Query context

Query context

The query context is used for various query configuration parameters. The following parameters apply to all queries.

property	default	description
timeout	`druid.server.http.defaultQueryTimeout`	Query timeout in millis, beyond which unfinished queries will be cancelled. 0 timeout means `no timeout`. To set the default timeout, see Broker configuration
priority	`0`	Query Priority. Queries with higher priority get precedence for computational resources.
queryId	auto-generated	Unique identifier given to this query. If a query ID is set or known, this can be used to cancel the query
useCache	`true`	Flag indicating whether to leverage the query cache for this query. When set to false, it disables reading from the query cache for this query. When set to true, Apache Druid uses `druid.broker.cache.useCache` or `druid.historical.cache.useCache` to determine whether or not to read from the query cache
populateCache	`true`	Flag indicating whether to save the results of the query to the query cache. Primarily used for debugging. When set to false, it disables saving the results of this query to the query cache. When set to true, Druid uses `druid.broker.cache.populateCache` or `druid.historical.cache.populateCache` to determine whether or not to save the results of this query to the query cache
useResultLevelCache	`true`	Flag indicating whether to leverage the result level cache for this query. When set to false, it disables reading from the query cache for this query. When set to true, Druid uses `druid.broker.cache.useResultLevelCache` to determine whether or not to read from the result-level query cache
populateResultLevelCache	`true`	Flag indicating whether to save the results of the query to the result level cache. Primarily used for debugging. When set to false, it disables saving the results of this query to the query cache. When set to true, Druid uses `druid.broker.cache.populateResultLevelCache` to determine whether or not to save the results of this query to the result-level query cache
bySegment	`false`	Return “by segment” results. Primarily used for debugging, setting it to `true` returns results associated with the data segment they came from
finalize	`true`	Flag indicating whether to “finalize” aggregation results. Primarily used for debugging. For instance, the `hyperUnique` aggregator will return the full HyperLogLog sketch instead of the estimated cardinality when this flag is set to `false`
chunkPeriod	`P0D` (off)	At the Broker process level, long interval queries (of any type) may be broken into shorter interval queries to parallelize merging more than normal. Broken up queries will use a larger share of cluster resources, but, if you use groupBy “v1, it may be able to complete faster as a result. Use ISO 8601 periods. For example, if this property is set to `P1M` (one month), then a query covering a year would be broken into 12 smaller queries. The broker uses its query processing executor service to initiate processing for query chunks, so make sure `druid.processing.numThreads` is configured appropriately on the broker. groupBy queries do not support chunkPeriod by default, although they do if using the legacy “v1” engine. This context is deprecated since it’s only useful for groupBy “v1”, and will be removed in the future releases.
maxScatterGatherBytes	`druid.server.http.maxScatterGatherBytes`	Maximum number of bytes gathered from data processes such as Historicals and realtime processes to execute a query. This parameter can be used to further reduce `maxScatterGatherBytes` limit at query time. See Broker configuration for more details.
maxQueuedBytes	`druid.broker.http.maxQueuedBytes`	Maximum number of bytes queued per query before exerting backpressure on the channel to the data server. Similar to `maxScatterGatherBytes`, except unlike that configuration, this one will trigger backpressure rather than query failure. Zero means disabled.
serializeDateTimeAsLong	`false`	If true, DateTime is serialized as long in the result returned by Broker and the data transportation between Broker and compute process
serializeDateTimeAsLongInner	`false`	If true, DateTime is serialized as long in the data transportation between Broker and compute process
enableParallelMerge	`true`	Enable parallel result merging on the Broker. Note that `druid.processing.merge.useParallelMergePool` must be enabled for this setting to be set to `true`. See Broker configuration for more details.
parallelMergeParallelism	`druid.processing.merge.pool.parallelism`	Maximum number of parallel threads to use for parallel result merging on the Broker. See Broker configuration for more details.
parallelMergeInitialYieldRows	`druid.processing.merge.task.initialYieldNumRows`	Number of rows to yield per ForkJoinPool merge task for parallel result merging on the Broker, before forking off a new task to continue merging sequences. See Broker configuration for more details.
parallelMergeSmallBatchRows	`druid.processing.merge.task.smallBatchNumRows`	Size of result batches to operate on in ForkJoinPool merge tasks for parallel result merging on the Broker. See Broker configuration for more details.

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

TopN queries

property	default	description
minTopNThreshold	`1000`	The top minTopNThreshold local results from each segment are returned for merging to determine the global topN.

Timeseries queries

property	default	description
skipEmptyBuckets	`false`	Disable timeseries zero-filling behavior, so only buckets with results will be returned.

GroupBy queries

See GroupBy query context.

Vectorizable queries

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”.
No virtual columns.
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 immutable segments (not real-time).

Other query types (like TopN, Scan, Select, and Search) ignore the “vectorize” parameter, and will execute without vectorization. These query types will ignore the “vectorize” parameter even if it is set to "force".

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.

property	default	description
vectorize	`false`	Enables or disables vectorized query execution. Possible values are `false` (disabled), `true` (enabled if possible, disabled otherwise, on a per-segment basis), and `force` (enabled, and groupBy or timeseries queries that cannot be vectorized will fail). The `“force”` setting is meant to aid in testing, and is not generally useful in production (since real-time segments can never be processed with vectorized execution, any queries on real-time data will fail). This will override `druid.query.vectorize` if it’s set.
vectorSize	`512`	Sets the row batching size for a particular query. This will override `druid.query.vectorSize` if it’s set.