zsxwing commented on a change in pull request #26470: [SPARK-27042][SS]
Invalidate cached Kafka producer in case of task retry
URL: https://github.com/apache/spark/pull/26470#discussion_r346969043
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File path:
external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/CachedKafkaProducer.scala
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@@ -93,6 +93,10 @@ private[kafka010] object CachedKafkaProducer extends
Logging {
.setAuthenticationConfigIfNeeded()
.build()
val key = toCacheKey(updatedKafkaParams)
+ if (TaskContext.get != null && TaskContext.get.attemptNumber >= 1) {
Review comment:
> I would assume it can't heal if programming failure would be in the
producer code itself.
That's true. Softwares have bugs. But I have never heard any Kafka producer
issues reported when using Spark. The task failure most likely is a user error,
transient network error, or something unrelated. And a task failure like this
should be isolated and should not impact other tasks in the same executor. This
seems overkill.
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