- For , context parameters are provided either as a JSON object named to the HTTP POST API, or as properties to the JDBC connection.
- For native queries, context parameters are provided as a JSON object named
context
.
Note that setting query context will override both the default value and the runtime properties value in the format of druid.query.default.context.{property_key}
(if set).
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 virtual columns must offer vectorized implementations. Currently for expression virtual columns, support for vectorization is decided on a per expression basis, depending on the type of input and the functions used by the expression. See the currently supported list in the .
- 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.
- Only table datasources (not joins, subqueries, lookups, or inline datasources).
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