Query context

In addition, some query types offer context parameters specific to that query type.

The GroupBy and Timeseries query types can run in vectorized mode, which speeds up query execution by processing batches of rows at a time. Not all queries can be vectorized. In particular, vectorization currently has the following requirements:

• All query-level filters must either be able to run on bitmap indexes or must offer vectorized row-matchers. These include “selector”, “bound”, “in”, “like”, “regex”, “search”, “and”, “or”, and “not”.
• All filters in filtered aggregators must offer vectorized row-matchers.
• All aggregators must offer vectorized implementations. These include “count”, “doubleSum”, “floatSum”, “longSum”, “hyperUnique”, and “filtered”.
• For GroupBy: All dimension specs must be “default” (no extraction functions or filtered dimension specs).
• For GroupBy: No multi-value dimensions.
• For Timeseries: No “descending” order.

Vectorization is an alpha-quality feature as of Druid 0.17.1. We heartily welcome any feedback and testing from the community as we work to battle-test it.