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[SPARK-22606][Streaming]Add threadId to the CachedKafkaConsumer key #19819

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[SPARK-22606][Streaming]Add threadId to the CachedKafkaConsumer key #19819

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9 changes: 5 additions & 4 deletions ...l/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/CachedKafkaConsumer.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -107,7 +107,7 @@ class CachedKafkaConsumer[K, V] private(
private[kafka010]
object CachedKafkaConsumer extends Logging {

private case class CacheKey(groupId: String, topic: String, partition: Int)
private case class CacheKey(groupId: String, topic: String, partition: Int, threadId: Long)

// Don't want to depend on guava, don't want a cleanup thread, use a simple LinkedHashMap
private var cache: ju.LinkedHashMap[CacheKey, CachedKafkaConsumer[_, _]] = null
Expand Down Expand Up @@ -147,9 +147,10 @@ object CachedKafkaConsumer extends Logging {
groupId: String,
topic: String,
partition: Int,
threadId: Long,
kafkaParams: ju.Map[String, Object]): CachedKafkaConsumer[K, V] =
CachedKafkaConsumer.synchronized {
val k = CacheKey(groupId, topic, partition)
val k = CacheKey(groupId, topic, partition, threadId)
val v = cache.get(k)
if (null == v) {
logInfo(s"Cache miss for $k")
Expand All @@ -175,8 +176,8 @@ object CachedKafkaConsumer extends Logging {
new CachedKafkaConsumer[K, V](groupId, topic, partition, kafkaParams)

/** remove consumer for given groupId, topic, and partition, if it exists */
def remove(groupId: String, topic: String, partition: Int): Unit = {
val k = CacheKey(groupId, topic, partition)
def remove(groupId: String, topic: String, partition: Int, threadId: Long): Unit = {
val k = CacheKey(groupId, topic, partition, threadId)
logInfo(s"Removing $k from cache")
val v = CachedKafkaConsumer.synchronized {
cache.remove(k)
Expand Down
6 changes: 4 additions & 2 deletions external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaRDD.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -193,6 +193,8 @@ private[spark] class KafkaRDD[K, V](
logInfo(s"Computing topic ${part.topic}, partition ${part.partition} " +
s"offsets ${part.fromOffset} -> ${part.untilOffset}")

val threadId = Thread.currentThread().getId

val groupId = kafkaParams.get(ConsumerConfig.GROUP_ID_CONFIG).asInstanceOf[String]

context.addTaskCompletionListener{ context => closeIfNeeded() }
Expand All @@ -201,9 +203,9 @@ private[spark] class KafkaRDD[K, V](
CachedKafkaConsumer.init(cacheInitialCapacity, cacheMaxCapacity, cacheLoadFactor)
if (context.attemptNumber >= 1) {
// just in case the prior attempt failures were cache related
CachedKafkaConsumer.remove(groupId, part.topic, part.partition)
CachedKafkaConsumer.remove(groupId, part.topic, part.partition, threadId)
}
CachedKafkaConsumer.get[K, V](groupId, part.topic, part.partition, kafkaParams)
CachedKafkaConsumer.get[K, V](groupId, part.topic, part.partition, threadId, kafkaParams)
} else {
CachedKafkaConsumer.getUncached[K, V](groupId, part.topic, part.partition, kafkaParams)
}
Expand Down