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Oracle Bitmapped Indexes

Oracle Tips by Burleson Consulting

The Data Warehouse Development Life Cycle

Oracle Features for the Data Warehouse
Oracle Bitmapped Indexes

Bitmaps are especially important for data warehouse/decision support systems, where ad-hoc, unanticipated queries make it impractical for the Oracle Remote DBA to index on all possible combinations of columns. Assume that a manager wants to know the average income for all college-educated customers who drive red or blue cars in Wyoming or Nevada. Furthermore, assume that there are 1 million rows in the customer table. The following query would be very hard to service using traditional indexing:

select avg(yearly_income)
from customer
state_residence in (‘WY’,’NV)
order by avg(yearly_income);

In a bitmapped index, it is not necessary to read all 1 million rows in the customer table. Instead, the query manager will build row-id lists for all “1” values for education, car_color, and state_residence, and then match up the row-ids for those that appear in all three columns. When the query is ready to access the rows, it already has a list of row-ids for all rows that meet the selection criteria.

To understand bitmapped indexes, imagine a very wide, fat table with only a few rows. In a bitmapped index, each unique value has one row, such that our REGION index contains only four rows. Across the bitmap, each row in the base table is represented by a column, with a “1” in the bitmap array if the value is true, and a “0” if it is false. Because of the high amount of repeating ones and zeros, bitmapped indexes can be very effectively compressed and expanded at runtime. In fact, the lower the cardinality, the better the compression, such that we can expect a higher compression of a GENDER index with two distinct values than with a STATE index with 50 distinct values. Uncompressed, the STATE index would be 48 times larger than the GENDER bitmap, because one row in the bitmap array is required for each unique value.

This is an excerpt from "High Performance Data Warehousing".
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