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Cache Event Processing with an Event Polling Table


The use of a Siebel Analytics Server event polling table (event table) is a way to notify the Analytics server that one or more physical tables have been updated. Each row that is added to an event table describes a single update event, such as an update occurring to the Product table in the 11308Production database. The Siebel Analytics Server cache system reads rows from, or polls, the event table, extracts the physical table information from the rows, and purges stale cache entries that reference those physical tables.

The event table is a physical table that resides on a database accessible to the Siebel Analytics Server. Regardless of where it resides—in its own database, or in a database with other tables—it requires a fixed schema, described in Table 28. It is normally exposed only in the Physical layer of the Administration Tool, where it is identified in the Physical Table dialog box as being a Siebel Analytics Server event table.

The use of event tables is one of the most accurate ways of invalidating stale cache entries, and it is probably the most reliable method. It does, however, require the event table to be populated each time a database table is updated (see Populating the Siebel Analytics Server Event Polling Table). Also, because there is a polling interval in which the cache is not completely up to date, there is always the potential for stale data in the cache.

A typical method of updating the event table is to include SQL INSERT statements in the extraction and load scripts or programs that populate the databases. The INSERT statements add one row to the event table each time a physical table is modified. After this process is in place and the event table is configured in the Siebel Analytics Server repository, cache invalidation occurs automatically. As long as the scripts that update the event table are accurately recording changes to the tables, stale cache entries are purged automatically at the specified polling intervals.


 Siebel Analytics Server Administration Guide
 Published: 11 March 2004