 5549 pages DETAIL: 119436 index row versions were removed. 529 index pages have been deleted, 129 are currently reusable. CPU 0.19s/0.46u sec elapsed 2.72 sec. INFO: index dok_doktyyp now contains 1235143 row versions in 3899 pages DETAIL: 119436 index row versions were removed. 188 index pages have been deleted, 13 are currently reusable. CPU 0.14s/0.44u sec elapsed 1.40 sec. INFO: index dok_sihtyksus_pattern_idx now contains 1235143 row versions in 5353 pages DETAIL: 119436 index row versions were removed. 286 index pages
Re: [PERFORM] Hash join on int takes 8..114 seconds
Andrus wrote: - what's the size of the dataset relative to the RAM ? Db size is 7417 MB relevant table sizes in desc by size order: 140595 dok 2345 MB 2 1214 pg_shdepend 2259 MB 6 1232 pg_shdepend_depender_index 795 MB 7 1233 pg_shdepend_reference_index 438 MB These three are highly suspicious. They track dependencies between system object (so you can't drop function F because trigger T depends on it). http://www.postgresql.org/docs/8.3/static/catalog-pg-shdepend.html You've got 3.5GB of data there, which is a *lot* of dependencies. Try SELECT count(*) FROM pg_shdepend. If it's not a million rows, then the table is bloated. Try (as postgres or some other db superuser) vacuum full pg_shdepend and a reindex pg_shdepend. If it is a million rows, you'll need to find out why. Do you have a lot of temporary tables that aren't being dropped or something similar? -- Richard Huxton Archonet Ltd -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Richard, Thank you. Try SELECT count(*) FROM pg_shdepend. This query returns 3625 and takes 35 seconds to run. If it's not a million rows, then the table is bloated. Try (as postgres or some other db superuser) vacuum full pg_shdepend and a reindex pg_shdepend. vacuum full verbose pg_shdepend INFO: vacuuming pg_catalog.pg_shdepend INFO: pg_shdepend: found 16103561 removable, 3629 nonremovable row versions in 131425 pages DETAIL: 0 dead row versions cannot be removed yet. Nonremovable row versions range from 49 to 49 bytes long. There were 0 unused item pointers. Total free space (including removable row versions) is 1009387632 bytes. 131363 pages are or will become empty, including 0 at the end of the table. 131425 pages containing 1009387632 free bytes are potential move destinations. CPU 2.12s/1.69u sec elapsed 52.66 sec. INFO: index pg_shdepend_depender_index now contains 3629 row versions in 101794 pages DETAIL: 16103561 index row versions were removed. 101311 index pages have been deleted, 2 are currently reusable. CPU 20.12s/14.52u sec elapsed 220.66 sec. After 400 seconds of run I got phone calls that server does not respond to other clients. So I was forced to cancel vacuum full verbose pg_shdepend command. How to run it so that other users can use database at same time ? If it is a million rows, you'll need to find out why. Do you have a lot of temporary tables that aren't being dropped or something similar? Application creates temporary tables in many places. Every sales operation probably creates some temporary tables. Should I change something in configuration or change application (Only single POS application which is used to access this db) or is only solution to manully run vacuum full pg_shdepend reindex pg_shdepend periodically ? How to vacuum full pg_shdepend automatically so that other users can work at same time ? Hopefully this table size does not affect to query speed. Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
How to vacuum full pg_shdepend automatically so that other users can work at same time ? Your table is horribly bloated. You must use VACUUM FULL + REINDEX (as superuser) on it, however unfortunately, it is blocking. Therefore, you should wait for sunday night to do this, when noone will notice. Meanwhile, you can always VACUUM it (as superuser) and REINDEX it. And while you're at it, VACUUM FULL + reindex the entire database. To avoid such annoyances in the future, you should ensure that autovacuum runs properly ; you should investigate this. If you use a cron'ed VACUUM that does not run as superuser, then it will not be able to VACUUM the system catalogs, and the problem will come back. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Server has 2 GB RAM. It has SATA RAID 0,1 integrated controller (1.5Gbps) and SAMSUNG HD160JJ mirrored disks. You could perhaps run a little check on the performance of the RAID, is it better than linux software RAID ? Does it leverage NCQ appropriately when running queries in parallel ? -- Receipt headers: DOK ( dokumnr INT SERIAL PRIMARY KEY, kuupaev DATE --- sales date ) -- Receipt details RID ( dokumnr INT, toode CHAR(20), -- item code CONSTRAINT rid_dokumnr_fkey FOREIGN KEY (dokumnr) REFERENCES dok (dokumnr), CONSTRAINT rid_toode_fkey FOREIGN KEY (toode) REFERENCES firma2.toode (toode) ) -- Products TOODE ( toode CHAR(20) PRIMARY KEY ) OK so pretty straightforward : dok -(dokumnr)- rid -(toode)- toode toode.toode should really be an INT though. explain analyze SELECT sum(1) FROM dok JOIN rid USING (dokumnr) JOIN toode USING (toode) LEFT JOIN artliik using(grupp,liik) WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01' By the way, note that the presence of the toode table in the query above is not required at all, unless you use columns of toode in your aggregates. Let's play with that, after all, it's friday night. BEGIN; CREATE TABLE orders (order_id INTEGER NOT NULL, order_date DATE NOT NULL); CREATE TABLE products (product_id INTEGER NOT NULL, product_name TEXT NOT NULL); CREATE TABLE orders_products (order_id INTEGER NOT NULL, product_id INTEGER NOT NULL, padding1 TEXT, padding2 TEXT); INSERT INTO products SELECT n, 'product number ' || n::TEXT FROM generate_series(1,4) AS n; INSERT INTO orders SELECT n,'2000-01-01'::date + (n/1000 * '1 DAY'::interval) FROM generate_series(1,100) AS n; SET work_mem TO '1GB'; INSERT INTO orders_products SELECT a,b,'aibaifbaurgbyioubyfazierugybfoaybofauez', 'hfohbdsqbhjhqsvdfiuazvfgiurvgazrhbazboifhaoifh' FROM (SELECT DISTINCT (1+(n/10))::INTEGER AS a, (1+(random()*3))::INTEGER AS b FROM generate_series( 1,999 ) AS n) AS x; DELETE FROM orders_products WHERE product_id NOT IN (SELECT product_id FROM products); DELETE FROM orders_products WHERE order_id NOT IN (SELECT order_id FROM orders); ALTER TABLE orders ADD PRIMARY KEY (order_id); ALTER TABLE products ADD PRIMARY KEY (product_id); ALTER TABLE orders_products ADD PRIMARY KEY (order_id,product_id); ALTER TABLE orders_products ADD FOREIGN KEY (product_id) REFERENCES products( product_id ) ON DELETE CASCADE; ALTER TABLE orders_products ADD FOREIGN KEY (order_id) REFERENCES orders( order_id ) ON DELETE CASCADE; CREATE INDEX orders_date ON orders( order_date ); COMMIT; SET work_mem TO DEFAULT; ANALYZE; With the following query : EXPLAIN ANALYZE SELECT sum(1) FROM orders JOIN orders_products USING (order_id) JOIN products USING (product_id) WHERE orders.order_date BETWEEN '2000-01-01' AND '2000-02-01' AND products.product_id = 12345; I get the following results : orders_products has a PK index on (order_id, product_id). I dropped it. No index on orders_products : = Big seq scan (16 seconds) Index on orders_products( product_id ) : Aggregate (cost=2227.22..2227.23 rows=1 width=0) (actual time=108.204..108.205 rows=1 loops=1) - Nested Loop (cost=1312.30..2227.20 rows=7 width=0) (actual time=105.929..108.191 rows=6 loops=1) - Index Scan using products_pkey on products (cost=0.00..8.27 rows=1 width=4) (actual time=0.010..0.014 rows=1 loops=1) Index Cond: (product_id = 12345) - Hash Join (cost=1312.30..2218.85 rows=7 width=4) (actual time=105.914..108.167 rows=6 loops=1) Hash Cond: (orders_products.order_id = orders.order_id) - Bitmap Heap Scan on orders_products (cost=6.93..910.80 rows=232 width=8) (actual time=0.194..2.175 rows=246 loops=1) Recheck Cond: (product_id = 12345) - Bitmap Index Scan on orders_products_product_id (cost=0.00..6.87 rows=232 width=0) (actual time=0.129..0.129 rows=246 loops=1) Index Cond: (product_id = 12345) - Hash (cost=949.98..949.98 rows=28432 width=4) (actual time=105.696..105.696 rows=31999 loops=1) - Index Scan using orders_date on orders (cost=0.00..949.98 rows=28432 width=4) (actual time=0.059..64.443 rows=31999 loops=1) Index Cond: ((order_date = '2000-01-01'::date) AND (order_date = '2000-02-01'::date)) Total runtime: 108.357 ms (don't trust this timing, it's a bit cached, this is the same plan as you get) Index on orders_products( product_id ) and orders_products( order_id ): = Same plan Note that in this case, a smarter planner would use the new index to perform a BitmapAnd before hitting the heap to get the rows. Index on ( order_id, product_id ), orders_products( product_id ): Index on ( order_id, product_id ): = Different plan, slower (especially in second
Re: [PERFORM] Hash join on int takes 8..114 seconds
Thomas, Thank you. Just the most important points: 1) dok table contains 1235086 row versions in 171641 pages (with 8kB pages this means 1.4GB MB of data), but there are 1834279 unused item pointers (i.e. about 60% of the space is wasted) 2) rid table contains 3275189 roiws in 165282 (with 8kB pages this means about 1.3GB of data), but there are 1878923 unused item pointers (i.e. about 30% of the space is wasted) 3) don't forget to execute analyze after vacuuming (or vacuum analyze) autovacuum is running. So if I understand properly, I must ran VACUUM FULL ANALYZE dok; VACUUM FULL ANALYZE rid; Those commands cause server probably to stop responding to other client like vacuum full pg_shdepend did. Should vacuum_cost_delay = 2000 allow other users to work when running those commands ? 4) I'm not sure why the sizes reported by you (for example 2.3GB vs 1.5GB for doc table) - the difference seems too large for me. I used pg_total_relation_size(). So 2.3 GB includes indexes also: 844286 dok_tasudok_idx245 MB 1044283 dok_klient_idx 142 MB 1844288 dok_tasumata_idx 91 MB 1944289 dok_tellimus_idx 89 MB 2044284dok_krdokumnr_idx 89 MB 2144285 dok_kuupaev_idx84 MB 2243531 makse_pkey 77 MB 2343479 dok_pkey 74 MB 2444282 dok_dokumnr_idx74 MB 26 18663923 dok_yksus_pattern_idx 43 MB 27 18801591 dok_sihtyksus_pattern_idx 42 MB Anyway the amount of wasted rows seems significant to me - I'd try to solve this first. Either by VACUUM FULL or by CLUSTER. The CLUSTER will lock the table exclusively, but the results may be better (when sorting by a well chosen index). Don't forget to run ANALYZE afterwards. How to invoke those commands so that other clients can continue work? I'm using 8.1.4. Log files show that autovacuum is running. I'm planning the following solution: 1. Set vacuum_cost_delay=2000 2. Run the following commands periodically in this order: VACUUM FULL; vacuum full pg_shdepend; CLUSTER rid on (toode); CLUSTER dok on (kuupaev); REINDEX DATABASE mydb; REINDEX SYSTEM mydb; ANALYZE; Are all those command required or can something leaved out ? Several other things to consider: 1) Regarding the toode column - why are you using CHAR(20) when the values are actually shorter? This may significantly increase the amount of space required. There may be some products whose codes may be up to 20 characters. PostgreSQL does not hold trailing spaces in db, so this does *not* affect to space. 