For high cardinality data or data with many possible values, B-tree indexes are most effective.
B-tree indexes are most effective for high cardinality data, or data with many
possible values. A common problem with traditional B-tree indexes occurs when an indexed column has low cardinality, which means it has too few distinct values to speed query access.
For example, an index of a REGION column that has only 4 values (North, South, East, West) does not have enough distinct values to speed access for queries. It is an index column with relatively few distinct values, compared to the number of rows in the table, and is referred to as a low cardinality column.
Oracle's answer to the problem of low cardinality is the bitmapped index.
We know that the purpose of an index is to provide pointers to the rows in a table that contain a given key value. In a bitmap index, a bitmap for each key value is used instead of a list of ROWIDs.
Each bit in the bitmap corresponds to a possible ROWID. If the bit is set, the row with the matching ROWID includes the key value.
A mapping function converts the bit position to an actual ROWID, so the bitmap index functions as a regular index although it has a different internal structure. If the number of different key values is small, bitmap indexes are very space-efficient.
In contrast to B-tree index, a bitmapped index has minimal storage requirements
Improved response time
In certain situations, a bitmapped index dramatically improves the response time
This is often the case where there are indexes that correspond to several conditions in a WHERE clause. A bitmap index efficiently merges these indexes, and this often dramatically improves the response time.
Improved response time for a bitmap scan
As shown below, access is much faster than a full-table scan or a B-tree index scan.
In spite of the advantages they offer, bitmapped indexes are not applicable to every query. They are most useful when the following conditions are true:
Index columns have few distinct values (less than 20)
The SQL has several predicates involving bitmap indexes in the WHERE clause
The SQL select statement is INDEX ONLY, meaning that reading the index without reading the table will satisfy the query.
In summary, bitmap indexes provide excellent performance, while using less storage. Because of their different performance characteristics, you should create bitmap indexes on low cardinality data, and keep B*tree indexes on high-cardinality data.
The next lesson discusses STAR index queries.