Apache Spark SQL get_json_object java.lang.String cannot be cast to org.apache.spark.unsafe.types.UTF8String

左心房为你撑大大i 提交于 2021-01-07 03:38:27

问题


I am trying to read a json stream from an MQTT broker in Apache Spark with structured streaming, read some properties of an incoming json and output them to the console. My code looks like that:

val spark = SparkSession
  .builder()
  .appName("BahirStructuredStreaming")
  .master("local[*]")
  .getOrCreate()

import spark.implicits._

val topic = "temp"
val brokerUrl = "tcp://localhost:1883"
val lines = spark.readStream
  .format("org.apache.bahir.sql.streaming.mqtt.MQTTStreamSourceProvider")
  .option("topic", topic).option("persistence", "memory")
  .load(brokerUrl)
  .toDF().withColumn("payload", $"payload".cast(StringType))

val jsonDF = lines.select(get_json_object($"payload", "$.eventDate").alias("eventDate"))

    val query = jsonDF.writeStream
      .format("console")
      .start()

    query.awaitTermination()

However, when the json arrives I get the following errors:

Exception in thread "main" org.apache.spark.sql.streaming.StreamingQueryException: Writing job aborted.
=== Streaming Query ===
Identifier: [id = 14d28475-d435-49be-a303-8e47e2f907e3, runId = b5bd28bb-b247-48a9-8a58-cb990edaf139]
Current Committed Offsets: {MQTTStreamSource[brokerUrl: tcp://localhost:1883, topic: temp clientId: paho7247541031496]: -1}
Current Available Offsets: {MQTTStreamSource[brokerUrl: tcp://localhost:1883, topic: temp clientId: paho7247541031496]: 0}

Current State: ACTIVE
Thread State: RUNNABLE

Logical Plan:
Project [get_json_object(payload#22, $.id) AS eventDate#27]
+- Project [id#10, topic#11, cast(payload#12 as string) AS payload#22, timestamp#13]
   +- StreamingExecutionRelation MQTTStreamSource[brokerUrl: tcp://localhost:1883, topic: temp clientId: paho7247541031496], [id#10, topic#11, payload#12, timestamp#13]

    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:300)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
Caused by: org.apache.spark.SparkException: Writing job aborted.
    at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.doExecute(WriteToDataSourceV2Exec.scala:92)
    at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:131)
    at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
    at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:296)
    at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3384)
    at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2783)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:3365)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3365)
    at org.apache.spark.sql.Dataset.collect(Dataset.scala:2783)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$15(MicroBatchExecution.scala:537)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$14(MicroBatchExecution.scala:533)
    at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:351)
    at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:349)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:532)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:198)
    at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
    at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:351)
    at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:349)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:166)
    at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279)
    ... 1 more
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 8, localhost, executor driver): java.lang.ClassCastException: java.lang.String cannot be cast to org.apache.spark.unsafe.types.UTF8String
    at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getUTF8String(rows.scala:46)
    at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getUTF8String$(rows.scala:46)
    at org.apache.spark.sql.catalyst.expressions.GenericInternalRow.getUTF8String(rows.scala:195)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:619)
    at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
    at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$2(WriteToDataSourceV2Exec.scala:117)
    at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
    at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:116)
    at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.$anonfun$doExecute$2(WriteToDataSourceV2Exec.scala:67)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:405)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:1887)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1875)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1874)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:407)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.doExecute(WriteToDataSourceV2Exec.scala:64)
    ... 34 more
Caused by: java.lang.ClassCastException: java.lang.String cannot be cast to org.apache.spark.unsafe.types.UTF8String
    at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getUTF8String(rows.scala:46)
    at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getUTF8String$(rows.scala:46)
    at org.apache.spark.sql.catalyst.expressions.GenericInternalRow.getUTF8String(rows.scala:195)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:619)
    at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
    at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$2(WriteToDataSourceV2Exec.scala:117)
    at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
    at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:116)
    at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.$anonfun$doExecute$2(WriteToDataSourceV2Exec.scala:67)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:405)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

I am sending the JSON records using mosquitto broker and they look like this:

mosquitto_pub -m '{"eventDate": "2020-11-11T15:17:00.000+0200"}' -t "temp"

回答1:


It seems that every strings coming from Bahir stream source provider raise this error. For instance the following code also raises this error :

spark.readStream
  .format("org.apache.bahir.sql.streaming.mqtt.MQTTStreamSourceProvider")
  .option("topic", topic).option("persistence", "memory")
  .load(brokerUrl)
  .select("topic")
  .writeStream
  .format("console")
  .start()

It looks like Spark does not recognize strings coming from Bahir, maybe some kind of weird string class version issue. I've tried the following actions to make the code work:

  • setup java version to 8
  • upgrade spark version from 2.4.0 to 2.4.7
  • setup scala version to 2.11.12
  • use decode function with all possible encoding combinations instead of .cast(StringType) to transform column "payload" to String
  • use substring function on column "payload" to recreate a compatible String.

Finally, I got working code by recreating the string using constructor and dataset:

val lines = spark.readStream
  .format("org.apache.bahir.sql.streaming.mqtt.MQTTStreamSourceProvider")
  .option("topic", topic).option("persistence", "memory")
  .load(brokerUrl)
  .select("payload")
  .as[Array[Byte]]
  .map(payload => new String(payload))
  .toDF("payload")

This solution is rather ugly but at least it works.

I believe that there is nothing wrong with the code provided in the question and I suspect a bug on Bahir or Spark side preventing Spark to handle String from Bahir source.



来源:https://stackoverflow.com/questions/64825099/apache-spark-sql-get-json-object-java-lang-string-cannot-be-cast-to-org-apache-s

易学教程内所有资源均来自网络或用户发布的内容,如有违反法律规定的内容欢迎反馈
该文章没有解决你所遇到的问题?点击提问,说说你的问题,让更多的人一起探讨吧!