kafka和spark流可以在本地工作，但不能在独立模式下工作

jhkqcmku  于 2021-05-27  发布在  Spark
关注(0)|答案(0)|浏览(361)

我正在尝试用一个非常简单的脚本来使用spark流：

from pyspark import SparkContext, SparkConf
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils

sc = SparkContext(appName="PythonSparkStreamingKafka")

ssc = StreamingContext(sc, 1)
kafkaParams = {"metadata.broker.list": "172.31.71.104:9092",
                       "auto.offset.reset": "smallest"}

training = KafkaUtils.createDirectStream(ssc, ["test"], kafkaParams)

training.pprint()

ssc.start()
ssc.awaitTermination()

但是，尽管它在本地工作，但是当集群使用独立模式时，它会崩溃。我也尝试过用createstream代替createdirectstream，但我仍然有同样的问题。我有一个有4台机器的集群：
一台机器与Kafka生产商，一个经纪人和一个Zookeeper1台机器是司机2台机器是工人。
奇怪的是，当我把Kafka的制作人、经纪人和zookeeper放在驱动程序所在的同一台机器上时，它在本地和集群中工作。但显然为了可伸缩性和模块化，我想使用当前的配置。
我使用的是spark 2.4.6，kafka流api是“spark-streaming-kafka-0-8-assembly\u 2.11-2.4.6”，我目前使用的kafka版本是kafka\u 2.11-2.4.1
结果如下：

020-07-24 09:48:25,869 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, 172.31.69.185, executor 0): java.nio.channels.ClosedChannelException
at kafka.network.BlockingChannel.send(BlockingChannel.scala:100)
at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:78)
at kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:68)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:110)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:197)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:213)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at org.apache.spark.util.NextIterator.foreach(NextIterator.scala:21)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:561)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:346)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:195)

2020-07-24 09:48:27,174 INFO scheduler.DAGScheduler: ResultStage 0 (runJob at PythonRDD.scala:153) failed in 2.943 s due to Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, 172.31.79.221, executor 1): java.nio.channels.ClosedChannelException
at kafka.network.BlockingChannel.send(BlockingChannel.scala:100)
at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:78)
at kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:68)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:110)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:197)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:213)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at org.apache.spark.util.NextIterator.foreach(NextIterator.scala:21)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:561)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:346)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:195)

Driver stacktrace:
2020-07-24 09:48:27,179 INFO scheduler.DAGScheduler: Job 0 failed: runJob at PythonRDD.scala:153, took 3.010820 s
2020-07-24 09:48:27,190 INFO scheduler.JobScheduler: Finished job streaming job 1595584104000 ms.0 from job set of time 1595584104000 ms
2020-07-24 09:48:27,191 INFO scheduler.JobScheduler: Starting job streaming job 1595584105000 ms.0 from job set of time 1595584105000 ms
2020-07-24 09:48:27,193 ERROR scheduler.JobScheduler: Error running job streaming job 1595584104000 ms.0
org.apache.spark.SparkException: An exception was raised by Python:
Traceback (most recent call last):
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/streaming/util.py", line 68, in call
    r = self.func(t, *rdds)
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/streaming/dstream.py", line 173, in takeAndPrint
    taken = rdd.take(num + 1)
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 1360, in take
    res = self.context.runJob(self, takeUpToNumLeft, p)
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/context.py", line 1069, in runJob
    sock_info = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)
  File "/home/ubuntu/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/home/ubuntu/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, 172.31.79.221, executor 1): java.nio.channels.ClosedChannelException
at kafka.network.BlockingChannel.send(BlockingChannel.scala:100)
at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:78)
at kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:68)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:110)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:197)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:213)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at org.apache.spark.util.NextIterator.foreach(NextIterator.scala:21)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:561)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:346)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:195)

Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1891)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1879)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1878)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1878)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:927)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2112)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2061)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2050)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:738)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:153)
at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.nio.channels.ClosedChannelException
at kafka.network.BlockingChannel.send(BlockingChannel.scala:100)
at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:78)
at kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:68)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:110)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:197)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:213)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at org.apache.spark.util.NextIterator.foreach(NextIterator.scala:21)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:561)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:346)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:195)