2) I've noticed the CPU used is Celeron, which may negatively affect the speed of hash computation. I'd try to replace it by something faster - say INTEGER as an artificial primary key of the toode table and using it as a FK in other tables. This might improve the Bitmap Heap Scan on rid part, but yes - it's just a minor improvement compared to the Hash Join part of the query. Natural key Toode CHAR(20) is used widely in different queries. Replacing it with INT surrogate key requires major application rewrite. Should I add surrogate index INT columns to toode and rid table and measure test query speed in this case? Materialized views seem like a good idea to me, but maybe I'm not seeing something. What do you mean by reports are different? If there is a lot of rows for a given product / day, then creating an aggregated table with (product code / day) as a primary key is quite simple. It may require a lot of disk space, but it'll remove the hash join overhead. But if the queries are very different, then it may be difficult to build such materialized view(s). log file seems that mostly only those queries are slow: SELECT ... FROM dok JOIN rid USING (dokumnr) JOIN ProductId USING (ProductId) WHERE rid.ProductId LIKE :p1 || '%' AND dok.SaleDate=:p2 :p1 and :p2 are parameters different for different queries. dok contains several years of data. :p2 is usually only few previous months or last year ago. SELECT column list contains fixed list of known columns from all tables. How to create index or materialized view to optimize this types of queries ? Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
log file seems that mostly only those queries are slow: SELECT ... FROM dok JOIN rid USING (dokumnr) JOIN ProductId USING (ProductId) WHERE rid.ProductId LIKE :p1 || '%' AND dok.SaleDate=:p2 :p1 and :p2 are parameters different for different queries. dok contains several years of data. :p2 is usually only few previous months or last year ago. SELECT column list contains fixed list of known columns from all tables. How to create index or materialized view to optimize this types of queries ? I would remove some granularity, for instance create a summary table (materialized view) by month : - date (contains the first day of the month) - product_id - total quantity, total price sold in given month You get the idea. If your products belong to categories, and you make queries on all the products in a category, it could be worth making a summary table for categories also. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
How to vacuum full pg_shdepend automatically so that other users can work at same time ? Your table is horribly bloated. You must use VACUUM FULL + REINDEX (as superuser) on it, however unfortunately, it is blocking. Therefore, you should wait for sunday night to do this, when noone will notice. Shops are closed late night for a short time, including sunday night. This time may be shorter than time required to complete VACUUM command. I discovered vacuum_cost_delay=2000 option. Will this remove blocking issue and allow vacuum full to work ? Meanwhile, you can always VACUUM it (as superuser) and REINDEX it. I expect that autovacuum does this automatically. And while you're at it, VACUUM FULL + reindex the entire database. To avoid such annoyances in the future, you should ensure that autovacuum runs properly ; you should investigate this. If you use a cron'ed VACUUM that does not run as superuser, then it will not be able to VACUUM the system catalogs, and the problem will come back. autovacuum is turned on in postgresql.conf file log file shows a lot of messages every day that database is vacuumed. I assume that it is running as user postgres. I do'nt understand how autovacuum can avoid this: it does not perform vacuum full so pg_shdepend ja my tables become bloated again and again. Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
On Friday 21 November 2008, Andrus [EMAIL PROTECTED] wrote: Those commands cause server probably to stop responding to other client like vacuum full pg_shdepend did. Should vacuum_cost_delay = 2000 allow other users to work when running those commands ? Any vacuum full or cluster will lock out other clients. A high vacuum_cost_delay will just make the vacuum run slower. -- Corporations will ingest natural resources and defecate garbage until all resources are depleted, debt can no longer be repaid and our money becomes worthless - Jay Hanson -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Andrus wrote: I discovered vacuum_cost_delay=2000 option. Will this remove blocking issue and allow vacuum full to work ? No. Are you really using vacuum_cost_delay=2000? If so, therein lies your problem. That's a silly value to use for that variable. Useful values are in the 20-40 range probably, or maybe 10-100 being extremely generous. -- Alvaro Herrerahttp://www.CommandPrompt.com/ PostgreSQL Replication, Consulting, Custom Development, 24x7 support -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Andrus wrote: Will value of 30 allow other clients to work when VACUUM FULL is running ? 1. vacuum_cost_delay does not affect vacuum full 2. vacuum full is always blocking, regardless of settings So I gather you're not doing any vacuuming, eh? -- Alvaro Herrerahttp://www.CommandPrompt.com/ The PostgreSQL Company - Command Prompt, Inc. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
PFC [EMAIL PROTECTED] writes: Index on orders_products( product_id ) and orders_products( order_id ): = Same plan Note that in this case, a smarter planner would use the new index to perform a BitmapAnd before hitting the heap to get the rows. Considering that the query has no constraint on orders_products.order_id, I'm not sure what you think the extra index is supposed to be used *for*. (Well, we could put orders as the outside of a nestloop and then we'd have such a constraint, but with 3 orders rows to process that plan would lose big.) (And yes, the planner did consider such a plan along the way. See choose_bitmap_and.) regards, tom lane -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Alvaro, 1. vacuum_cost_delay does not affect vacuum full 2. vacuum full is always blocking, regardless of settings So only way is to disable other database acces if vacuum full is required. So I gather you're not doing any vacuuming, eh? Log files for every day are full of garbage messages below. So I hope that vacuum is running well, isn't it ? Andrus. 