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add clarification for maxSubqueryRows (#11687)
* add clarification for maxSubqueryRows
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@ -1678,7 +1678,7 @@ Druid uses Jetty to serve HTTP requests. Each query being processed consumes a s
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|`druid.server.http.enableRequestLimit`|If enabled, no requests would be queued in jetty queue and "HTTP 429 Too Many Requests" error response would be sent. |false|
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|`druid.server.http.defaultQueryTimeout`|Query timeout in millis, beyond which unfinished queries will be cancelled|300000|
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|`druid.server.http.maxScatterGatherBytes`|Maximum number of bytes gathered from data processes such as Historicals and realtime processes to execute a query. Queries that exceed this limit will fail. This is an advance configuration that allows to protect in case Broker is under heavy load and not utilizing the data gathered in memory fast enough and leading to OOMs. This limit can be further reduced at query time using `maxScatterGatherBytes` in the context. Note that having large limit is not necessarily bad if broker is never under heavy concurrent load in which case data gathered is processed quickly and freeing up the memory used. Human-readable format is supported, see [here](human-readable-byte.md). |Long.MAX_VALUE|
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|`druid.server.http.maxSubqueryRows`|Maximum number of rows from subqueries per query. These rows are stored in memory.|100000|
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|`druid.server.http.maxSubqueryRows`|Maximum number of rows from all subqueries per query. Druid stores the subquery rows in temporary tables that live in the Java heap. `druid.server.http.maxSubqueryRows` is a guardrail to prevent the system from exhausting available heap. When a subquery exceeds the row limit, Druid throws a resource limit exceeded exception: "Subquery generated results beyond maximum."<br><br>It is a good practice to avoid large subqueries in Druid. However, if you choose to raise the subquery row limit, you must also increase the heap size of all Brokers, Historicals, and task Peons that process data for the subqueries to accommodate the subquery results.<br><br>There is no formula to calculate the correct value. Trial and error is the best approach.|100000|
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|`druid.server.http.gracefulShutdownTimeout`|The maximum amount of time Jetty waits after receiving shutdown signal. After this timeout the threads will be forcefully shutdown. This allows any queries that are executing to complete(Only values greater than zero are valid).|`PT30S`|
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|`druid.server.http.unannouncePropagationDelay`|How long to wait for zookeeper unannouncements to propagate before shutting down Jetty. This is a minimum and `druid.server.http.gracefulShutdownTimeout` does not start counting down until after this period elapses.|`PT0S` (do not wait)|
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|`druid.server.http.maxQueryTimeout`|Maximum allowed value (in milliseconds) for `timeout` parameter. See [query-context](../querying/query-context.md) to know more about `timeout`. Query is rejected if the query context `timeout` is greater than this value. |Long.MAX_VALUE|
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@ -85,9 +85,7 @@ their "base" (bottom-leftmost) datasource, as described in the [join](#join) sec
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the results are brought back to the Broker. Then, the Broker continues on with the rest of the query as if the subquery
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was replaced with an inline datasource.
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In most cases, subquery results are fully buffered in memory on the Broker before the rest of the query proceeds,
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meaning subqueries execute sequentially. The total number of rows buffered across all subqueries of a given query
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in this way cannot exceed the [`druid.server.http.maxSubqueryRows` property](../configuration/index.md).
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In most cases, Druid buffers subquery results in memory on the Broker before the rest of the query proceeds. Therefore, subqueries execute sequentially. The total number of rows buffered across all subqueries of a given query cannot exceed the [`druid.server.http.maxSubqueryRows`](../configuration/index.md) which defaults to 100000 rows. Otherwise Druid throws a resource limit exceeded exception: "Subquery generated results beyond maximum."
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There is one exception: if the outer query and all subqueries are the [groupBy](groupbyquery.md) type, then subquery
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results can be processed in a streaming fashion and the `druid.server.http.maxSubqueryRows` limit does not apply.
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