Reducing the Workload
Important as it is to efficiently access and process query data, it is even better if you can avoid doing the work in the first place. Most of the major database vendors have invested significant engineering effort to find ways of reducing the amount of data that needs to be processed and the amount of processing that is required. The main techniques for reducing the workload are discussed in this section.
Data Partitioning
One way of significantly reducing the volume of data to be processed is to partition or fragment the data so that the bulk of the data doesn’t need to be accessed at all. For example, data often retrieved by date could be partitioned into different disk areas according to month. A query predicate specifying ...
Get Configuring and Tuning Databases on the Solaris™ Platform now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
