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Updating a materialized view in oracle

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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.

At an extreme case, consider a million rows table where the column has 100,000 distinct values and clustering_factor ~= blocks.

You can use the Remember how bitmap indexes are generally used.

Because they are low cardinality, they have very little value by themselves, and the power comes when Oracle combines multiple bitmaps in a bitmap merge operation: We also have to deal with the volatility of low cardinality columns.

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.

As the number if distinct values increases, the size of the bitmap increases exponentially, such that an index with 100 values may perform thousands of times faster than a bitmap index on 1,000 distinct column values.

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.

All else being equal, cardinality is one of the most important factors in deciding to use a bitmap index, but there are rare cases where a bitmap on a column with 10,000 key values might be appropriate.

updating a materialized view in oracle-27

Also, remember that bitmap indexes are only suitable for static tables and materialized views which are updated at nigh and rebuilt after batch row loading.

Hence, a bitmap index on a million row table with ten distinct values in the index column will have ten million cells in the bitmap.

Conversely, a bitmap on a million rows table with an index column with 1,000 distinct values will be much larger, with a billion cells.

As a personal go-to guide, it pays attention to issues which I have come across, and contains summarized information which I find useful.

Oracle is huge and the possible tuning and diagnostic approaches are overwhelming; a quick look at Oracle’s Tuning Guide will demonstrate this.