我使用结构化的spark流来写入来自kafka的hbase数据。
我的集群发行版是：hadoop3.0.0-cdh6.2.0，我使用的是spark2.4.0
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\u 2.11库。此库包含在spark core中，但版本不正确，会产生冲突。。。
为了解决这个问题，我在spark core中排除了json4s-jacksonï2.11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>

当我在本地计算机中执行代码时，它工作得很好，但问题是，当我在cloudera集群中提交代码时，出现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，它也在使用它们，因此，在spark提交中，我将confs spark.driver.userclasspathfirst和spark.executor.userclasspathfirst设置为true，但我有另一个错误，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，在我的pom中使用json4s-jacksonè2.11而不是spark内核中的json4s-jacksonè2.11来生成spark