spark3访问低版本hive填坑记_神云瑟瑟的博客-程序员秘密

技术标签： hive  spark  大数据  

目录

 

一、背景

二、代码

三、异常信息

四、原因分析

五、问题处理

1、开发环境调试处理

2、线上环境部署

一、背景

现有的大数据平台版本

组件 版本
hadoop 2.7.3
hive 1.2.1

因业务需要引入spark组件，引入的为最新版本spark3.0.1。

业务上做测试，将Dataframe数据写入hive中。

二、代码

scala代码

package com.shenyun.scala.exchange

import org.apache.spark.sql.types.{StringType, StructField, StructType}
import org.apache.spark.sql.{Row, SparkSession}

object DfToHive {
  def main(args: Array[String]){
    System.setProperty("HADOOP_USER_NAME","root");
    //初始化参数
    val builder = SparkSession.builder()
    //本地模式需要设置该行
    //也可以VM OPTION设置 :-Dspark.master=local
    if(args!=null&&args.size>0&&args(0).equals("dev")){
      builder.master("local[2]")
    }
    builder.appName(this.getClass.getName)
    //启用hive
    builder.enableHiveSupport()
    //设置工作目录,正式环境可以不用设置
    //    builder.config("spark.sql.warehouse.dir", "D:\\tmp\\spark")
    val spark = builder.getOrCreate();

    import spark.implicits._

//    val studentRDD
//      studentRDD=spark.sparkContext.textFile("file:///D:\\workplace\\scala\\scala-spark\\src\\main\\resources\\exchange\\student.data")
    val studentRDD = spark.sparkContext.textFile("/user/luoyong/data/student.data")
    val head = studentRDD.first()
    val studentRDDData = studentRDD
      .filter(row => row!=head)
      .map(x => x.split("\\|"))
      .map(x => Row(x(0),x(1),x(2),x(3)))

    val schema=StructType(Array(
      StructField ("id", StringType, nullable = true)
      ,StructField ("name", StringType, nullable = true)
      ,StructField ("phone", StringType, nullable = true)
      ,StructField ("email", StringType, nullable = true))
    )

    val studentDf=spark.createDataFrame(studentRDDData,schema)
    studentDf.createOrReplaceTempView("student_tmp");
    spark.sql("insert into luoyong.student_ly select id,name,phone,email from student_tmp");
    //关闭
    spark.stop()
  }
}

pom.xml，

注意这种引用方式访问高版本的hive应该是没有问题的（为测试，理论应该是的）

         <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.12</artifactId>
            <version>3.0.1</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-hive_2.12</artifactId>
            <version>3.0.1</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-hive-thriftserver_2.12</artifactId>
            <version>3.0.1</version>
            <scope>provided</scope>
        </dependency>

三、异常信息

WARN metadata.Hive: Failed to register all functions.
org.apache.hadoop.hive.ql.metadata.HiveException: org.apache.thrift.TApplicationException: Invalid method name: 'get_all_functions'

