Additional Indexing Options
If the data is not very selective, you may consider using bitmap indexes. As described in Chapter
16, bitmap indexes are most effective for queries against large, static data sets with few distinct
values. You can create both bitmap indexes and normal (B-tree) indexes on the same table, and
Oracle will perform any necessary index conversions dynamically during query processing. See
Chapter 16 for details on using bitmap indexes.
NOTE
Avoid creating bitmap indexes on tables modified by online transactions;
data warehouse tables, however, are excellent candidates for bitmap
indexes.
If two tables are frequently queried together, then clusters may be effective in improving
performance. Clusters store rows from multiple tables in the same physical data blocks, based
on their logical values (the cluster key).
Queries in which a column??™s value is compared to an exact value (rather than a range of
values) are called equivalence queries. A hash cluster stores a row in a specific location based
on its value in the cluster key column. Every time a row is inserted, its cluster key value is used
to determine in which block it should be stored; this same logic can be used during queries to
quickly find data blocks that are needed for retrieval. Hash clusters are designed to improve the
performance of equivalence queries; they will not be as helpful in improving the performance of
the range queries discussed earlier.
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