Kalvin Chau created SPARK-19185:
-----------------------------------
Summary: ConcurrentModificationExceptions with
CachedKafkaConsumers when Windowing
Key: SPARK-19185
URL: https://issues.apache.org/jira/browse/SPARK-19185
Project: Spark
Issue Type: Bug
Components: DStreams
Affects Versions: 2.0.2
Environment: Spark 2.0.2
Spark Streaming Kafka 010
Mesos 0.28.0 - client mode
spark.executor.cores 1
spark.mesos.extra.cores 1
Reporter: Kalvin Chau
We've been running into ConcurrentModificationExcpetions "KafkaConsumer is not
safe for multi-threaded access" with the CachedKafkaConsumer. I've been working
through debugging this issue and after looking through some of the spark source
code I think this is a bug.
Our set up is:
Spark 2.0.2, running in Mesos 0.28.0-2 in client mode, using
Spark-Streaming-Kafka-010
spark.executor.cores 1
spark.mesos.extra.cores 1
Batch interval: 10s, window interval: 180s, and slide interval: 30s
We would see the exception when in one executor there are two task worker
threads assigned the same Topic+Partition, but a different set of offsets.
They would both get the same CachedKafkaConsumer, and whichever task thread
went first would seek and poll for all the records, and at the same time the
second thread would try to seek to its offset but fail because it is unable to
acquire the lock.
Time0 E0 Task0 - TopicPartition("abc", 0) X to Y
Time0 E0 Task1 - TopicPartition("abc", 0) Y to Z
Time1 E0 Task0 - Seeks and starts to poll
Time1 E0 Task1 - Attempts to seek, but fails
Here are some relevant logs:
{code}
17/01/06 03:10:01 Executor task launch worker-1 INFO KafkaRDD: Computing topic
test-topic, partition 2 offsets 4394204414 -> 4394238058
17/01/06 03:10:01 Executor task launch worker-0 INFO KafkaRDD: Computing topic
test-topic, partition 2 offsets 4394238058 -> 4394257712
17/01/06 03:10:01 Executor task launch worker-1 DEBUG CachedKafkaConsumer: Get
spark-executor-consumer test-topic 2 nextOffset 4394204414 requested 4394204414
17/01/06 03:10:01 Executor task launch worker-0 DEBUG CachedKafkaConsumer: Get
spark-executor-consumer test-topic 2 nextOffset 4394204414 requested 4394238058
17/01/06 03:10:01 Executor task launch worker-0 INFO CachedKafkaConsumer:
Initial fetch for spark-executor-consumer test-topic 2 4394238058
17/01/06 03:10:01 Executor task launch worker-0 DEBUG CachedKafkaConsumer:
Seeking to test-topic-2 4394238058
17/01/06 03:10:01 Executor task launch worker-0 WARN BlockManager: Putting
block rdd_199_2 failed due to an exception
17/01/06 03:10:01 Executor task launch worker-0 WARN BlockManager: Block
rdd_199_2 could not be removed as it was not found on disk or in memory
17/01/06 03:10:01 Executor task launch worker-0 ERROR Executor: Exception in
task 49.0 in stage 45.0 (TID 3201)
java.util.ConcurrentModificationException: KafkaConsumer is not safe for
multi-threaded access
at
org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
at
org.apache.kafka.clients.consumer.KafkaConsumer.seek(KafkaConsumer.java:1132)
at
org.apache.spark.streaming.kafka010.CachedKafkaConsumer.seek(CachedKafkaConsumer.scala:95)
at
org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:69)
at
org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:227)
at
org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:193)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:462)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at
org.apache.spark.storage.memory.MemoryStore.putIteratorAsBytes(MemoryStore.scala:360)
at
org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:951)
at
org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:926)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
at
org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:926)
at
org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:670)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:281)
at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:105)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
17/01/06 03:10:01 Executor task launch worker-1 DEBUG CachedKafkaConsumer:
Polled [test-topic-2] 8237
17/01/06 03:10:01 Executor task launch worker-1 DEBUG CachedKafkaConsumer: Get
spark-executor-consumer test-topic 2 nextOffset 4394204415 requested 4394204415
17/01/06 03:10:01 Executor task launch worker-1 DEBUG CachedKafkaConsumer: Get
spark-executor-consumer test-topic 2 nextOffset 4394204416 requested 4394204416
...
{code}
It looks like when WindowedDStream does the getOrCompute call its computing all
the sets of of offsets it needs and tries to farm out the work in parallel. So
each available worker task gets each set of offsets that need to be read.
After realizing what was going on I tested four states:
* spark.executor.cores 1 and spark.mesos.extra.cores 0
** No Exceptions
* spark.executor.cores 1 and spark.mesos.extra.cores 1
** ConcurrentModificationException
* spark.executor.cores 2 and spark.mesos.extra.cores 0
** ConcurrentModificationException
* spark.executor.cores 2 and spark.mesos.extra.cores 1
** ConcurrentModificationException
Minimal set of code I was able to reproduce with:
Streaming batch interval was set to 2 seconds. This increased the rate of
exceptions I saw.
{code}
val kafkaParams = Map[String, Object](
"bootstrap.servers" -> brokers,
"key.deserializer" -> classOf[KafkaAvroDeserializer],
"value.deserializer" -> classOf[KafkaAvroDeserializer],
"enable.auto.commit" -> (false: java.lang.Boolean),
"group.id" -> groupId,
"schema.registry.url" -> schemaRegistryUrl,
"auto.offset.reset" -> offset
)
val inputStream = KafkaUtils.createDirectStream[Object, Object](
ssc,
PreferConsistent,
Subscribe[Object, Object]
(kafkaTopic, kafkaParams)
)
val windowStream = inputStream.map(_.toString).window(Seconds(180), Seconds(30))
windowStream.foreachRDD{
rdd => {
val filtered = rdd.filter(_.contains("idb"))
filtered.foreach(
message => {
var i = 0
if (i == 0) {
logger.info(message)
i = i + 1
}
}
)
}
}
{code}
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