20/12/17 11:19:56 INFO hive.metastore: Connected to metastore.
20/12/17 11:19:56 WARN metadata.Hive: Failed to register all functions.
org.apache.hadoop.hive.ql.metadata.HiveException: org.apache.thrift.TApplicationException: Invalid method name: 'get_all_functions'
	at org.apache.hadoop.hive.ql.metadata.Hive.getAllFunctions(Hive.java:3897)
	at org.apache.hadoop.hive.ql.metadata.Hive.reloadFunctions(Hive.java:248)
	at org.apache.hadoop.hive.ql.metadata.Hive.registerAllFunctionsOnce(Hive.java:231)
	at org.apache.hadoop.hive.ql.metadata.Hive.<init>(Hive.java:388)
	at org.apache.hadoop.hive.ql.metadata.Hive.create(Hive.java:332)
	at org.apache.hadoop.hive.ql.metadata.Hive.getInternal(Hive.java:312)
	at org.apache.hadoop.hive.ql.metadata.Hive.get(Hive.java:288)
	at org.apache.spark.sql.hive.client.HiveClientImpl.client(HiveClientImpl.scala:260)
	at org.apache.spark.sql.hive.client.HiveClientImpl.$anonfun$withHiveState$1(HiveClientImpl.scala:286)
	at org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:227)
	at org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:226)
	at org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:276)
	at org.apache.spark.sql.hive.client.HiveClientImpl.databaseExists(HiveClientImpl.scala:389)
	at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$databaseExists$1(HiveExternalCatalog.scala:225)
	at scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23)
	at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:103)
	at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:225)
	at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:137)
	at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:127)
	at org.apache.spark.sql.internal.SharedState.globalTempViewManager$lzycompute(SharedState.scala:157)
	at org.apache.spark.sql.internal.SharedState.globalTempViewManager(SharedState.scala:155)
	at org.apache.spark.sql.hive.HiveSessionStateBuilder.$anonfun$catalog$2(HiveSessionStateBuilder.scala:60)
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.globalTempViewManager$lzycompute(SessionCatalog.scala:93)
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.globalTempViewManager(SessionCatalog.scala:93)
	at org.apache.spark.sql.catalyst.catalog.SessionCatalog.lookupGlobalTempView(SessionCatalog.scala:789)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveTempViews$.lookupTempView(Analyzer.scala:858)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveTempViews$$anonfun$apply$7.applyOrElse(Analyzer.scala:840)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveTempViews$$anonfun$apply$7.applyOrElse(Analyzer.scala:836)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUp$5(AnalysisHelper.scala:94)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:72)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUp$1(AnalysisHelper.scala:94)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:194)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUp(AnalysisHelper.scala:86)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUp$(AnalysisHelper.scala:84)
	at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsUp(LogicalPlan.scala:29)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveTempViews$.apply(Analyzer.scala:836)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:962)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:934)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:149)
	at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
	at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
	at scala.collection.immutable.List.foldLeft(List.scala:89)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:146)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:138)
	at scala.collection.immutable.List.foreach(List.scala:392)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:138)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:176)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:170)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:130)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:116)
	at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:116)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$executeAndCheck$1(Analyzer.scala:154)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:201)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:153)
	at org.apache.spark.sql.execution.QueryExecution.$anonfun$analyzed$1(QueryExecution.scala:68)
	at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
	at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:133)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
	at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:133)
	at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:68)
	at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:66)
	at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:58)
	at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
	at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:97)
	at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:607)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
	at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:602)
	at com.shenyun.scala.exchange.DfToHive$.main(DfToHive.scala:43)
	at com.shenyun.scala.exchange.DfToHiveTest$.main(DfToHiveTest.scala:9)
	at com.shenyun.scala.exchange.DfToHiveTest.main(DfToHiveTest.scala)
Caused by: org.apache.thrift.TApplicationException: Invalid method name: 'get_all_functions'
	at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:79)
	at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_all_functions(ThriftHiveMetastore.java:3845)
	at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_all_functions(ThriftHiveMetastore.java:3833)
	at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getAllFunctions(HiveMetaStoreClient.java:2399)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:173)
	at com.sun.proxy.$Proxy33.getAllFunctions(Unknown Source)
	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.invoke(Method.java:498)
	at org.apache.hadoop.hive.metastore.HiveMetaStoreClient$SynchronizedHandler.invoke(HiveMetaStoreClient.java:2336)
	at com.sun.proxy.$Proxy33.getAllFunctions(Unknown Source)
	at org.apache.hadoop.hive.ql.metadata.Hive.getAllFunctions(Hive.java:3894)
	... 71 more
20/12/17 11:19:56 WARN client.HiveClientImpl: HiveClient got thrift exception, destroying client and retrying (23 tries remaining)

