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RE: When should a table be partitioned?

From: Hamid Alavi <hamid.alavi_at_quovadx.com>
Date: Tue, 22 Jan 2002 11:00:51 -0800
Message-ID: <F001.003F76DF.20020122101957@fatcity.com>

Cheri,
Just wondered even when you have a table with data still you can partition it or you have to create a new table with partitioning and load the data from old to new one. Is it right or not?

-----Original Message-----
Sent: Tuesday, January 22, 2002 8:10 AM
To: Multiple recipients of list ORACLE-L

Cherie,
We used the data volume and performance criterion while deciding to partition our tables. One of the major tables had grown over 100Mil rows and had 4 indexes. All tables had 4 digit YEAR field and most queries used YEAR in them, so it was a no-brainer. A few important queries were modified to use YEAR to facilitate partition pruning. So, after partitioning all these tables by YEAR, the performance was much improved. Archival criterion was also a driver, initially. But after the clients saw the results (good performance), they had other ideas. Now we are holding on to 12 years of data instead of 10 years. Looks like we are heading towards 15 years of historical data. And we have added 2 more indexes to that major table. Data loads are once a month.

HTH,

>>> Cherie_Machler_at_gelco.com 01/18/02 08:20AM >>>

We have a number of partitioned tables in a couple of existing data warehouses.
We are working on the design for a new warehouse and need to decide which
tables should be partitioned.

For you folks that have partitioned tables, how do you decide which tables
to
be partition? Some tables with very large row counts are obvious candidates.
If you go off of row counts solely, what is the cut-off point for where you
should start
partitioning? Is there a rule-of-thumb?

I'm having difficulty with the not-as-huge, not-as-obvious candidates.

What other criteria do you use besides row-count? Perhaps archival requirements?

I guess it would depend on what you are using the partitioning to achieve.
Partition
exclusion for read performance improvement or for culling off old data,
etc.

Any shared insights for where to draw the line on partitioning candidates
would
be greatly appreciated.

Thanks,

Cherie Machler

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Author:
  INET: Cherie_Machler_at_gelco.com

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Author: Deshpande, Kirti
  INET: kirti.deshpande_at_verizon.com

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Author: Hamid Alavi
  INET: hamid.alavi_at_quovadx.com
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