Github user JasonMWhite commented on a diff in the pull request:
https://github.com/apache/spark/pull/17774#discussion_r113753764
--- Diff:
external/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/DirectKafkaStreamSuite.scala
---
@@ -617,6 +617,94 @@ class DirectKafkaStreamSuite
ssc.stop()
}
+ test("maxMessagesPerPartition with rate equal to one") {
+ val topic = "backpressure"
+ val kafkaParams = getKafkaParams()
+ val batchIntervalMilliseconds = 10000
+ val sparkConf = new SparkConf()
+ // Safe, even with streaming, because we're using the direct API.
+ // Using 1 core is useful to make the test more predictable.
+ .setMaster("local[1]")
+ .setAppName(this.getClass.getSimpleName)
+ .set("spark.streaming.kafka.maxRatePerPartition", "100")
+
+ // Setup the streaming context
+ ssc = new StreamingContext(sparkConf,
Milliseconds(batchIntervalMilliseconds))
+ val estimatedRate = 1
+ val fromOffsets = Map(
+ new TopicPartition(topic, 0) -> 0L,
+ new TopicPartition(topic, 1) -> 0L,
+ new TopicPartition(topic, 2) -> 0L
+ )
+ val kafkaStream = withClue("Error creating direct stream") {
+ new DirectKafkaInputDStream[String, String](
+ ssc,
+ preferredHosts,
+ ConsumerStrategies.Subscribe[String, String](List(topic),
kafkaParams.asScala),
+ new DefaultPerPartitionConfig(sparkConf)
+ ) {
+ currentOffsets = fromOffsets
+ override val rateController = Some(new ConstantRateController(id,
null, estimatedRate))
+ }
+ }
+
+ val offsets = Map[TopicPartition, Long](
+ new TopicPartition(topic, 0) -> 100L,
+ new TopicPartition(topic, 1) -> 100L,
+ new TopicPartition(topic, 2) -> 100L
+ )
+ val result = kafkaStream.maxMessagesPerPartition(offsets)
+ assert(result.isDefined, s"Messages per partitions should exist for
estimated rate of 1")
--- End diff --
The actual result should be deterministic, why not check the correct value
instead of just `not None` ?
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