美文网首页
Ambari HDP 下 SPARK2 与 Phoenix 整合

Ambari HDP 下 SPARK2 与 Phoenix 整合

作者: 跟着大数据和AI去旅行 | 来源:发表于2020-02-20 17:53 被阅读0次

    1、环境说明

    操作系统 CentOS Linux release 7.4.1708 (Core)
    Ambari 2.6.x
    HDP 2.6.3.0
    Spark 2.x
    Phoenix 4.10.0-HBase-1.2

    2、条件

    1. HBase 安装完成

    2. Phoenix 已经启用,Ambari界面如下所示:

    3. Spark 2安装完成

    3、Spark2 与 Phoenix整合

    Phoenix 官网整合教程: http://phoenix.apache.org/phoenix_spark.html

    步骤:

    1. 进入 Ambari Spark2 配置界面

    2. 找到自定义 spark2-defaults并添加如下配置项:

      spark.driver.extraClassPath=/usr/hdp/current/phoenix-client/phoenix-4.10.0-HBase-1.2-client.jar
      spark.executor.extraClassPath=/usr/hdp/current/phoenix-client/phoenix-4.10.0-HBase-1.2-client.jar
      
      mark

    4、Yarn HA 问题

    如果配置了Yarn HA, 则需要修改 Yarn HA 配置,否则spark-submit提交任务会报如下错误:

    Exception in thread "main" java.lang.IllegalAccessError: tried to access method org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider.getProxyInternal()Ljava/lang/Object; from class org.apache.hadoop.yarn.client.RequestHedgingRMFailoverProxyProvider
            at org.apache.hadoop.yarn.client.RequestHedgingRMFailoverProxyProvider.init(RequestHedgingRMFailoverProxyProvider.java:75)
            at org.apache.hadoop.yarn.client.RMProxy.createRMFailoverProxyProvider(RMProxy.java:163)
            at org.apache.hadoop.yarn.client.RMProxy.createRMProxy(RMProxy.java:94)
            at org.apache.hadoop.yarn.client.ClientRMProxy.createRMProxy(ClientRMProxy.java:72)
            at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.serviceStart(YarnClientImpl.java:187)
            at org.apache.hadoop.service.AbstractService.start(AbstractService.java:193)
            at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:153)
            at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:56)
            at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173)
            at org.apache.spark.SparkContext.<init>(SparkContext.scala:509)
            at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2516)
            at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:922)
            at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:914)
            at scala.Option.getOrElse(Option.scala:121)
            at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:914)
            at cn.spark.sxt.SparkOnPhoenix$.main(SparkOnPhoenix.scala:13)
            at cn.spark.sxt.SparkOnPhoenix.main(SparkOnPhoenix.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.i
    

    修改Yarn HA配置:

    原来的配置:

    yarn.client.failover-proxy-provider=org.apache.hadoop.yarn.client.RequestHedgingRMFailoverProxyProvider
    

    改为现在的配置

    yarn.client.failover-proxy-provider=org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider
    

    如果没有配置 Yarn HA, 则不需要进行此步配置


    欢迎关注微信公众号

    相关文章

      网友评论

          本文标题:Ambari HDP 下 SPARK2 与 Phoenix 整合

          本文链接:https://www.haomeiwen.com/subject/dbtfqhtx.html