四、原因分析

主要原因spark版本与hive版本的兼容问题。

spark3.0.1的默认编译的hive版本依赖的包为hive2.3.7

而集群中使用的hive版本为1.2.1

五、问题处理

1、开发环境调试处理

修改pom依赖低版本的hive jar

最终的pom依赖如下，注意scope是provided或者是test。是因为线上集群中在spark3的jars目录有这些包，或者放置。

<dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.12</artifactId>
            <version>3.0.1</version>
            <scope>provided</scope>
        </dependency>
        <!--        去掉依赖两个jar的依赖-->
        <!--        <dependency>-->
        <!--            <groupId>org.apache.spark</groupId>-->
        <!--            <artifactId>spark-hive_2.12</artifactId>-->
        <!--            <version>3.0.1</version>-->
        <!--            <scope>provided</scope>-->
        <!--        </dependency>-->
        <!--        <dependency>-->
        <!--            <groupId>org.apache.spark</groupId>-->
        <!--            <artifactId>spark-hive-thriftserver_2.12</artifactId>-->
        <!--            <version>3.0.1</version>-->
        <!--            <scope>provided</scope>-->
        <!--        </dependency>-->
        
        <!--        spark-hive_2.12，及spark-hive-thriftserver_2.12重新依赖，并排除对hive的传递依赖-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-hive_2.12</artifactId>
            <version>3.0.1</version>
            <scope>test</scope>
            <exclusions>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-common</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-exec</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-metastore</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-serde</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-shims</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-hive-thriftserver_2.12</artifactId>
            <version>3.0.1</version>
            <scope>test</scope>
            <exclusions>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-cli</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-jdbc</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.hive</groupId>
                    <artifactId>hive-beeline</artifactId>
                </exclusion>
            </exclusions>
        </dependency>

        <!--        hive版本降级为1.2.1，spark3原本依赖2.3.7-->
        <!--        spark-hive-thriftserver_2.12的传递依赖-->
        <dependency>
            <groupId>org.spark-project.hive</groupId>
            <artifactId>hive-cli</artifactId>
            <version>1.2.1.spark2</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.spark-project.hive</groupId>
            <artifactId>hive-jdbc</artifactId>
            <version>1.2.1.spark2</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.spark-project.hive</groupId>
            <artifactId>hive-beeline</artifactId>
            <version>1.2.1.spark2</version>
            <scope>test</scope>
        </dependency>

        <!--        spark-hive_2.12的传递依赖-->
        <dependency>
            <groupId>org.spark-project.hive</groupId>
            <artifactId>hive-common</artifactId>
            <version>1.2.1.spark2</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.spark-project.hive</groupId>
            <artifactId>hive-metastore</artifactId>
            <version>1.2.1.spark2</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.spark-project.hive</groupId>
            <artifactId>hive-exec</artifactId>
            <version>1.2.1.spark2</version>
            <scope>test</scope>
            <exclusions>
                <exclusion>
                    <groupId>org.apache.commons</groupId>
                    <artifactId>commons-lang3</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <!--        hive-exec中传递依赖的commons-lang3需要升级回3.9版本-->
        <dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-lang3</artifactId>
            <version>3.9</version>
            <scope>test</scope>
        </dependency>

2、线上环境部署

${SPARK3_HOME}/jars目录包替换。

将处理hive的包替换成一下版本的

包名 
groupId
 
artifactId
 version
hive-cli.1.2.1.spark2.jar 
org.spark-project.hive
 hive-cli 1.2.1.spark2
hive-jdbc.1.2.1.spark2.jar hive-jdbc
hive-beeline.1.2.1.spark2.jar hive-beeline
hive-common.1.2.1.spark2.jar hive-common
hive-metastore.1.2.1.spark2.jar hive-metastore
hive-exec.1.2.1.spark2.jar hive-exec
       

 
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本文链接：https://blog.csdn.net/shenyunsese/article/details/111299659

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