Hi Sudip,

Your results are very interesting. Maybe you can quickly respond to some
questions:
 - What OS?
 - What is the average size of your emails?
 - Why does James collapse at 70% assuming that MySQL is running on a
different server as you state in point 8?
 - Have you performed such a stress test with file-based repositories in
order to measure the performance gain?
 - Have you detected any memory leak on long test runs?
 - How long have you kept running your test environment? Don't you get
any MySQL performance loss without periodic 'OPTIMIZE TABLE spool'?
 - Do you plan similar stress tests against some other DB such as
PostgreSQL?

Regards,


Diego

-----Message d'origine-----
De�: Sudip Shekhawat [mailto:[EMAIL PROTECTED] 
Envoy�: jeudi 16 octobre 2003 19:22
��: [EMAIL PROTECTED]
Objet�: Stress test on James

Finally we have some real numbers!! The stress test on James concluded.

Test Scenario:
1.      We used two servers running james 2.2.08a. We start by sending
�n� 
mails/min to server1. Server1 processes these mails and sends them to 
server2. Server2 ghosts the mails.
2.      The servers were 2.4 Ghz Pentium 4 with 1 GB of memory.
3.      We used mySQL 4.0.13 and JDBC connector 3.0.9
4.      JDK 1.4.2 was used with the �server option and we also set the
JVM heap 
to be 384 MB.
5.      By using trial and error and some logic we came up with the
optimal 
number of spool threads to be 12 and the outgoing threads to be 20 for 
server1.
6.      Server2 used 100 spool threads.
7.      Maxcache was set to be 125.
8.      We used james database repository. By making james and james�s
database 
repository use the same server leads to contention of CPU time and james

doesn�t perform to its fullest. Therefore the database repository
(mySQL) 
was installed on a different server.
9.      Max connection for the database was set to 20.

Method:
1.      We started by sending 800 mails/min to server1. We were
constantly 
following up with the spool size of James.
2.      We kept increasing the mails/min till we saw a rate when james
couldn�t 
handle 100% of the mails.

Results:
1.      James was able to process (receiver/process/send) all of the 800

mails/min.
2.      As we increased the rate, James comfortably processed around
2600 
mails/min with a CPU usage of 70% for James and the CPU usage of 30% for

mySQL
3.      When we reached 2800 mails/min, the spool started increasing in
size and 
the number of mails processed per min started decreasing. The decrease
was 
exponential with the increase in the number of messages/min. When we
sent 
4000 mails/min, james processed 400 mails/min.

Conclusion:
James with our current configuration can handle 2600 mails/min which is 
pretty neat.

Thanks
Sudip

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