SparkSQL读取hive数据本地idea运行

灰太狼 2022-12-07 13:19 147阅读 0赞

### 环境准备： ###

hadoop版本：2.6.5
    spark版本：2.3.0
    hive版本：1.2.2
    master主机：192.168.100.201
    slave1主机：192.168.100.201

### **pom.xml依赖如下：** ###

<?xml version="1.0" encoding="UTF-8"?>
    <project xmlns="http://maven.apache.org/POM/4.0.0"
             xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
             xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
        <modelVersion>4.0.0</modelVersion>
    
        <groupId>com.spark</groupId>
        <artifactId>spark_practice</artifactId>
        <version>1.0-SNAPSHOT</version>
    
        <properties>
            <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
            <maven.compiler.source>1.8</maven.compiler.source>
            <maven.compiler.target>1.8</maven.compiler.target>
            <spark.core.version>2.3.0</spark.core.version>
        </properties>
    
        <dependencies>
            <dependency>
                <groupId>junit</groupId>
                <artifactId>junit</artifactId>
                <version>4.11</version>
                <scope>test</scope>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-core_2.11</artifactId>
                <version>${spark.core.version}</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-sql_2.11</artifactId>
                <version>${spark.core.version}</version>
            </dependency>
            <dependency>
                <groupId>mysql</groupId>
                <artifactId>mysql-connector-java</artifactId>
                <version>5.1.38</version>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-hive_2.11</artifactId>
                <version>2.3.0</version>
            </dependency>
        </dependencies>
    
    </project>

### **注意：**一定要将hive-site.xml配置文件放到工程resources目录下 ###

hive-site.xml配置如下：

<?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration> 
    
      <property>
        <name>hive.metastore.uris</name>
        <value>thrift://192.168.100.201:9083</value>
      </property>
      <property>
        <name>hive.server2.thrift.port</name>
        <value>10000</value>
      </property>  
        <property>       
            <name>javax.jdo.option.ConnectionURL</name>
            <value>jdbc:mysql://node01:3306/hive?createDatabaseIfNotExist=true</value>   
        </property>   
        <property>       
            <name>javax.jdo.option.ConnectionDriverName</name>
            <value>com.mysql.jdbc.Driver</value>   
        </property>   
        <property>       
            <name>javax.jdo.option.ConnectionUserName</name>
            <value>root</value>
        </property>
        <property>
            <name>javax.jdo.option.ConnectionPassword</name>
            <value>123456</value>
        </property>
        <property>
         <name>hive.zookeeper.quorum</name>
             <value>node01,node02,node03</value>
         </property>
    
         <property>
         <name>hbase.zookeeper.quorum</name>
             <value>node01,node02,node03</value>
         </property>
          
      <property>
        <name>hive.metastore.warehouse.dir</name>
        <value>/user/hive/warehouse</value>
      </property>
      
      <property>
        <name>fs.defaultFS</name>
        <value>hdfs://192.168.100.201:9000</value>
      </property>
      <property>
        <name>hive.metastore.schema.verification</name>
        <value>false</value>
      </property>
      <property>
        <name>datanucleus.autoCreateSchema</name>
        <value>true</value>
      </property>
      <property>
        <name>datanucleus.autoStartMechanism</name>
        <value>checked</value>
      </property>
    
    
    </configuration>

主类代码：

import org.apache.spark.sql.SparkSession
    
    object SparksqlTest2 {
      def main(args: Array[String]): Unit = {
    
        val spark: SparkSession = SparkSession
          .builder
          .master("local[*]")
          .appName("Java Spark Hive Example")
          .enableHiveSupport
          .getOrCreate
    
        spark.sql("show databases").show()
        spark.sql("show tables").show()
        spark.sql("select * from person").show()
        spark.stop()
      }
    }

### **前提：数据库访问的是default,表person中有三条数据。** ###

![20200916110545117.png][]

测试前先确保hadoop集群正常启动，然后需要启动hive的metastore服务。

./bin/hive --service metastore

运行，结果如下：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTExMTAzMDE_size_16_color_FFFFFF_t_70][]

--------------------

如果报错：

Exception in thread "main" org.apache.spark.sql.AnalysisException: java.lang.RuntimeException: java.io.IOException: (null) entry in command string: null chmod 0700 C:\Users\dell\AppData\Local\Temp\c530fb25-b267-4dd2-b24d-741727a6fbf3_resources;
    	at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:106)
    	at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:194)
    	at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:114)
    	at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:102)
    	at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:39)
    	at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog$lzycompute(HiveSessionStateBuilder.scala:54)
    	at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog(HiveSessionStateBuilder.scala:52)
    	at org.apache.spark.sql.hive.HiveSessionStateBuilder$$anon$1.<init>(HiveSessionStateBuilder.scala:69)
    	at org.apache.spark.sql.hive.HiveSessionStateBuilder.analyzer(HiveSessionStateBuilder.scala:69)
    	at org.apache.spark.sql.internal.BaseSessionStateBuilder$$anonfun$build$2.apply(BaseSessionStateBuilder.scala:293)
    	at org.apache.spark.sql.internal.BaseSessionStateBuilder$$anonfun$build$2.apply(BaseSessionStateBuilder.scala:293)
    	at org.apache.spark.sql.internal.SessionState.analyzer$lzycompute(SessionState.scala:79)
    	at org.apache.spark.sql.internal.SessionState.analyzer(SessionState.scala:79)
    	at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
    	at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
    	at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
    	at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:74)
    	at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:638)
    	at com.tongfang.learn.spark.hive.HiveTest.main(HiveTest.java:15)

解决：

1.下载hadoop windows binary包，链接：[https://github.com/steveloughran/winutils][https_github.com_steveloughran_winutils]

2.在启动类的运行参数中设置环境变量，HADOOP\_HOME=D:\\winutils\\hadoop-2.6.4，后面是hadoop windows 二进制包的目录。

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTExMTAzMDE_size_16_color_FFFFFF_t_70 1][]

[20200916110545117.png]: /images/20221123/2d0bc052d15a407b87bd0ab6cc00f89e.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTExMTAzMDE_size_16_color_FFFFFF_t_70]: /images/20221123/ced9af2314d54ec1ab43988c1cdac886.png
[https_github.com_steveloughran_winutils]: https://github.com/steveloughran/winutils
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTExMTAzMDE_size_16_color_FFFFFF_t_70 1]: /images/20221123/ee3d85166f414daaa607fc638a3f77b7.png