2008-11-19 00:00:48 EET11728 1 LOG: autovacuum: processing database postgres 2008-11-19 00:01:48 EET11729 1 LOG: autovacuum: processing database mydb1 2008-11-19 00:02:48 EET11730 1 LOG: autovacuum: processing database emydb1 2008-11-19 00:03:48 EET11731 1 LOG: autovacuum: processing database template1 2008-11-19 00:04:48 EET11732 1 LOG: autovacuum: processing database testmydb1 2008-11-19 00:05:48 EET11733 1 LOG: autovacuum: processing database mydb3 2008-11-19 00:06:48 EET11734 1 LOG: autovacuum: processing database postgres 2008-11-19 00:07:48 EET11735 1 LOG: autovacuum: processing database mydb1 2008-11-19 00:08:48 EET11736 1 LOG: autovacuum: processing database emydb1 2008-11-19 00:09:48 EET11737 1 LOG: autovacuum: processing database template1 2008-11-19 00:10:48 EET11750 1 LOG: autovacuum: processing database testmydb1 2008-11-19 00:11:48 EET11751 1 LOG: autovacuum: processing database mydb3 2008-11-19 00:12:48 EET11752 1 LOG: autovacuum: processing database postgres 2008-11-19 00:13:48 EET11753 1 LOG: autovacuum: processing database mydb1 2008-11-19 00:14:48 EET11754 1 LOG: autovacuum: processing database emydb1 2008-11-19 00:15:48 EET11755 1 LOG: autovacuum: processing database template1 2008-11-19 00:16:48 EET11756 1 LOG: autovacuum: processing database testmydb1 2008-11-19 00:17:48 EET11757 1 LOG: autovacuum: processing database mydb3 ... -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Andrus wrote: So I gather you're not doing any vacuuming, eh? Log files for every day are full of garbage messages below. So I hope that vacuum is running well, isn't it ? This does not really mean that autovacuum has done anything in the databases. If the times are consistently separated by 1 min, then it's possible that it always exits without doing anything. In such old a release we didn't have any decent logging mechanism in autovacuum :-( You can change log_min_messages to debug2 to see if it actually does anything or not. I suggest you connect to the problem database (and then to all others, just to be sure) and run vacuum (no full). -- Alvaro Herrerahttp://www.CommandPrompt.com/ PostgreSQL Replication, Consulting, Custom Development, 24x7 support -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Thank you. My 8.1.4 postgresql.conf does not contain such option. So vacuum_cost_delay is off probably. Since doc does not recommend any value, I planned to use 2000 Will value of 30 allow other clients to work when VACUUM FULL is running ? No, as someone already noted the VACUUM FULL is blocking anyway (and does not use this value at all). Uncommented relevant values in postgresql.conf file are: shared_buffers = 15000 work_mem = 512 I'd consider increasing this value a little - 0.5 MB seems too low to me (but not necessarily). maintenance_work_mem = 131072 fsync = on effective_cache_size= 7 Well, your server has 2GB of RAM and usually it's recommended to set this value to about 60-70% of your RAM, so using 540MB (25%) seems quite low. Anyway this is just a hint to PostgreSQL, it does not increase memory consumption or so - it's just an estimate of how much data are cached by kernel. Anyway, I don't expect these values have significant effect in case of the issue solved in this thread. regards Tomas -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
2. Run the following commands periodically in this order: VACUUM FULL; vacuum full pg_shdepend; CLUSTER rid on (toode); CLUSTER dok on (kuupaev); REINDEX DATABASE mydb; REINDEX SYSTEM mydb; ANALYZE; Are all those command required or can something leaved out ? Running CLUSTER after VACUUM FULL is just a waste of time. In my experience CLUSTER is actually faster in case of such heavily bloated tables - I think this is caused by the fact that it creates indexes from the beginning instead of updating them (as VACUUM FULL does). So CLUSTER actually performs REINDEX, so I'd just run CLUSTER rid ON rid_pkey; CLUSTER dok ON dok_pkey; ANALYZE rid; ANALYZE dok; Clustering by other indexes might give better performance, using primary keys is just a safe guess here. This should improve the performance of your query and it seems these two tables are the most bloated ones. I wouldn't do the same maintenance on the other tables now - it's just a waste of time. Several other things to consider: 1) Regarding the toode column - why are you using CHAR(20) when the values are actually shorter? This may significantly increase the amount of space required. There may be some products whose codes may be up to 20 characters. PostgreSQL does not hold trailing spaces in db, so this does *not* affect to space. OK, I haven't realized this. You're right. 2) I've noticed the CPU used is Celeron, which may negatively affect the speed of hash computation. I'd try to replace it by something faster - say INTEGER as an artificial primary key of the toode table and using it as a FK in other tables. This might improve the Bitmap Heap Scan on rid part, but yes - it's just a minor improvement compared to the Hash Join part of the query. Natural key Toode CHAR(20) is used widely in different queries. Replacing it with INT surrogate key requires major application rewrite. Should I add surrogate index INT columns to toode and rid table and measure test query speed in this case? Test it. Create tables with fake data, and compare the performance with and without the surrogate keys. Using a simple data type instead of text gave me huge performance boost. For example one of my colleagues used VARCHAR(15) to store IP addresses, and then used them to join tables (and suffered by the poor perfomance). Replacing them by INET improved the speed by several orders of magnitude. Materialized views seem like a good idea to me, but maybe I'm not seeing something. What do you mean by reports are different? If there is a lot of rows for a given product / day, then creating an aggregated table with (product code / day) as a primary key is quite simple. It may require a lot of disk space, but it'll remove the hash join overhead. But if the queries are very different, then it may be difficult to build such materialized view(s). log file seems that mostly only those queries are slow: SELECT ... FROM dok JOIN rid USING (dokumnr) JOIN ProductId USING (ProductId) WHERE rid.ProductId LIKE :p1 || '%' AND dok.SaleDate=:p2 :p1 and :p2 are parameters different for different queries. dok contains several years of data. :p2 is usually only few previous months or last year ago. SELECT column list contains fixed list of known columns from all tables. How to create index or materialized view to optimize this types of queries ? Well, difficult to answer without detailed information about the queries you want to run, aggregated values, etc. Materialized views is a world on it's own, and the best solution depends on (for example): 1) what aggregated values are you interested in (additive values are the most primitive ones, while VARIANCE etc. make it difficult) 2) do you need current data, or is it OK that today's data are not available till midnight (for example)? Another thing you have to consider is whether you want to create materialized view with final or intermediary data and then compute the final data somehow (for example monthly totals from daily totals). The most primitive (but often sufficient) solution is recreating the materialized view periodically (for example every midnight). In your case it'd mean running something like CREATE TABLE materialized_view AS SELECT ... your query here ... GROUP BY productId, saleDate This gives you daily totals for each product - the clients then can run another query to compute the final data. But of course, if you need to maintain 'current' data, you may create a set of triggers to update the materialized view. Either after each modification or (more sophisticated) when it's needed. See for example a great presentation from this year's PGCon: http://www.pgcon.org/2008/schedule/events/69.en.html regards Tomas -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
If Autovacuum was working, and your tables still got very bloated, it may be because your free space map is not configured large enough. What is your value for max_fsm_pages? The effect of having max_fsm_pages or max_fsm_relations too small is bloating of tables and indexes. Increasing it too large will not use a lot of memory. Since you had over 13 free pages in just one table below, make sure it is set to at least 15. This may be overkill with regular vacuum or autovacuum, however its much better to have this too large than too small. Your server has 2GB of RAM? You should make sure your shared_buffers is between 100MB and 400MB if this is a dedicated server, or more in some cases. If you can, plan to migrate to 8.3 (or 8.4 early next year). Vacuum, bloating, and configuration related to these have improved a great deal since 8.1. Although your Indexes below remain bloated, the fact that they have been vacuumed, combined with a large enough value set in max_fsm_pages, means that they should not get any larger. I am not sure how to foce these to be smaller. The larger size, after a vacuum and large enough max_fsm_pages value will also not cause a performance problem. It will waste some disk space and be a bit slower to access, but only very slightly. -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Andrus Sent: Friday, November 21, 2008 1:51 PM To: Richard Huxton Cc: PFC; pgsql-performance@postgresql.org Subject: Re: [PERFORM] Hash join on int takes 8..114 seconds If it's not a million rows, then the table is bloated. Try (as postgres or some other db superuser) vacuum full pg_shdepend and a reindex pg_shdepend. reindex table pg_shdepend causes error ERROR: shared table pg_shdepend can only be reindexed in stand-alone mode vacuum full verbose pg_shdepend seems to work but indexes are still bloated. How to remove index bloat ? sizes after vacuum full are below. pg_shdepend size 1234 MB includes its index sizes, so indexes are 100% bloated. 4 1214 pg_catalog.pg_shdepend1234 MB 6 1232 pg_catalog.pg_shdepend_depender_index 795 MB 7 1233 pg_catalog.pg_shdepend_reference_index439 MB Andrus. vacuum full verbose pg_shdepend; INFO: vacuuming pg_catalog.pg_shdepend INFO: pg_shdepend: found 254 removable, 3625 nonremovable row versions in 131517 pages DETAIL: 0 dead row versions cannot be removed yet. Nonremovable row versions range from 49 to 49 bytes long. There were 16115259 unused item pointers. Total free space (including removable row versions) is 1010091872 bytes. 131456 pages are or will become empty, including 8 at the end of the table. 131509 pages containing 1010029072 free bytes are potential move destinations. CPU 2.08s/0.92u sec elapsed 63.51 sec. INFO: index pg_shdepend_depender_index now contains 3625 row versions in 101794 pages DETAIL: 254 index row versions were removed. 101611 index pages have been deleted, 2 are currently reusable. CPU 0.87s/0.28u sec elapsed 25.44 sec. INFO: index pg_shdepend_reference_index now contains 3625 row versions in 56139 pages DETAIL: 254 index row versions were removed. 56076 index pages have been deleted, 2 are currently reusable. CPU 0.51s/0.15u sec elapsed 23.10 sec. INFO: pg_shdepend: moved 1518 row versions, truncated 131517 to 25 pages DETAIL: CPU 5.26s/2.39u sec elapsed 89.93 sec. INFO: index pg_shdepend_depender_index now contains 3625 row versions in 101794 pages DETAIL: 1518 index row versions were removed. 101609 index pages have been deleted, 2 are currently reusable. CPU 0.94s/0.28u sec elapsed 24.61 sec. INFO: index pg_shdepend_reference_index now contains 3625 row versions in 56139 pages DETAIL: 1518 index row versions were removed. 56088 index pages have been deleted, 2 are currently reusable. CPU 0.54s/0.14u sec elapsed 21.11 sec. Query returned successfully with no result in 253356 ms -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Just a question, what are you doing with the 20.000 result rows ? Those rows represent monthly sales data of one item. They are used as following: 1. Detailed sales report for month. This report can browsed in screen for montly sales and ordering analysis. 