The following question appeared in a comment to an earlier posting on multi-column bitmap indexes and the inability of Oracle to create a bitmap index join when (to the human eye) the strategy was an obvious choice.
I have a query which is using 2 indexes both are bitmap indexes (sizes are 37 and 24 Mbs) and table size is 17gb. While i ran the following query which can very well get the index itself, it takes around 6-8 minutes and using pga around 3 gb.
could you please explain me why ?
In a recent note I wrote about index joins I made a passing comment about limitations in the optimizer’s available strategies that might make you choose to write your code to emulate an index join through explicit SQL references.
Here are two SQL similar SQL statements (with execution plans) that demonstrate the initial problem – the first is just a restatement of the basic example I supplied in the first article:
I’ve recently been writing about the index join mechanism and ways of emulating it. Those notes were originally inspired by an example of an index join that appeared on OTN a little while ago.
It was a plan that combined “bitmap/btree conversion” with the basic index join strategy so, with hindsight, it was an “obvious” and brilliant execution plan for a certain type of query. The query in the original posting was a simple select (with no predicates) against a huge table in a data warehouse – presumably extracting a small number of columns from a much wider row.
In an earlier article introducing the index join I raised a question that came up at the first ES2N virtual conference:
“If you hint an index hash join, is there any way of telling Oracle the order in which it should use the indexes?”
Consider the following example:
One of the less well known access paths available to the optimizer is the “index join” also known as the “index hash join” path. It’s an access path that can be used when the optimizer decides that it doesn’t need to visit a table to supply the select list because there are indexes on the table that, between them, hold all the required columns. A simple example might look something like the following: