Indexing Engine: Multi-Column Index Combinations

When the Indexing Engine processes the scan list, it doesn't just extract the individual index elements. It also generates a list of potential combinations of these elements to allow consideration of multi-column index options. Multi-column indexes have two primary benefits:

They allow a single index to provide a more selective answer, without having to resort to a BitmapAnd operation that combines multiple indexes They allow use of the same index by multiple queries with different clauses (in some cases)

Adding more columns to an index increases its Index Write Overhead, as more data needs to be stored in the index. We avoid recommending a multi-column index when a single column index is good enough.

To assess the best multi-column choice, we generate all different permutations of index elements for each index. We then sort the index elements based on a special set of rules, to make it most effective for each index type:

  • B-Tree: Lead with index elements referenced in a clause through an equality operator (e.g. col = $1), followed by all other elements. Within that set of elements, sort by selectivity (more selective parameters are ordered first).
  • GIST: Sort elements by number of distinct values in the table (more distinct elements are ordered first).

Note that we are still fine tuning the GIST recommendation logic, as well as other indexing types such as GIN (which are not yet available with the Indexing Engine).

Once different combinations have been generated, they are run through "What If?" analysis to determine their cost improvements.

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