2. Total reports. In those reports, sum( sales), sum(quantity) is used to get total sales in day, week, month, time for item and resulting rows are summed. Andrus. -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Andrus wrote: Query below seems to use indexes everywhere in most optimal way. dokumnr column is of type int Speed of this query varies rapidly: In live db fastest response I have got is 8 seconds. Re-running same query after 10 seconds may take 60 seconds. Re-running it again after 10 seconds may take 114 seconds. Any idea how to speed it up ? Is it possible to optimize it, will upgrading to 8.3.5 help or should I require to add more RAM, disk or CPU speed ? At a quick glance, the plans look the same to me. The overall costs are certainly identical. That means whatever is affecting the query times it isn't the query plan. Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual time=62164.496..62164.500 rows=1 loops=1) Total runtime: 62164.789 ms Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual time=40185.499..40185.503 rows=1 loops=1) Total runtime: 40186.102 ms Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual time=29650.398..29650.402 rows=1 loops=1) Total runtime: 29650.696 ms Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual time=11131.392..11131.396 rows=1 loops=1) Total runtime: 11131.694 ms So - what other activity is happening on this machine? Either other queries are taking up noticeable resources, or some other process is (it might be disk activity from checkpointing, logging some other application). -- Richard Huxton Archonet Ltd -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
Richard, At a quick glance, the plans look the same to me. The overall costs are certainly identical. That means whatever is affecting the query times it isn't the query plan. So - what other activity is happening on this machine? Either other queries are taking up noticeable resources, or some other process is (it might be disk activity from checkpointing, logging some other application). Thank you. This is dedicated server running only PostgreSql which serves approx 6 point of sales at this time. Maybe those other clients make queries which invalidate lot of data loaded into server cache. In next time server must read it again from disk which causes those perfomance differences. top output is currently: top - 13:13:10 up 22 days, 18:25, 1 user, load average: 0.19, 0.12, 0.19 Tasks: 53 total, 2 running, 51 sleeping, 0 stopped, 0 zombie Cpu(s): 13.7% us, 2.0% sy, 0.0% ni, 78.3% id, 6.0% wa, 0.0% hi, 0.0% si Mem: 2075828k total, 2022808k used,53020k free,0k buffers Swap: 3911816k total, 88k used, 3911728k free, 1908536k cached PID USER PR NI VIRT RES SHR S %CPU %MEMTIME+ COMMAND 5382 postgres 15 0 144m 43m 40m S 15.0 2.2 0:00.45 postmaster 5358 postgres 15 0 152m 87m 75m S 0.3 4.3 0:00.97 postmaster 1 root 16 0 1480 508 444 S 0.0 0.0 0:01.35 init 2 root 34 19 000 S 0.0 0.0 0:00.01 ksoftirqd/0 3 root 10 -5 000 S 0.0 0.0 0:00.00 events/0 4 root 10 -5 000 S 0.0 0.0 0:00.42 khelper 5 root 10 -5 000 S 0.0 0.0 0:00.00 kthread 7 root 10 -5 000 S 0.0 0.0 2:03.91 kblockd/0 8 root 20 -5 000 S 0.0 0.0 0:00.00 kacpid 115 root 13 -5 000 S 0.0 0.0 0:00.00 aio/0 114 root 15 0 000 S 0.0 0.0 8:49.67 kswapd0 116 root 10 -5 000 S 0.0 0.0 0:10.32 xfslogd/0 117 root 10 -5 000 S 0.0 0.0 0:39.96 xfsdatad/0 706 root 10 -5 000 S 0.0 0.0 0:00.00 kseriod 723 root 13 -5 000 S 0.0 0.0 0:00.00 kpsmoused 738 root 11 -5 000 S 0.0 0.0 0:00.00 ata/0 740 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_0 741 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_1 742 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_2 743 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_3 762 root 10 -5 000 S 0.0 0.0 0:17.54 xfsbufd 763 root 10 -5 000 S 0.0 0.0 0:00.68 xfssyncd 963 root 16 -4 1712 528 336 S 0.0 0.0 0:00.24 udevd 6677 root 15 0 1728 572 400 S 0.0 0.0 0:04.99 syslog-ng 7128 postgres 16 0 140m 10m 9900 S 0.0 0.5 0:05.60 postmaster in few seconds later: top - 13:14:01 up 22 days, 18:26, 1 user, load average: 1.72, 0.53, 0.32 Tasks: 52 total, 2 running, 50 sleeping, 0 stopped, 0 zombie Cpu(s): 5.3% us, 3.0% sy, 0.0% ni, 0.0% id, 91.0% wa, 0.0% hi, 0.7% si Mem: 2075828k total, 2022692k used,53136k free,0k buffers Swap: 3911816k total, 88k used, 3911728k free, 1905028k cached PID USER PR NI VIRT RES SHR S %CPU %MEMTIME+ COMMAND 1179 postgres 18 0 155m 136m 122m D 6.7 6.7 1:32.52 postmaster 4748 postgres 15 0 145m 126m 122m D 1.3 6.2 0:14.38 postmaster 5358 postgres 16 0 160m 98m 81m D 0.7 4.9 0:01.21 postmaster 1 root 16 0 1480 508 444 S 0.0 0.0 0:01.35 init 2 root 34 19 000 S 0.0 0.0 0:00.01 ksoftirqd/0 3 root 10 -5 000 S 0.0 0.0 0:00.00 events/0 4 root 10 -5 000 S 0.0 0.0 0:00.42 khelper 5 root 10 -5 000 S 0.0 0.0 0:00.00 kthread 7 root 10 -5 000 S 0.0 0.0 2:03.97 kblockd/0 8 root 20 -5 000 S 0.0 0.0 0:00.00 kacpid 115 root 13 -5 000 S 0.0 0.0 0:00.00 aio/0 114 root 15 0 000 S 0.0 0.0 8:49.79 kswapd0 116 root 10 -5 000 S 0.0 0.0 0:10.32 xfslogd/0 117 root 10 -5 000 S 0.0 0.0 0:39.96 xfsdatad/0 706 root 10 -5 000 S 0.0 0.0 0:00.00 kseriod 723 root 13 -5 000 S 0.0 0.0 0:00.00 kpsmoused 738 root 11 -5 000 S 0.0 0.0 0:00.00 ata/0 740 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_0 741 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_1 742 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_2 743 root 11 -5 000 S 0.0 0.0 0:00.00 scsi_eh_3 762 root 10 -5 000 S 0.0 0.0 0:17.54 xfsbufd 763 root 10 -5 000 S 0.0 0.0 0:00.68 xfssyncd 963 root 16 -4 1712 528 336 S 0.0 0.0 0:00.24
Re: [PERFORM] Hash join on int takes 8..114 seconds
Andrus wrote: Richard, At a quick glance, the plans look the same to me. The overall costs are certainly identical. That means whatever is affecting the query times it isn't the query plan. So - what other activity is happening on this machine? Either other queries are taking up noticeable resources, or some other process is (it might be disk activity from checkpointing, logging some other application). Thank you. This is dedicated server running only PostgreSql which serves approx 6 point of sales at this time. Maybe those other clients make queries which invalidate lot of data loaded into server cache. In next time server must read it again from disk which causes those perfomance differences. In addition to top below, you'll probably find vmstat 5 useful. top output is currently: top - 13:13:10 up 22 days, 18:25, 1 user, load average: 0.19, 0.12, 0.19 Tasks: 53 total, 2 running, 51 sleeping, 0 stopped, 0 zombie Cpu(s): 13.7% us, 2.0% sy, 0.0% ni, 78.3% id, 6.0% wa, 0.0% hi, 0.0% si Mem: 2075828k total, 2022808k used,53020k free,0k buffers Swap: 3911816k total, 88k used, 3911728k free, 1908536k cached PID USER PR NI VIRT RES SHR S %CPU %MEMTIME+ COMMAND 5382 postgres 15 0 144m 43m 40m S 15.0 2.2 0:00.45 postmaster 5358 postgres 15 0 152m 87m 75m S 0.3 4.3 0:00.97 postmaster 1 root 16 0 1480 508 444 S 0.0 0.0 0:01.35 init Looks pretty quiet. in few seconds later: top - 13:14:01 up 22 days, 18:26, 1 user, load average: 1.72, 0.53, 0.32 Tasks: 52 total, 2 running, 50 sleeping, 0 stopped, 0 zombie Cpu(s): 5.3% us, 3.0% sy, 0.0% ni, 0.0% id, 91.0% wa, 0.0% hi, 0.7% si Mem: 2075828k total, 2022692k used,53136k free,0k buffers Swap: 3911816k total, 88k used, 3911728k free, 1905028k cached PID USER PR NI VIRT RES SHR S %CPU %MEMTIME+ COMMAND 1179 postgres 18 0 155m 136m 122m D 6.7 6.7 1:32.52 postmaster 4748 postgres 15 0 145m 126m 122m D 1.3 6.2 0:14.38 postmaster 5358 postgres 16 0 160m 98m 81m D 0.7 4.9 0:01.21 postmaster 1 root 16 0 1480 508 444 S 0.0 0.0 0:01.35 init Here you're stuck waiting for disks (91.0% wa). Check out vmstat and iostat to see what's happening. -- Richard Huxton Archonet Ltd -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
Re: [PERFORM] Hash join on int takes 8..114 seconds
OK so vmstat says you are IO-bound, this seems logical if the same plan
has widely varying timings...
Let's look at the usual suspects :
- how many dead rows in your tables ? are your tables data, or bloat ?
(check vacuum verbose, etc)
- what's the size of the dataset relative to the RAM ?
Now let's look more closely at the query :
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
LEFT JOIN artliik using(grupp,liik)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
OK, so artliik is a very small table (84 rows) :
Seq Scan on artliik (cost=0.00..6.84 rows=84 width=19)
(actual time=20.104..29.845 rows=84 loops=1)
I presume doing the query without artliik changes nothing to the runtime,
yes ?
Let's look at the main part of the query :
FROM dok JOIN rid USING (dokumnr) JOIN toode USING (toode)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
Postgres's plan is logical. It starts by joining rid and dok since your
WHERE is on those :
- Hash Join (cost=52103.94..233488.08 rows=24126 width=24) (actual
time=100386.921..114037.986 rows=20588 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4127.51..175020.84 rows=317003
width=28) (actual time=9.932..76225.918 rows=277294 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx (cost=0.00..4127.51 rows=317003
width=0) (actual time=11105.807..11105.807 rows=280599 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=47376.82..47376.82 rows=93444 width=4) (actual
time=35082.427..35082.427 rows=105202 loops=1)
- Index Scan using dok_kuupaev_idx on dok (cost=0.00..47376.82
rows=93444 width=4) (actual time=42.110..34586.331 rows=105202 loops=1)
Index Cond: (kuupaev = '2008-09-01'::date)
Your problem here is that, no matter what, postgres will have to examine
- all rows where dok.kuupaev='2008-09-01',
- and all rows where rid.toode = 'X05'.
If you use dok.kuupaev='2007-09-01' (note : 2007) it will probably have
to scan many, many more rows.
If you perform this query often you could CLUSTER rid on (toode) and dok
on (kuupaev), but this can screw other queries.
What is the meaning of the columns ?
To make this type of query faster I would tend to think about :
- materialized views
- denormalization (ie adding a column in one of your tables and a
multicolumn index)
- materialized summary tables (ie. summary of sales for last month, for
instance)
Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual
time=114479.933..114479.936 rows=1 loops=1)
- Hash Left Join (cost=52111.20..234218.21 rows=24126 width=0)
(actual time=100435.523..114403.293 rows=20588 loops=1)
Hash Cond: ((outer.grupp = inner.grupp) AND (outer.liik =
inner.liik))
- Nested Loop (cost=52103.94..233735.35 rows=24126 width=19)
(actual time=100405.258..114207.387 rows=20588 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01
rows=1 width=43) (actual time=18.312..18.325 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=52103.94..233488.08 rows=24126
width=24) (actual time=100386.921..114037.986 rows=20588 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4127.51..175020.84
rows=317003 width=28) (actual time=9.932..76225.918 rows=277294
loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4127.51 rows=317003 width=0) (actual time=11105.807..11105.807
rows=280599 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=47376.82..47376.82 rows=93444
width=4) (actual time=35082.427..35082.427 rows=105202 loops=1)
- Index Scan using dok_kuupaev_idx on dok
(cost=0.00..47376.82 rows=93444 width=4) (actual time=42.110..34586.331
rows=105202 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
- Hash (cost=6.84..6.84 rows=84 width=19) (actual
time=30.220..30.220 rows=84 loops=1)
- Seq Scan on artliik (cost=0.00..6.84 rows=84 width=19)
(actual time=20.104..29.845 rows=84 loops=1)
Total runtime: 114480.373 ms
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[PERFORM] Hash join on int takes 8..114 seconds
Query below seems to use indexes everywhere in most optimal way.
dokumnr column is of type int
Speed of this query varies rapidly:
In live db fastest response I have got is 8 seconds.
