Github user JasonMWhite commented on a diff in the pull request:
https://github.com/apache/spark/pull/10089#discussion_r46449467
--- Diff:
external/kafka/src/test/scala/org/apache/spark/streaming/kafka/DirectKafkaStreamSuite.scala
---
@@ -364,8 +365,8 @@ class DirectKafkaStreamSuite
val batchIntervalMilliseconds = 100
val estimator = new ConstantEstimator(100)
- val messageKeys = (1 to 200).map(_.toString)
- val messages = messageKeys.map((_, 1)).toMap
+ val messages = Map("foo" -> 200)
+ kafkaTestUtils.sendMessages(topic, messages)
--- End diff --
The kafka messages don't actually need to be sent three times, just once is
sufficent for all tests. When I send "foo" 200 times in one batch, they all go
to the same partition. However, when I do this 3 times (for each of 100, 50,
20), the batches of 200 go to a random partition each time. I suspect something
in how the test kafka cluster does the partitioning.
I was usually getting 200 on 1 partitions, and 400 on the other 2. I was
explicitly changing the test case to "all the messages are on one partition"
since I can't control the split deterministically.
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