The Clustering Factor
The clustering factor is a number which represent the degree to which data is randomly distributed in a table.
In simple terms it is the number of “block switches” while reading a table using an index.
Figure: Bad clustering factor
The above diagram explains that how scatter the rows of the table are. The first index entry (from left of index) points to the first data block and second index entry points to second data block. So while making index range scan or full index scan, optimizer have to switch between blocks and have to revisit the same block more than once because rows are scatter. So the number of times optimizer will make these switches is actually termed as “Clustering factor”.
Figure: Good clustering factor
The above image represents "Good CF”. In an event of index range scan, optimizer will not have to jump to next data block as most of the index entries points to same data block. This helps significantly in reducing the cost of your SELECT statements.
Clustering factor is stored in data dictionary and can be viewed from dba_indexes (or user_indexes)
SQL> create table sac as select * from all_objects;
SQL> create index obj_id_indx on sac(object_id);
SQL> select clustering_factor from user_indexes where index_name='OBJ_ID_INDX';
SQL> select count(*) from sac;
SQL> select blocks from user_segments where segment_name='OBJ_ID_INDX';
The above example shows that index has to jump 545 times to give you the full data had you performed full table scan using the index.
- A good CF is equal (or near) to the values of number of blocks of table.
- A bad CF is equal (or near) to the number of rows of table.
- Rebuilding of index can improve the CF.
Then how to improve the CF?
- To improve the CF, it’s the table that must be rebuilt (and reordered).
- If table has multiple indexes, careful consideration needs to be given by which index to order table.
Important point: The above is my interpretation of the subject after reading the book on Optimizer of Jonathan Lewis.