Oracle RAC CR Block Requests Test
Data blocks requested from the Global Cache are of two types: current and consistent-read (CR) blocks. When you update data in the database, Oracle Database must locate the most recent version of the data block that contains the data, which is called the current block. If you perform a query, only data committed before the query began is visible to the query. Data blocks that were changed after the start of the query are reconstructed from data in the undo segments, and the reconstructed data is made available to the query in the form of a consistent-read block.
Whenever a session requests for a CR block, Oracle first checks whether it has that block in its local cache. If the block does not exist in the local cache but is available in the remote cache, then it is transferred from the remote to local cache via the interconnect. The time that elapses between when a CR block is requested and when the session receives it should be tracked continuously, so that global cache block access latencies (if any) are detected proactively and resolved promptly. Use the Oracle CR Block Requests test to perform this tracking.
This test, at configured intervals, monitors requests for CR blocks and reports how long it took for the requests to be serviced by the buffer caches. This sheds light on request processing delays (if any).
Target of the test : Oracle RAC
Agent deploying the test : An internal agent
Outputs of the test : One set of results for every Oracle cluster.
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Measurement | Description | Measurement Unit | Interpretation |
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Average cr block request time: |
Indicates the time taken to service requests for cr blocks.
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Centisecs |
Ideally the value of this measure should be low. A high value for this measure is indicative of high latencies while accessing global cache blocks. This can be caused by any of the following:
When global cache requests cause a performance problem, optimizing SQL plans and the schema to improve the rate at which data blocks are located in the local buffer cache, and minimizing I/O is a successful strategy for performance tuning. |