- Management at the individual partition level for data loads, indexcreation and rebuilding, and backup/recovery. This can result in less down time because only individual partitions being actively managed are unavailable.
- Increased query performance by selecting only from the relevant partitions. This weeding out process eliminates the partitions that do not contain the data needed by the query through a technique called
- When a table reaches a “large” size. Large is defined relative to your environment. Tables greater than 2GB should always be considered for partitioning.
- When the archiving of data is on a schedule and is repetitive. For instance, data warehouses usually hold data for a specific amount of time (rolling window). Old data is then rolled off to be archived.
Saturday, July 21, 2012
When to Partition your data
There are two main reasons to use partitioning in a large database environment. These reasons are related to management and performance improvement. Partitioning offers: