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From: Pallav Kalva <pkalva@livedatagroup.com>
To: pgsql-performance@postgresql.org
Subject: Vacuum template databases, Urgent: Production problem
Date: Tue, 14 Mar 2006 11:44:12 -0500
Message-ID: <4416F2DC.4010400@livedatagroup.com> (raw)

Hi, 

   Do we have to vacuum template0 database regularly ? We got this warning this morning while vacuuming databases. As a part of my daily vacuum job I do vacuum of quartz, helix_fdc and affiliate databases which are the 
one's which are heavily updated and used. But today I realized that usps, template1 and template0 is also being used in a transaction somehow based on this (SELECT datname, age(datfrozenxid) FROM pg_database;) query.
Actually we dont do any updates on usps , template1 and templat0 databases but some how still the age(datfrozenxid keeps incrementing. 

   My question now is do I have to vacuum daily template1 and template0 databse, is there any harm on vacuuming these databases daily ?, since these are postgres system tables I am kind of worried.  
   I was told that template0 is freezed but not sure why the age(datfrozenxid keeps incrementing.   
   I am going to vacuum usps from now anyway. We are using Postgres version 8.0.2 


   If some one can please help me on this it would be really great, this is a production database and we cant afford to loose anything. 

Thanks!
Pallav. 


Message from the log
---------------------
WARNING:  some databases have not been vacuumed in 1618393379 transactions
HINT:  Better vacuum them within 529090268 transactions, or you may have a wraparound failure.



SELECT datname, age(datfrozenxid) FROM pg_database;
  datname  |    age
-----------+------------
 quartz    | 1076729648
 helix_fdc | 1078452246
 usps      | 1621381218
 affiliate | 1078561327
 template1 | 1621381218
 template0 | 1621381218
(6 rows)
 
 
SELECT datname, age(datfrozenxid) FROM pg_database;
  datname  |    age
-----------+------------
 quartz    | 1076770467
 helix_fdc | 1078493065
 usps      | 1621422037
 affiliate | 1078602146
 template1 | 1621422037
 template0 | 1621422037
(6 rows)
 
 
I ran this just 2 minutes apart and you can see the age value changes for 
template0 and template1




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