at org.apache.spark.streaming.api.python.TransformFunction.callPythonTransformFunction(PythonDStream.scala:95)
at org.apache.spark.streaming.api.python.TransformFunction.apply(PythonDStream.scala:78)
at org.apache.spark.streaming.api.python.PythonDStream$$anonfun$callForeachRDD$1.apply(PythonDStream.scala:179)
at org.apache.spark.streaming.api.python.PythonDStream$$anonfun$callForeachRDD$1.apply(PythonDStream.scala:179)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:257)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:256)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2020-07-24 09:48:27,211 INFO spark.SparkContext: Starting job: runJob at PythonRDD.scala:153
2020-07-24 09:48:27,215 INFO scheduler.DAGScheduler: Got job 1 (runJob at PythonRDD.scala:153) with 1 output partitions
2020-07-24 09:48:27,215 INFO scheduler.DAGScheduler: Final stage: ResultStage 1 (runJob at PythonRDD.scala:153)
2020-07-24 09:48:27,215 INFO scheduler.DAGScheduler: Parents of final stage: List()
2020-07-24 09:48:27,216 INFO scheduler.DAGScheduler: Missing parents: List()
2020-07-24 09:48:27,216 INFO scheduler.DAGScheduler: Submitting ResultStage 1 (PythonRDD[9] at RDD at PythonRDD.scala:53), which has no missing parents
2020-07-24 09:48:27,220 INFO memory.MemoryStore: Block broadcast_1 stored as values in memory (estimated size 6.9 KB, free 366.3 MB)
2020-07-24 09:48:27,223 INFO memory.MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 4.0 KB, free 366.3 MB)
2020-07-24 09:48:27,225 INFO storage.BlockManagerInfo: Added broadcast_1_piece0 in memory on ip-172-31-69-46.ec2.internal:41579 (size: 4.0 KB, free: 366.3 MB)
2020-07-24 09:48:27,226 INFO spark.SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1163
2020-07-24 09:48:27,227 INFO scheduler.DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (PythonRDD[9] at RDD at PythonRDD.scala:53) (first 15 tasks are for partitions Vector(0))
2020-07-24 09:48:27,229 INFO scheduler.TaskSchedulerImpl: Adding task set 1.0 with 1 tasks
2020-07-24 09:48:27,230 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 1.0 (TID 4, 172.31.69.185, executor 0, partition 0, ANY, 7785 bytes)
2020-07-24 09:48:27,248 INFO storage.BlockManagerInfo: Added broadcast_1_piece0 in memory on 172.31.69.185:44675 (size: 4.0 KB, free: 366.3 MB)
Traceback (most recent call last):
  File "/home/ubuntu/./prova2.py", line 22, in <module>
    ssc.awaitTermination()
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/streaming/context.py", line 192, in awaitTermination
  File "/home/ubuntu/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
  File "/home/ubuntu/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value

py4j.protocol.Py4JJavaError: An error occurred while calling o23.awaitTermination.
: org.apache.spark.SparkException: An exception was raised by Python:
Traceback (most recent call last):
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/streaming/util.py", line 68, in call
    r = self.func(t, *rdds)
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/streaming/dstream.py", line 173, in takeAndPrint
    taken = rdd.take(num + 1)
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 1360, in take
    res = self.context.runJob(self, takeUpToNumLeft, p)
  File "/home/ubuntu/spark/python/lib/pyspark.zip/pyspark/context.py", line 1069, in runJob
    sock_info = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)
  File "/home/ubuntu/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/home/ubuntu/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, 172.31.79.221, executor 1): java.nio.channels.ClosedChannelException
at kafka.network.BlockingChannel.send(BlockingChannel.scala:100)
at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:78)
at kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:68)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:110)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:197)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:213)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at org.apache.spark.util.NextIterator.foreach(NextIterator.scala:21)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:561)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:346)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:195)

Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1891)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1879)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1878)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1878)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:927)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2112)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2050)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:738)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:153)
at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.nio.channels.ClosedChannelException
at kafka.network.BlockingChannel.send(BlockingChannel.scala:100)
at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:78)
at kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:68)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:110)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:197)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:213)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at org.apache.spark.util.NextIterator.foreach(NextIterator.scala:21)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:561)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:346)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:195)

at org.apache.spark.streaming.api.python.TransformFunction.callPythonTransformFunction(PythonDStream.scala:95)
at org.apache.spark.streaming.api.python.TransformFunction.apply(PythonDStream.scala:78)
at org.apache.spark.streaming.api.python.PythonDStream$$anonfun$callForeachRDD$1.apply(PythonDStream.scala:179)
at org.apache.spark.streaming.api.python.PythonDStream$$anonfun$callForeachRDD$1.apply(PythonDStream.scala:179)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:257)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:256)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)

2020-07-24 09:48:27,532 ERROR scheduler.JobScheduler: Error running job streaming job 1595584105000 ms.0
py4j.Py4JException: Error while sending a command.
at py4j.CallbackClient.sendCommand(CallbackClient.java:397)
at py4j.CallbackClient.sendCommand(CallbackClient.java:356)
at py4j.reflection.PythonProxyHandler.invoke(PythonProxyHandler.java:106)
at com.sun.proxy.$Proxy18.call(Unknown Source)
at org.apache.spark.streaming.api.python.TransformFunction.callPythonTransformFunction(PythonDStream.scala:92)
at org.apache.spark.streaming.api.python.TransformFunction.apply(PythonDStream.scala:78)
at org.apache.spark.streaming.api.python.PythonDStream$$anonfun$callForeachRDD$1.apply(PythonDStream.scala:179)
at org.apache.spark.streaming.api.python.PythonDStream$$anonfun$callForeachRDD$1.apply(PythonDStream.scala:179)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:257)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:256)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: py4j.Py4JNetworkException: Error while sending a command: null response: c

我已经调试了所有的东西，但是我不知道如何解决这个问题。你有什么建议吗？可能是Kafka的配置问题？提前谢谢，
戴维德

apache-kafkaapache-sparkpysparkspark-streamingspark-streaming-kafka

暂无答案！

目前还没有任何答案，快来回答吧！

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