Hello,
I've been struggling to understand what's happening on my
databases/query for several days, and I'm turning to higher mind for a
logical answer.
I'm dealing with a fairly large database, containing logs informations,
that I crunch to get data out of it, with several indexes on them that I
hoped were logical
\d ruddersysevents
Table « public.ruddersysevents »
Colonne | Type |
Modificateurs
--------------------+--------------------------+--------------------------------------------------
id | integer | non NULL Par défaut,
nextval('serial'::regclass)
executiondate | timestamp with time zone | non NULL
nodeid | text | non NULL
directiveid | text | non NULL
ruleid | text | non NULL
serial | integer | non NULL
component | text | non NULL
keyvalue | text |
executiontimestamp | timestamp with time zone | non NULL
eventtype | character varying(64) |
policy | text |
msg | text |
Index :
"ruddersysevents_pkey" PRIMARY KEY, btree (id)
"component_idx" btree (component)
"configurationruleid_idx" btree (ruleid)
"executiontimestamp_idx" btree (executiontimestamp)
"keyvalue_idx" btree (keyvalue)
"nodeid_idx" btree (nodeid)
Contraintes de vérification :
"ruddersysevents_component_check" CHECK (component <> ''::text)
"ruddersysevents_configurationruleid_check" CHECK (ruleid <> ''::text)
"ruddersysevents_nodeid_check" CHECK (nodeid <> ''::text)
"ruddersysevents_policyinstanceid_check" CHECK (directiveid <>
''::text)
It contains 11018592 entries, with the followinf patterns :
108492 distinct executiontimestamp
14 distinct nodeid
59 distinct directiveid
26 distinct ruleid
35 distinct serial
Related table/index size are
relation | size
----------------------------------------+---------
public.ruddersysevents | 3190 MB
public.nodeid_idx | 614 MB
public.configurationruleid_idx | 592 MB
public.ruddersysevents_pkey | 236 MB
public.executiontimestamp_idx | 236 MB
I'm crunching the data by looking for each
nodeid/ruleid/directiveid/serial with an executiontimestamp in an interval:
explain analyze select executiondate, nodeid, ruleid, directiveid,
serial, component, keyValue, executionTimeStamp, eventtype, policy, msg
from RudderSysEvents where 1=1 and nodeId =
'31264061-5ecb-4891-9aa4-83824178f43d' and ruleId =
'61713ff1-aa6f-4c86-b3cb-7012bee707dd' and serial = 10 and
executiontimestamp between to_timestamp('2012-11-22 16:00:16.005',
'YYYY-MM-DD HH24:MI:SS.MS') and to_timestamp('2013-01-25 18:53:52.467',
'YYYY-MM-DD HH24:MI:SS.MS') ORDER BY executionTimeStamp asc;
Sort (cost=293125.41..293135.03 rows=3848 width=252) (actual
time=28628.922..28647.952 rows=62403 loops=1)
Sort Key: executiontimestamp
Sort Method: external merge Disk: 17480kB
-> Bitmap Heap Scan on ruddersysevents (cost=74359.66..292896.27
rows=3848 width=252) (actual time=1243.150..28338.927 rows=62403 loops=1)
Recheck Cond: ((nodeid =
'31264061-5ecb-4891-9aa4-83824178f43d'::text) AND (ruleid =
'61713ff1-aa6f-4c86-b3cb-7012bee707dd'::text))
Filter: ((serial = 10) AND (executiontimestamp >=
to_timestamp('2012-11-22 16:00:16.005'::text, 'YYYY-MM-DD
HH24:MI:SS.MS'::text)) AND (executiontimestamp <=
to_timestamp('2013-01-25 18:53:52.467'::text, 'YYYY-MM-DD
HH24:MI:SS.MS'::text)))
-> BitmapAnd (cost=74359.66..74359.66 rows=90079 width=0)
(actual time=1228.610..1228.610 rows=0 loops=1)
-> Bitmap Index Scan on nodeid_idx
(cost=0.00..25795.17 rows=716237 width=0) (actual time=421.365..421.365
rows=690503 loops=1)
Index Cond: (nodeid =
'31264061-5ecb-4891-9aa4-83824178f43d'::text)
-> Bitmap Index Scan on configurationruleid_idx
(cost=0.00..48562.32 rows=1386538 width=0) (actual time=794.490..794.490
rows=1381391 loops=1)
Index Cond: (ruleid =
'61713ff1-aa6f-4c86-b3cb-7012bee707dd'::text)
Total runtime: 28657.352 ms
I'm surprised that the executiontimestamp index is not used, since it
seems to be where most of the query time is spent.
For all my tests, I removed all the incoming logs, so that this table
has only selects and no writes
I'm using Postgres 8.4, on a quite smallish VM, with some process
runnings, with the following non default configuration
shared_buffers = 112MB
work_mem = 8MB
maintenance_work_mem = 48MB
max_stack_depth = 3MB
wal_buffers = 1MB
effective_cache_size = 128MB
checkpoint_segments = 6
Increasing the shared_buffers to 384, 1GB or 1500MB didn't improve the
performances (less than 10%). I would have expected it to improve, since
the indexes would all fit in RAM
Every explain analyze made after modification of configuration and
indexes where done after a complete batch of crunch of logs by our apps,
to be sure the stats were corrects
I tested further with the indexes, and reached these results :
1/ dropping the unique index "configurationruleid_idx" btree (ruleid),
"executiontimestamp_idx" btree (executiontimestamp), "keyvalue_idx"
btree (keyvalue), "nodeid_idx" btree (nodeid) to replace them by a
unique index did lower the perfs :
create index composite_idx on ruddersysevents (executiontimestamp,
ruleid, serial, nodeid);
Index Scan using composite_idx on ruddersysevents (cost=0.01..497350.22
rows=3729 width=252) (actual time=7.989..83717.901 rows=62403 loops=1)
Index Cond: ((executiontimestamp >= to_timestamp('2012-11-22
16:00:16.005'::text, 'YYYY-MM-DD HH24:MI:SS.MS'::text)) AND
(executiontimestamp <= to_timestamp('2013-01-25 18:53:52.467'::text,
'YYYY-MM-DD HH24:MI:SS.MS'::text)) AND (ruleid =
'61713ff1-aa6f-4c86-b3cb-7012bee707dd'::text) AND (serial = 10) AND
(nodeid = '31264061-5ecb-4891-9aa4-83824178f43d'::text))
2/ Removing nodeid from the index did lower again the perf
create index composite2_idx on ruddersysevents (executiontimestamp,
ruleid, serial);
Index Scan using composite2_idx on ruddersysevents
(cost=0.01..449948.98 rows=3729 width=252) (actual
time=23.507..84888.349 rows=62403 loops=1)
Index Cond: ((executiontimestamp >= to_timestamp('2012-11-22
16:00:16.005'::text, 'YYYY-MM-DD HH24:MI:SS.MS'::text)) AND
(executiontimestamp <= to_timestamp('2013-01-25 18:53:52.467'::text,
'YYYY-MM-DD HH24:MI:SS.MS'::text)) AND (ruleid =
'61713ff1-aa6f-4c86-b3cb-7012bee707dd'::text) AND (serial = 10))
Filter: (nodeid = '31264061-5ecb-4891-9aa4-83824178f43d'::text)
3/ Removing executiontimestamp from the composite index makes the query
performs better at the begining of its uses (around 17 secondes), but
over time it degrades (I'm logging query longer than 20 secondes, and
there are very rare in the first half of the batch, and getting more and
more common at the end) to what is below
create index composite3_idx on ruddersysevents (ruleid, serial, nodeid);
Sort (cost=24683.44..24693.07 rows=3849 width=252) (actual
time=60454.558..60474.013 rows=62403 loops=1)
Sort Key: executiontimestamp
Sort Method: external merge Disk: 17480kB
-> Bitmap Heap Scan on ruddersysevents (cost=450.12..24454.23
rows=3849 width=252) (actual time=146.065..60249.143 rows=62403 loops=1)
Recheck Cond: ((ruleid =
'61713ff1-aa6f-4c86-b3cb-7012bee707dd'::text) AND (serial = 10) AND
(nodeid = '31264061-5ecb-4891-9aa4-83824178f43d'::text))
Filter: ((executiontimestamp >= to_timestamp('2012-11-22
16:00:16.005'::text, 'YYYY-MM-DD HH24:MI:SS.MS'::text)) AND
(executiontimestamp <= to_timestamp('2013-01-25 18:53:52.467'::text,
'YYYY-MM-DD HH24:MI:SS.MS'::text)))
-> Bitmap Index Scan on composite3_idx (cost=0.00..449.15
rows=6635 width=0) (actual time=129.102..129.102 rows=62403 loops=1)
Index Cond: ((ruleid =
'61713ff1-aa6f-4c86-b3cb-7012bee707dd'::text) AND (serial = 10) AND
(nodeid = '31264061-5ecb-4891-9aa4-83824178f43d'::text))
Total runtime: 60484.022 ms
And with all these tests, the difference of the whole database
processing with each index time is within 10% error margin (2h10 to
2h25), even if most of the time is spent on the SQL query.
So my question is :
"Why *not* indexing the column which is not used makes the query slower
over time, while not slowing the application?"
If you have some clues, I'm really interested.
Best regards
Nicolas
--
Sent via pgsql-performance mailing list (pgsql-performance@xxxxxxxxxxxxxx)
To make changes to your subscription:
http://www.postgresql.org/mailpref/pgsql-performance
