Analyzing Cache Fusion Transfer Impact Using GCS Statistics

This section describes how to monitor GCS performance by identifying objects read and modified frequently and the service times imposed by the remote access. Waiting for blocks to arrive may constitute a significant portion of the response time, in the same way that reading from disk could increase the block access delays, only that cache fusion transfers are usually faster than disk access latencies.

The following wait events indicate that the remotely cached blocks were shipped to the local instance without having been busy, pinned or requiring a log flush:

  • gc current block 2-way

  • gc current block 3-way

  • gc cr block 2-way

  • gc cr block 3-way

The object statistics for gc current blocks received and gc cr blocks received enable quick identification of the indexes and tables which are shared by the active instances. As mentioned earlier, creating an ADDM analysis will usually point you to the SQL statements and database objects that could be impacted by inter-instance contention.

Any increases in the average wait times for the events mentioned in the preceding list could be caused by the following occurrences:

  • High load: CPU shortages, long run queues, scheduling delays

  • Misconfiguration: using public instead of private interconnect for message and block traffic

If the average wait times are acceptable and no interconnect or load issues can be diagnosed, then the accumulated time waited can usually be attributed to a few SQL statements which need to be tuned to minimize the number of blocks accessed.

The column CLUSTER_WAIT_TIME in V$SQLAREA represents the wait time incurred by individual SQL statements for global cache events and will identify the SQL which may need to be tuned.