Thanks, yes it is Linux. I will look at those limits settings.
And yes, I've built indexes and analyze (nothing to vacuum yet since
it's a fresh import).
Stephen
On 06/04/2010 12:16 PM, Alan Brown wrote:
> On Fri, 4 Jun 2010, Stephen Thompson wrote:
>
>>
>>
>> Correction:
>> I didn't notice the 8k per unit settings at first with postgres 8.1.
>> Should read:
>> effective_cache_size = 786432 # 6Gb
>
> Assuming this is linux, you need to tweak /etc/sysctl/limits.conf a
> little:
>
> postgres soft memlock unlimited
> postgres hard memlock unlimited
> @postgres hard memlock unlimited
> @postgres soft memlock unlimited
> bacula soft memlock unlimited
> bacula hard memlock unlimited
> @bacula soft memlock unlimited
> @bacula hard memlock unlimited
>
> postgres soft rss unlimited
> postgres hard rss unlimited
>
>
> Don't forget to build the indexes and run analyse/vacuum commands.
>
> So far I'm finding Postgres is far more forgiving than MySQL and has far
> fewer parts to tune...
>
>
>
>>
>>
>> On 06/04/2010 10:58 AM, Stephen Thompson wrote:
>>>
>>>
>>> Hello everyone,
>>>
>>> We recently attempted a mysql to postgresql migration for our bacula
>>> 5.0.2 server. The data migration itself was successful, however we are
>>> disappointly either getting the same or significantly worse performance
>>> out of the postgres db.
>>>
>>> I was hoping that someone might have some insight into this.
>>>
>>> Here is some background:
>>>
>>> software:
>>> centos 5.5 (64bit)
>>> bacula 5.0.2 (64bit)
>>> postgresql 8.1.21 (64bit)
>>> (previously... mysql-5.0.77 (64bit) MyISAM)
>>>
>>> database:
>>> select count(*) from File --> 1,439,626,558
>>> du -sk /var/lib/pgsql/data --> 346,236,136 /var/lib/pgsql/data
>>>
>>> hardware:
>>> 1Tb EXT3 external fibre-RAID storage
>>> 8Gb RAM
>>> 2Gb SWAP
>>> 2 dual-core [AMD Opteron(tm) Processor 2220] CPUs
>>>
>>>
>>> Some of the postgres tuning that I've attempted thus far (comments are
>>> either default or alternatively settings I've tried without effect):
>>>
>>> #shared_buffers = 1000 # min 16 or max_connections*2, 8KB each
>>> shared_buffers = 262144 # 2Gb
>>> #work_mem = 1024 # min 64, size in KB
>>> work_mem = 524288 # 512Mb
>>> #maintenance_work_mem = 16384 # min 1024, size in KB
>>> maintenance_work_mem = 2097152 # 2Gb
>>> #checkpoint_segments = 3 # in logfile segments, min 1, 16MB each
>>> checkpoint_segments = 16
>>> #checkpoint_warning = 30 # in seconds, 0 is off
>>> checkpoint_warning = 16
>>> #effective_cache_size = 1000 # typically 8KB each
>>> #effective_cache_size = 262144 # 256Mb
>>> effective_cache_size = 6291456 # 6Gb
>>> #random_page_cost = 4 # units are one sequential page fetch cost
>>> random_page_cost = 2
>>>
>>> Now, as to what I'm 'seeing'. Building restore trees are on par with my
>>> previous mysql db, but what I'm seeing as significantly worse are:
>>>
>>> mysql postgresql
>>> Within Bat:
>>> 1) Version Browser (large sample job) 3min 9min
>>> 2) Restore Tree (average sample job) 40sec 25sec
>>> 3) Restore Tree (large sample job) 10min 8.5min
>>> 2) Jobs Run (1000 Records) 10sec 2min
>>>
>>> Within psql/mysql:
>>> 1) select count(*) from File; 1sec 30min
>>>
>>> Catalog dump:
>>> 1) mysqldump/pgdump 2hrs 3hrs
>>>
>>>
>>> I get a win on building Restore trees, but everywhere else, it's
>>> painfully slow. It makes the bat utility virtually unusable as an
>>> interface. Why the win (albeit moderate) in some cases but terrible
>>> responses in others?
>>>
>>> I admit that I am not familiar with postgres at all, but I tried to walk
>>> through some of the postgres tuning documents, including the notes in
>>> the bacula manual to arrive at the above settings. Also note that I've
>>> tried several variants on the configuration above (including the
>>> postgres defaults), don't have a detailed play by play of the results,
>>> but the time results above seemed typical regardless of what settings I
>>> tweaked.
>>>
>>> Any help would be greatly appreciated!
>>> Stephen
>>
>>
>>
>
--
Stephen Thompson Berkeley Seismological Laboratory
stephen AT seismo.berkeley DOT edu 215 McCone Hall # 4760
404.538.7077 (phone) University of California, Berkeley
510.643.5811 (fax) Berkeley, CA 94720-4760
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