Help in avoiding a query 'Warm-Up' period/shared buffer cache

From: Mark Liberman <mliberman(at)mixedsignals(dot)com>
To: pgsql-performance(at)postgresql(dot)org
Subject: Help in avoiding a query 'Warm-Up' period/shared buffer cache
Date: 2006-01-04 22:49:43
Message-ID: 200601041449.43557.mliberman@mixedsignals.com
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Hello,

We have a web-application running against a postgres 8.1 database, and
basically, every time I run a report after no other reports have been run for
several hours, the report will take significantly longer (e.g. 30 seconds),
then if I re-run the report again, or run the report when the web-application
has been used recently (< 1 second).

Keep in mind that our web-app might issue 30 or more individual queries to
return a given report and that this behavior is not just isolated to a single
report-type - it basically happens for any of the reports after the web-app
has been inactive. Also, I can trace it back to the timing of the underlying
queries, which show this same behavior (e.g. it's not because of overhead in
our web-app).

So, it appears to be some sort of caching issue. I'm not 100% clear on how
the shared buffer cache works, and what we might do to make sure that we
don't have these periods where queries take a long time. Since our users'
typical usage scenario is to not use the web-app for a long time and then
come back and use it, if reports which generally take a second are taking 30
seconds, we have a real problem.

I have isolated a single example of one such query which is very slow when no
other queries have been run, and then speeds up significantly on the second
run.

First run, after a night of inactivity:

explain analyze SELECT average_size, end_time FROM 1min_events WHERE file_id =
'137271' AND end_time > now() - interval '2 minutes' ORDER BY end_time DESC
LIMIT 1;

Limit (cost=47.06..47.06 rows=1 width=24) (actual time=313.585..313.585
rows=1 loops=1)
-> Sort (cost=47.06..47.06 rows=1 width=24) (actual time=313.584..313.584
rows=1 loops=1)
Sort Key: end_time
-> Bitmap Heap Scan on 1min_events (cost=44.03..47.05 rows=1
width=24) (actual time=313.562..313.568 rows=2 loops=1)
Recheck Cond: ((end_time > (now() - '00:02:00'::interval)) AND
(file_id = 137271))
-> BitmapAnd (cost=44.03..44.03 rows=1 width=0) (actual
time=313.551..313.551 rows=0 loops=1)
-> Bitmap Index Scan on 1min_events_end_idx
(cost=0.00..5.93 rows=551 width=0) (actual time=0.076..0.076 rows=46 loops=1)
Index Cond: (end_time > (now() -
'00:02:00'::interval))
-> Bitmap Index Scan on 1min_events_file_id_begin_idx
(cost=0.00..37.85 rows=3670 width=0) (actual time=313.468..313.468 rows=11082
loops=1)
Index Cond: (file_id = 137271)
Total runtime: 313.643 ms
(11 rows)

Second run, after that:

explain analyze SELECT average_size, end_time FROM 1min_events WHERE file_id
= '137271' AND end_time > now() - interval '2 minutes' ORDER BY end_time DESC
LIMIT 1;

Limit (cost=47.06..47.06 rows=1 width=24) (actual time=2.209..2.209 rows=1
loops=1)
-> Sort (cost=47.06..47.06 rows=1 width=24) (actual time=2.208..2.208
rows=1 loops=1)
Sort Key: end_time
-> Bitmap Heap Scan on 1min_events (cost=44.03..47.05 rows=1
width=24) (actual time=2.192..2.194 rows=2 loops=1)
Recheck Cond: ((end_time > (now() - '00:02:00'::interval)) AND
(file_id = 137271))
-> BitmapAnd (cost=44.03..44.03 rows=1 width=0) (actual
time=2.186..2.186 rows=0 loops=1)
-> Bitmap Index Scan on 1min_events_end_idx
(cost=0.00..5.93 rows=551 width=0) (actual time=0.076..0.076 rows=46 loops=1)
Index Cond: (end_time > (now() -
'00:02:00'::interval))
-> Bitmap Index Scan on 1min_events_file_id_begin_idx
(cost=0.00..37.85 rows=3670 width=0) (actual time=2.106..2.106 rows=11082
loops=1)
Index Cond: (file_id = 137271)
Total runtime: 2.276 ms
(11 rows)

One of the things that is perplexing about the initial slowness of this query
is that it's accessing the most recent rows in a given table (e.g. those in
the last 2 minutes). So, I would expect the OS cache to be updated with
these new rows.

Some general information about the server / db:

1) The database is 25G, and has about 60 tables - some very small, but several
> 5 MM rows.

2) The table I am querying against above (1min_events) has 5.5 MM rows, but is
indexed on end_time, as well as a compound index on file_id, begin_time

3) The following are running on the server that holds the db:

a) A program which is reading files and making several (5-10) database calls
per minute (these calls tend to take < 100 ms each). These calls are
inserting 10's of rows into several of the tables.

b) An apache web-server

c) The 8.1 postgres DB

d) we are running periodic CRON jobs (generally at 11pm, 1 am and 3am) that
truncate some of the older data

e) we have autovacuum on with a 60 second naptime and and low scale factors
0.2, so analyzes and vacuums happen throughout the day - vacuums are
generally triggered by the truncate CRON jobs too.

4) Some of our config settings:

shared_buffers = 8192
work_mem = 8192

Total RAM on server is 1 Gig

Basically any advice as to what to look at to avoid this situation would be
greatly appreciated. Is this simply a matter of tuning the shared_buffers
parameter? If not, is scheduling a set of queries to force the proper
loading of the cache a logical solution?

Thanks in advance,

Mark

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