A query takes twice as long for an identical database on two separate systems.

Hi, I'm looking for help with a performance issue on a particular database.

I'm running the query
' for $o in the collection ("rx.dbxml") / RX [dbxml:metadata("janusId") = "12345"] descending return $o/@dos < id item = '{replace (dbxml:metadata("dbxml:name",_$o)' & #34; (», «_»)} "> {$o} < / item > '"
on two different systems through a ServerProxy xmlrpclib python object. This is the my test request, but the other query performance presents the same problem.

Data on both systems are identical, and the time required to execute this query is the same for both systems throughout
each database, except one. For this particular database, the time required to run the query on system B is double
the system has.

This is only the case for a particular database that makes me think it's a matter of data?
However, the data are identical on both systems.

Is anyone aware of all data related issues that could trigger such a success of performance-based
the configurations below? What should be my next step to diagnose this problem?

System A
---
-1 x Quad core Intel Xeon CPU E5450 @ 3 .00GHz
-32 GB OF RAM

-Red Hat Enterprise Linux Server 5.1 (Tikanga)
-Berkeley dbxml 2.4.13 patched for 2.4.16
-bsddb3 4.5.0
-Python 2.4.4
twisted-8.2.0
-0.12.0 sOAPpy

-Size used Avail use % mounted file system
/ dev/sda5 39 33 G G 4.3 G 89%.
...
---

System B
---
-2 x Intel Xeon CPU @ 2.80 GHz Dual core
-12 GB OF RAM

-Red Hat Enterprise Linux Server 5.3 (Tikanga)
-Berkeley dbxml 2.4.16
-bsddb3 4.7.5
-Python 2.4.4
twisted-8.2.0
-0.12.0 sOAPpy

-Size used Avail use % mounted file system
/ dev/map/VolGroup00-LogVol00 384 G 88 277 G 25%.
...
---

Thanks for any help.

Try looking at the exit of db_stat for each system to the query itself.
1 clear stats:
db_stat z m
2. run the query
3. look at his stats:
db_stat m

Note the suspicious differences. You can / must also monitor the disk and the e/s during queries. If the plans are really the same and the data are the same that points to differences in system that would essentially be IO. At least this is the first place to look.

Kind regards
George

Tags: Database

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