Re-running same query after 10 seconds may take 60 seconds.
Re-running it again after 10 seconds may take 114 seconds.
Any idea how to speed it up ?
Is it possible to optimize it, will upgrading to 8.3.5 help or should I
require to add more RAM, disk or CPU speed ?
Real query contains column list instead of sum(1) used in test below.
Andrus.
explain analyze
SELECT sum(1)
FROM dok JOIN rid USING (dokumnr)
JOIN toode USING (toode)
LEFT JOIN artliik using(grupp,liik)
WHERE rid.toode='X05' AND dok.kuupaev='2008-09-01'
longest response time:
Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual
time=114479.933..114479.936 rows=1 loops=1)
- Hash Left Join (cost=52111.20..234218.21 rows=24126 width=0) (actual
time=100435.523..114403.293 rows=20588 loops=1)
Hash Cond: ((outer.grupp = inner.grupp) AND (outer.liik =
inner.liik))
- Nested Loop (cost=52103.94..233735.35 rows=24126 width=19)
(actual time=100405.258..114207.387 rows=20588 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01
rows=1 width=43) (actual time=18.312..18.325 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=52103.94..233488.08 rows=24126 width=24)
(actual time=100386.921..114037.986 rows=20588 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4127.51..175020.84
rows=317003 width=28) (actual time=9.932..76225.918 rows=277294
loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4127.51 rows=317003 width=0) (actual time=11105.807..11105.807
rows=280599 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=47376.82..47376.82 rows=93444 width=4)
(actual time=35082.427..35082.427 rows=105202 loops=1)
- Index Scan using dok_kuupaev_idx on dok
(cost=0.00..47376.82 rows=93444 width=4) (actual time=42.110..34586.331
rows=105202 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
- Hash (cost=6.84..6.84 rows=84 width=19) (actual
time=30.220..30.220 rows=84 loops=1)
- Seq Scan on artliik (cost=0.00..6.84 rows=84 width=19)
(actual time=20.104..29.845 rows=84 loops=1)
Total runtime: 114480.373 ms
Same query in other runs:
Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual
time=62164.496..62164.500 rows=1 loops=1)
- Hash Left Join (cost=52111.20..234218.21 rows=24126 width=0) (actual
time=46988.005..62088.379 rows=20588 loops=1)
Hash Cond: ((outer.grupp = inner.grupp) AND (outer.liik =
inner.liik))
- Nested Loop (cost=52103.94..233735.35 rows=24126 width=19)
(actual time=46957.750..61893.613 rows=20588 loops=1)
- Index Scan using toode_pkey on toode (cost=0.00..6.01
rows=1 width=43) (actual time=146.530..146.543 rows=1 loops=1)
Index Cond: ('X05'::bpchar = toode)
- Hash Join (cost=52103.94..233488.08 rows=24126 width=24)
(actual time=46811.194..61595.560 rows=20588 loops=1)
Hash Cond: (outer.dokumnr = inner.dokumnr)
- Bitmap Heap Scan on rid (cost=4127.51..175020.84
rows=317003 width=28) (actual time=1870.209..55864.237 rows=277294 loops=1)
Recheck Cond: (toode = 'X05'::bpchar)
- Bitmap Index Scan on rid_toode_idx
(cost=0.00..4127.51 rows=317003 width=0) (actual time=1863.713..1863.713
rows=280599 loops=1)
Index Cond: (toode = 'X05'::bpchar)
- Hash (cost=47376.82..47376.82 rows=93444 width=4)
(actual time=1650.823..1650.823 rows=105202 loops=1)
- Index Scan using dok_kuupaev_idx on dok
(cost=0.00..47376.82 rows=93444 width=4) (actual time=0.091..1190.962
rows=105202 loops=1)
Index Cond: (kuupaev =
'2008-09-01'::date)
- Hash (cost=6.84..6.84 rows=84 width=19) (actual
time=30.210..30.210 rows=84 loops=1)
- Seq Scan on artliik (cost=0.00..6.84 rows=84 width=19)
(actual time=20.069..29.836 rows=84 loops=1)
Total runtime: 62164.789 ms
Aggregate (cost=234278.53..234278.54 rows=1 width=0) (actual
time=40185.499..40185.503 rows=1 loops=1)
- Hash Left Join (cost=52111.20..234218.21 rows=24126 width=0) (actual
time=32646.761..40109.470 rows=20585 loops=1)
Hash Cond: ((outer.grupp = inner.grupp) AND (outer.liik =
inner.liik))
- Nested Loop (cost=52103.94..233735.35 rows=24126 width=19)
(actual time=32645.933..39944.242 rows=20585 loops=1)
- Index Scan using toode_pkey on toode
Re: [PERFORM] Hash join on int takes 8..114 seconds
Query below seems to use indexes everywhere in most optimal way. dokumnr column is of type int Speed of this query varies rapidly: In live db fastest response I have got is 8 seconds. Re-running same query after 10 seconds may take 60 seconds. Re-running it again after 10 seconds may take 114 seconds. Any idea how to speed it up ? Is it possible to optimize it, will upgrading to 8.3.5 help or should I require to add more RAM, disk or CPU speed ? Real query contains column list instead of sum(1) used in test below. Andrus. Just a question, what are you doing with the 20.000 result rows ? -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
