Analyzing Performance Using GCS and GES Statistics

This section describes how to monitor GCS performance by identifying data blocks and objects which are frequently used (hot) by all instances. High concurrency on certain blocks may be identified by GCS wait events and times.

The gc current block busy wait event indicates that the access to cached data blocks was delayed because they were busy either in the remote or the local cache. This could be caused by any of the following:

  • The blocks were pinned

  • The blocks were held up by sessions

  • The blocks were delayed by a log write on a remote instance

  • A session on the same instance was already accessing a block which was in transition between instances and the current session needed to wait behind it (for example, gc current block busy)

Use the V$SESSION_WAIT view to identify objects and data blocks with contention. The GCS wait events contain the file and block number for a block request in p1 and p2, respectively.

An additional segment statistic, gc buffer busy, has been added to quickly determine the busy objects without having to query the V$SESSION_WAIT view mentioned earlier.

The AWR infrastructure provides a view of active session history which can also be used to trace recent wait events and their arguments. It is therefore useful for hot block analysis. Most of the reporting facilities used by AWR and Statspack contain the object statistics and cluster wait class category, so that sampling of the views mentioned earlier is largely unnecessary.


Oracle recommends using ADDM and AWR. However, Statspack is available for backward compatibility. Statspack provides reporting only. You must run Statspack at level 7 to collect statistics related to block contention and segment block waits.

It is advisable to run ADDM on the snapshot data collected by the AWR infrastructure to obtain an overall evaluation of the impact of the global cache. The advisory will also identify the busy objects and SQL highest cluster wait time.