Tables with dozens of updates per second can see slowdowns because of the overhead of updating the bitmap.So, which is the right maxi Benchmarks have shown these trends in SQL performance and the number of distinct bitmap index values (as a percentage of total table rows), and the clustering factor for the index column.As a bitmap is being created or updated, Oracle looks to the previous index entry.If it is the same, Oracle replaces the bitmap entry with a "same as prior" flag, and continues until a new key value is detected.It underlies the Oracle APIs of popular languages and environments including Node.js, Python and PHP, as well as providing access for OCI, OCCI, JDBC, ODBC and Pro*C applications.Tools included in Instant Client, such as SQL*Plus and Oracle Data Pump, provide quick and convenient data access.As a general rule, a cardinality of under 1% makes a good candidate for a bitmap index." However, there are rare cases where high cardinality columns can be used in bitmap indexes, and Oracle suggests that these conditions are acceptable for a bitmap index: Now that we understand bitmap index compression, it should be clear that there are rare cases where high cardinality columns might be candidates for bitmap indexes.So, which are the right maximum values for your bitmap index? You will need to run performance benchmarks on your unique database to see!
You are correct that the maximum cardinality for bitmap indexes is a function of the number of distinct values and the size of the key, but far and away it is the number of distinct values that is the largest contributing factor to the maximum number of distinct values you can have in a bitmap index.
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If a bitmap index column has a "good" clustering factor (e.g.
close to the number of blocks in the table) then the index values are adjacent, and Oracle will be able to compress the index far better than a bitmap on an un-clustered column.