Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/15307#discussion_r82855520
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
---
@@ -176,7 +184,9 @@ class StreamExecution(
// Mark ACTIVE and then post the event. QueryStarted event is
synchronously sent to listeners,
// so must mark this as ACTIVE first.
state = ACTIVE
- postEvent(new QueryStarted(this.toInfo)) // Assumption: Does not
throw exception.
+
sparkSession.sparkContext.env.metricsSystem.registerSource(streamMetrics)
--- End diff --
This is not expensive. A lot of these sources are registered by default in
the SparkContext, the additional overhead is minimal. Also, the overhead
depends solely on how frequently the Dropwizard metrics polls for the values of
rates, latencies, etc. Typically this is every 10s of seconds.
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