Applies to:
Oracle Server - Enterprise Edition - Version: 8.0.3.0 to 11.2.0.2 - Release: 8.0.3 to 11.2
Information in this document applies to any platform.
This article outlines the meaning of the Clustering Factor Statistic
This article provides developers and DBAs more in depth information regarding the Clustering Factor Statistic
Clustering Factor is statistics collected for use by the Cost Based Optimizer (CBO) and is a measure of the 'ordered-ness' of an index in comparison to the table that it is based upon. It is used as an indicator for computing the estimated cost of the table lookup following an index access.
The Clustering Factor records the number of data blocks that will be accessed when scanning an index.
Clustering factor values can be seen in the following views:
It can be set also in:
when the indexes are partitioned.
For further details on Clustering Factor see:
Oracle® Database Concepts
11g Release 2 (11.2)
Part Number E10713-05
Chapter 3 Indexes and Index-Organized Tables
It is calculated as follows:
If the count is close to the number of blocks in the table then the index is well ordered. This is true because the counter only gets incremented when the actual data is found in a different block from the last piece of row data. What this means is that when an index block is read, the table lookups required based on that block are likely to be in the same table blocks. So, the lower the Clustering Factor the less I/O is likely to be used by the statement and so the optimizer is more likely to choose that index.
If the count is close to the number of rows in the table then the index is less well ordered. In this case adjacent index entries do not tend to point to the same block in the table, thus more block reads are likely to be required. An index with a higher clustering factor is more likely to have to revisit Data blocks than with a lower Clustering factor .
The clustering factor can be used by the optimizer to adjust the potential number of blocks that will be accessed by a particular predicate or query. This is useful for determining the number of base table blocks that will be visited when accessed via the index.
The clustering factor is effectively a count of the number of data blocks visited as the result of an index lookup. Multiplying the clustering factor by the selectivity will give the cost of the operation. It is predominately used to calculate costs for index range scans.