Re: PostgreSQL as a local in-memory cache

From: Mark Kirkwood
Subject: Re: PostgreSQL as a local in-memory cache
Date: ,
Msg-id: 4C1881C7.1050501@catalyst.net.nz
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In response to: Re: PostgreSQL as a local in-memory cache  ("")
List: pgsql-performance

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Re: PostgreSQL as a local in-memory cache  (Chris Browne, )
 Re: PostgreSQL as a local in-memory cache  (Steve Wampler, )
  Re: PostgreSQL as a local in-memory cache  (Craig James, )
 Re: PostgreSQL as a local in-memory cache  ("", )
 Re: PostgreSQL as a local in-memory cache  (Chris Browne, )
  Re: PostgreSQL as a local in-memory cache  (Jaime Casanova, )
  Re: PostgreSQL as a local in-memory cache  (Josh Berkus, )
 Re: PostgreSQL as a local in-memory cache  ("", )
  Re: PostgreSQL as a local in-memory cache  (Mark Kirkwood, )
  Re: PostgreSQL as a local in-memory cache  ("Pierre C", )
   Re: PostgreSQL as a local in-memory cache  (Jonathan Gardner, )
  Re: PostgreSQL as a local in-memory cache  ("Pierre C", )
  Re: PostgreSQL as a local in-memory cache  (Greg Smith, )
   Re: PostgreSQL as a local in-memory cache  ("Pierre C", )
    Re: PostgreSQL as a local in-memory cache  (Jonathan Gardner, )
     Re: PostgreSQL as a local in-memory cache  ("Pierre C", )
   Re: PostgreSQL as a local in-memory cache  (Jonathan Gardner, )
  Re: PostgreSQL as a local in-memory cache  (Alvaro Herrera, )
  Re: PostgreSQL as a local in-memory cache  (Josh Berkus, )
   Re: PostgreSQL as a local in-memory cache  (Jonathan Gardner, )
    Re: PostgreSQL as a local in-memory cache  (Balkrishna Sharma, )
   Re: PostgreSQL as a local in-memory cache  (Craig James, )

On 16/06/10 18:30,  wrote:
> On Jun 15, 4:18 pm, j...@agliodbs.com (Josh Berkus) wrote:
>
>> On 6/15/10 10:37 AM, Chris Browne wrote:
>>
>> I'd like to see some figures about WAL on RAMfs vs. simply turning off
>> fsync and full_page_writes.  Per Gavin's tests, PostgreSQL is already
>> close to TokyoCabinet/MongoDB performance just with those turned off; I
>> wonder if actually having the WAL on a memory partition would make any
>> real difference in throughput.
>>
>> I've seen a lot of call for this recently, especially since PostgreSQL
>> seems to be increasingly in use as a reporting server for Hadoop.  Might
>> be worth experimenting with just making wal writing a no-op.  We'd also
>> want to disable checkpointing, of course.
>>
>>
> My back-of-the-envelope experiment: Inserting single integers into a
> table without indexes using a prepared query via psycopg2.
>
> Python Script:
> import psycopg2
> from time import time
> conn = psycopg2.connect(database='jgardner')
> cursor = conn.cursor()
> cursor.execute("CREATE TABLE test (data int not null)")
> conn.commit()
> cursor.execute("PREPARE ins AS INSERT INTO test VALUES ($1)")
> conn.commit()
> start = time()
> tx = 0
> while time() - start<  1.0:
>      cursor.execute("EXECUTE ins(%s)", (tx,));
>      conn.commit()
>      tx += 1
> print tx
> cursor.execute("DROP TABLE test");
> conn.commit();
>
> Local disk, WAL on same FS:
> * Default config =>  90
> * full_page_writes=off =>  90
> * synchronous_commit=off =>  4,500
> * fsync=off =>  5,100
> * fsync=off and synchronous_commit=off =>  5,500
> * fsync=off and full_page_writes=off =>  5,150
> * fsync=off, synchronous_commit=off and full_page_writes=off =>  5,500
>
> tmpfs, WAL on same tmpfs:
> * Default config: 5,200
> * full_page_writes=off =>  5,200
> * fsync=off =>  5,250
> * synchronous_commit=off =>  5,200
> * fsync=off and synchronous_commit=off =>  5,450
> * fsync=off and full_page_writes=off =>  5,250
> * fsync=off, synchronous_commit=off and full_page_writes=off =>  5,500
>
> NOTE: If I do one giant commit instead of lots of littler ones, I get
> much better speeds for the slower cases, but I never exceed 5,500
> which appears to be some kind of wall I can't break through.
>
> If there's anything else I should tinker with, I'm all ears.
>
>

Seeing some profiler output (e.g oprofile) for the fastest case (and
maybe 'em all later) might be informative about what limit is being hit
here.

regards

Mark


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Subject: Re: PostgreSQL as a local in-memory cache