Marcin Kuthan created SPARK-17853:
-------------------------------------
Summary: Kafka OffsetOutOfRangeException on DStreams union from
separate Kafka clusters with identical topic names.
Key: SPARK-17853
URL: https://issues.apache.org/jira/browse/SPARK-17853
Project: Spark
Issue Type: Bug
Components: Streaming
Affects Versions: 2.0.0
Reporter: Marcin Kuthan
During migration from Spark 1.6 to 2.0 I observed OffsetOutOfRangeException
reported by Kafka client. In our scenario we create single DStream as a union
of multiple DStreams. One DStream for one Kafka cluster (multi dc solution).
Both Kafka clusters have the same topics and number of partitions.
After quick investigation, I found that class DirectKafkaInputDStream keeps
offset state for topic and partitions, but it is not aware of different Kafka
clusters.
For every topic, single DStream is created as a union from all configured Kafka
clusters.
{code}
class KafkaDStreamSource(configs: Iterable[Map[String, String]]) {
def createSource(ssc: StreamingContext, topic: String): DStream[(String,
Array[Byte])] = {
val streams = configs.map { config =>
val kafkaParams = config
val kafkaTopics = Set(topic)
KafkaUtils.
createDirectStream[String, Array[Byte]](
ssc,
LocationStrategies.PreferConsistent,
ConsumerStrategies.Subscribe[String, Array[Byte]](kafkaTopics,
kafkaParams)
).map { record =>
(record.key, record.value)
}
}
ssc.union(streams.toSeq)
}
}
{code}
At the end, offsets from one Kafka cluster overwrite offsets from second one.
Fortunately OffsetOutOfRangeException was thrown because offsets in both Kafka
clusters are significantly different.
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