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apache-spark - 排除 CDH 中 spark-core 的依赖性

问题描述

我正在使用结构化 Spark Streaming 写入来自 Kafka 的 HBase 数据。

我的集群分布是：Hadoop 3.0.0-cdh6.2.0，我使用的是 Spark 2.4.0

我的代码如下：

val df = spark
 .readStream
 .format("kafka")
 .option("kafka.bootstrap.servers", bootstrapServers)
 .option("subscribe", topic)
 .option("failOnDataLoss", false)
 .load()
 .selectExpr("CAST(key AS STRING)" , "CAST(value AS STRING)")
 .as(Encoders.STRING)

df.writeStream
  .foreachBatch { (batchDF: Dataset[Row], batchId: Long) =>
     batchDF.write
           .options(Map(HBaseTableCatalog.tableCatalog->catalog, HBaseTableCatalog.newTable -> "6"))
          .format("org.apache.spark.sql.execution.datasources.hbase").save()
     }
     .option("checkpointLocation", checkpointDirectory)
     .start()
     .awaitTermination()

HBaseTableCatalog 使用 json4s-jackson_2.11 库。这个库包含在 Spark Core 中，但版本不好，这会产生冲突......

为了解决这个问题，我在 spark 核心中排除了 json4s-jackson_2.11 库，并在 pom 中添加了一个降级版本：

<dependency>
  <groupId>org.apache.spark</groupId>
  <artifactId>spark-core_2.11</artifactId>
  <version>2.4.0-cdh6.2.0</version>
  <exclusions>
    <exclusion>
      <groupId>org.json4s</groupId>
      <artifactId>json4s-jackson_2.11</artifactId>
    </exclusion>
  </exclusions>
</dependency>
<dependency>
  <groupId>org.json4s</groupId>
  <artifactId>json4s-jackson_2.11</artifactId>
  <version>3.2.11</version>
</dependency>

当我在我的语言环境机器上执行代码时，它运行良好，但问题是当我在 cloudera 集群中提交它时，我遇到了库冲突的第一个错误：

Caused by: java.lang.NoSuchMethodError: org.json4s.jackson.JsonMethods$.parse(Lorg/json4s/JsonInput;Z)Lorg/json4s/JsonAST$JValue;
        at org.apache.spark.sql.execution.datasources.hbase.HBaseTableCatalog$.apply(HBaseTableCatalog.scala:257)
        at org.apache.spark.sql.execution.datasources.hbase.HBaseRelation.<init>(HBaseRelation.scala:80)
        at org.apache.spark.sql.execution.datasources.hbase.DefaultSource.createRelation(HBaseRelation.scala:59)
        at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
        at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
        at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
        at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
        at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
        at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
        at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
        at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
        at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:668)
        at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:668)
        at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
        at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
        at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:668)
        at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:276)
        at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:270)
        at com.App$$anonfun$main$1.apply(App.scala:129)
        at com.App$$anonfun$main$1.apply(App.scala:126)

我知道集群有自己的 hadoop 和 spark 库并且它使用它们，所以，在 spark 提交中，我将 confs spark.driver.userClassPathFirst 和 spark.executor.userClassPathFirst 设为 true，但我有另一个错误和我不明白：

Exception in thread "main" java.lang.ExceptionInInitializerError
        at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$.<init>(YarnSparkHadoopUtil.scala:48)
        at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$.<clinit>(YarnSparkHadoopUtil.scala)
        at org.apache.spark.deploy.yarn.Client$$anonfun$1.apply$mcJ$sp(Client.scala:83)
        at org.apache.spark.deploy.yarn.Client$$anonfun$1.apply(Client.scala:83)
        at org.apache.spark.deploy.yarn.Client$$anonfun$1.apply(Client.scala:83)
        at scala.Option.getOrElse(Option.scala:121)
        at org.apache.spark.deploy.yarn.Client.<init>(Client.scala:82)
        at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1603)
        at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:851)
        at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
        at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:195)
        at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
        at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:926)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:935)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.ClassCastException: org.apache.hadoop.yarn.api.records.impl.pb.PriorityPBImpl cannot be cast to org.apache.hadoop.yarn.api.records.Priority
        at org.apache.hadoop.yarn.api.records.Priority.newInstance(Priority.java:39)
        at org.apache.hadoop.yarn.api.records.Priority.<clinit>(Priority.java:34)
        ... 15 more

最后，我想要的是使用我的 pom 中的 json4s-jackson_2.11 而不是 Spark 核心中的那个来制作 Spark

标签： apache-sparkhadoopapache-kafkahbasecloudera-cdh

解决方案

为了解决这个问题，不要使用spark.driver.userClassPathFirstandspark.executor.userClassPathFirst而是使用spark.driver.extraClassPathand spark.executor.extraClassPath。

官方文档中的定义：“附加到驱动程序类路径的额外类路径条目。”

  • “prepend”，例如，放在 Spark 的核心类路径之前。

例子 ：

--conf spark.driver.extraClassPath=C:\Users\Khalid\Documents\Projects\libs\jackson-annotations-2.6.0.jar;C:\Users\Khalid\Documents\Projects\libs\jackson-core-2.6 .0.jar;C:\Users\Khalid\Documents\Projects\libs\jackson-databind-2.6.0.jar

这解决了我的问题（我想使用的 Jackson 版本与正在使用的一个 spark 版本之间的冲突）。

希望能帮助到你。

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