我想将数据从Spark作业推送到kafka。
我正在使用Spark Kafka流，如下所示。
pivotDataDataset.selectExpr("CAST(columnName as STRING) value")
.write()
.format("kafka")
.option("kafka.bootstrap.servers","kafkaServerIp:9092")
.option("topic", "topicname")
.save();
这给了我以下例外。
Driver stacktrace:
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 4, prod-fdphadoop-krios-dn-1015, executor 1): org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms.
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1517)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1505)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1504)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1504)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1732)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1687)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1676)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2050)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2069)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2094)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:926)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:924)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:924)
at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1.apply$mcV$sp(KafkaWriter.scala:89)
at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1.apply(KafkaWriter.scala:89)
at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1.apply(KafkaWriter.scala:89)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecutio Caused by: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms.
18/11/26 21:38:47 INFO yarn.ApplicationMaster: Final app status: FAILED, exitCode: 15, (reason: User class threw exception: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 4, prod-fdphadoop-krios-dn-1015, executor 1): org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms.
我正在尝试调试..但是无法做到这一点。