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15 3,'26-30', 16 4,'31-40', 17 5,'41 and over'), 18 rpad( '*', 20, '*') 19 from big_table.big_table 20 where rownum <= 100000; Table created. ops$tkyte%ORA11GR2> create bitmap index gender_idx on t(gender); Index created. ops$tkyte%ORA11GR2> create bitmap index location_idx on t(location); Index created. ops$tkyte%ORA11GR2> create bitmap index age_group_idx on t(age_group); Index created. ops$tkyte%ORA11GR2> exec dbms_stats.gather_table_stats( user, 'T'); PL/SQL procedure successfully completed. Now we ll take a look at the plans for our various ad hoc queries from earlier: ops$tkyte%ORA11GR2> Select count(*) 2 from T 3 where gender = 'M' 4 and location in ( 1, 10, 30 ) 5 and age_group = '41 and over'; Execution Plan ---------------------------------------------------------Plan hash value: 1811480857 -----------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| -----------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 13 | 5 (0)| | 1 | SORT AGGREGATE | | 1 | 13 | | | 2 | BITMAP CONVERSION COUNT | | 1 | 13 | 5 (0)| | 3 | BITMAP AND | | | | | |* 4 | BITMAP INDEX SINGLE VALUE | GENDER_IDX | | | | | 5 | BITMAP OR | | | | | |* 6 | BITMAP INDEX SINGLE VALUE| LOCATION_IDX | | | | |* 7 | BITMAP INDEX SINGLE VALUE| LOCATION_IDX | | | | |* 8 | BITMAP INDEX SINGLE VALUE| LOCATION_IDX | | | | |* 9 | BITMAP INDEX SINGLE VALUE | AGE_GROUP_IDX | | | | -----------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------4 6 7 8 9 access("GENDER"='M') access("LOCATION"=1) access("LOCATION"=10) access("LOCATION"=30) access("AGE_GROUP"='41 and over')
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CHAPTER 11 INDEXES
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This example shows the power of the bitmap indexes. Oracle is able to see the location in (1,10,30) and knows to read the index on location for these three values and logically OR together the bits in the bitmap. It then takes that resulting bitmap and logically ANDs that with the bitmaps for AGE_GROUP='41 AND OVER' and GENDER='M'. Then a simple count of 1s and the answer is ready. ops$tkyte%ORA11GR2> select * 2 from t 3 where ( ( gender = 'M' and location = 20 ) 4 or ( gender = 'F' and location = 22 )) 5 and age_group = '18 and under'; Execution Plan ---------------------------------------------------------Plan hash value: 906765108 --------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes |Cost(%C)| --------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 510 | 16830 |78 (0)| | 1 | TABLE ACCESS BY INDEX ROWID | T | 510 | 16830 |78 (0)| | 2 | BITMAP CONVERSION TO ROWIDS | | | | | | 3 | BITMAP AND | | | | | |* 4 | BITMAP INDEX SINGLE VALUE | AGE_GROUP_IDX | | | | | 5 | BITMAP OR | | | | | | 6 | BITMAP AND | | | | | |* 7 | BITMAP INDEX SINGLE VALUE| LOCATION_IDX | | | | |* 8 | BITMAP INDEX SINGLE VALUE| GENDER_IDX | | | | | 9 | BITMAP AND | | | | | |* 10 | BITMAP INDEX SINGLE VALUE| GENDER_IDX | | | | |* 11 | BITMAP INDEX SINGLE VALUE| LOCATION_IDX | | | | --------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------4 7 8 10 11 access("AGE_GROUP"='18 and under') access("LOCATION"=22) access("GENDER"='F') access("GENDER"='M') access("LOCATION"=20)
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This shows similar logic: the plan shows the OR d conditions are each evaluated by AND-ing together the appropriate bitmaps and then OR-ing together those results. Throw in another AND to satisfy the AGE_GROUP='18 AND UNDER' and we have it all. Since we asked for the actual rows this time, Oracle will convert each bitmap 1 and 0 into rowids to retrieve the source data. In a data warehouse or a large reporting system supporting many ad hoc SQL queries, this ability to use as many indexes as make sense simultaneously comes in very handy indeed. Using conventional B*Tree indexes here would not be nearly as usual or usable, and as the number of columns that are to be searched by the ad hoc queries increases, the number of combinations of B*Tree indexes you would need increases as well. However, there are times when bitmaps are not appropriate. They work well in a read-intensive environment, but they are extremely ill suited for a write-intensive environment. The reason is that a single bitmap index key entry points to many rows. If a session modifies the indexed data, then all of the
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