gaborgsomogyi 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_r346469913
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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:
To answer the question1: Yes, job 2 can use job 1 created producers in the
same JVM. Such case another task retry is needed to recover in the following
way:
* job 2 task 1 attempt 0 runs with producer 1 and fails
* job 2 task 1 attempt 1 runs with producer 3 (this would invalidate
producer 1 and 2 if not used)
If I consider the use-case this would mean 2 jobs must write the same
`TopicPartition` at the same time. Until now I haven't seen use-cases where the
exact same topic would be used by 2 different job (of course this doesn't mean
it's not done).
To answer the question2: Kafka consumers and producers doesn't provide any
kind of self healing.
I think I have to take some time to check the other way because I've similar
fear what @HeartSaVioR mentioned (horror complicated code with catch blocks all
the places where producer touched). The general fear what I have with the
invalidation from exception side is the following: if the code is leaking and
doesn't catch one single exception then the task may not heal itself.
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