Java + Spark SQL + Hive + Maven简单实现和异常问题

ゞ浴缸里的玫瑰 2022-06-17 12:13 278阅读 0赞

# 一. 前期准备 #

#### 1.linux搭建Java和Scala环境搭建 ####

#### 2. linux搭建hadoop+spark+hive分布式集群 ####

hadoop分布式集群搭建：[hadoop分布式集群搭建][hadoop]

spark分布式集群搭建:[spark分布式集群搭建][spark]

hive分布式集群搭建：待完善

# 二.项目代码实现 #

#### 1 需求 ####

通过Spark Sql 查询Hive数据库数据

数据库：bi\_ods;

表：owms\_m\_locator

#### 2 maven 项目搭建 ####

新增一个Mave project工程

![1240][]

maven project工程

#### 3 实现代码 ####

package com.lm.hive.SparkHive;
    
    import org.apache.spark.SparkConf;
    import org.apache.spark.api.java.JavaSparkContext;
    import org.apache.spark.sql.SQLContext;
    import org.apache.spark.sql.hive.HiveContext;
    
    /**
     * Spark sql获取Hive数据
     *
     */
    public class App 
    {
        public static void main( String[] args ) 
        {
            SparkConf sparkConf = new SparkConf().setAppName("SparkHive").setMaster("local[2]");
            JavaSparkContext sc = new JavaSparkContext(sparkConf);
            
            //不要使用SQLContext,部署异常找不到数据库和表
            HiveContext hiveContext = new HiveContext(sc);
            SQLContext sqlContext = new SQLContext(sc);
            //查询表前10条数据
            hiveContext.sql("select * from bi_ods.owms_m_locator limit 10").show();
            
            sc.stop();
        }
    }

## 4. pom.xml文件 ##

<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.lm.hive</groupId>
    	<artifactId>SparkHive</artifactId>
    	<version>0.0.1-SNAPSHOT</version>
    	<packaging>jar</packaging>
    
    	<name>SparkHive</name>
    	<url>http://maven.apache.org</url>
    
    	<properties>
    		<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    	</properties>
    
    	<dependencies>
    		<dependency>
    			<groupId>junit</groupId>
    			<artifactId>junit</artifactId>
    			<version>3.8.1</version>
    			<scope>test</scope>
    		</dependency>
    		<dependency>
    			<groupId>mysql</groupId>
    			<artifactId>mysql-connector-java</artifactId>
    			<version>5.1.39</version>
    		</dependency>
    
    		<dependency>
    			<groupId>org.slf4j</groupId>
    			<artifactId>slf4j-log4j12</artifactId>
    			<version>1.7.22</version>
    		</dependency>
    		<dependency>
    			<groupId>org.apache.hadoop</groupId>
    			<artifactId>hadoop-client</artifactId>
    			<version>2.6.4</version>
    		</dependency>
    
    		<dependency>
    			<groupId>org.apache.spark</groupId>
    			<artifactId>spark-sql_2.10</artifactId>
    			<version>1.6.0</version>
    		</dependency>
    		<dependency>
    			<groupId>org.apache.spark</groupId>
    			<artifactId>spark-hive_2.10</artifactId>
    			<version>1.6.0</version>
    		</dependency>
    
    		<dependency>
    			<groupId>org.apache.spark</groupId>
    			<artifactId>spark-streaming_2.10</artifactId>
    			<version>1.6.0</version>
    			<exclusions>
    				<exclusion>
    					<artifactId>slf4j-log4j12</artifactId>
    					<groupId>org.slf4j</groupId>
    				</exclusion>
    			</exclusions>
    		</dependency>
    		<dependency>
    			<groupId>org.apache.spark</groupId>
    			<artifactId>spark-core_2.10</artifactId>
    			<version>1.6.0</version>
    		</dependency>
    
    
    		
    		<dependency>
    			<groupId>org.apache.hive</groupId>
    			<artifactId>hive-jdbc</artifactId>
    			<version>2.1.1</version>
    		</dependency>
    
    		
    		<dependency>
    			<groupId>org.apache.hive</groupId>
    			<artifactId>hive-exec</artifactId>
    			<version>2.1.1</version>
    		</dependency>
    
    	</dependencies>
    	<build>
    
    		<plugins>
    			<plugin>
    				<groupId>org.apache.maven.plugins</groupId>
    				<artifactId>maven-shade-plugin</artifactId>
    				<executions>
    					<execution>
    						<phase>package</phase>
    						<goals>
    							<goal>shade</goal>
    						</goals>
    						<configuration>
    							<shadedArtifactAttached>true</shadedArtifactAttached>
    							<shadedClassifierName>allinone</shadedClassifierName>
    							<artifactSet>
    								<includes>
    									<include>*:*</include>
    								</includes>
    							</artifactSet>
    							<filters>
    								<filter>
    									<artifact>*:*</artifact>
    									<excludes>
    										<exclude>META-INF/*.SF</exclude>
    										<exclude>META-INF/*.DSA</exclude>
    										<exclude>META-INF/*.RSA</exclude>
    									</excludes>
    								</filter>
    							</filters>
    							<transformers>
    								<transformer
    									implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
    									<resource>reference.conf</resource>
    								</transformer>
    								<transformer
    									implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
    									<resource>META-INF/spring.handlers</resource>
    								</transformer>
    								<transformer
    									implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
    									<resource>META-INF/spring.schemas</resource>
    								</transformer>
    								<transformer
    									implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
    									<manifestEntries>
    										<Main-Class></Main-Class>
    									</manifestEntries>
    								</transformer>
    							</transformers>
    						</configuration>
    					</execution>
    				</executions>
    			</plugin>
    		</plugins>
    	</build>
    </project>

# 三. 项目部署 #

#### 1 maven项目编译成jar包 ####

本文编译成 SparkHive-0.0.1-SNAPSHOT-allinone.jar

#### 2 上传jar包至linux服务器 ####

通过rz命令上传

#### 3 通过spark-submit命令运行jar包 ####

命令：

sh bin/spark-submit --class com.lm.hive.SparkHive.App --master yarn  --files /home/winit/spark-1.6.0/conf/hive-site.xml  java_jar/SparkHive-0.0.1-SNAPSHOT-allinone.jar

结果：

![1240 1][]

运行结果

# 四.异常问题 #

在网上搜索，很多是通过SQLContext实例去查询Hive数据，当本人使用时，出现以下异常

1. Exception in thread "main" org.apache.spark.sql.AnalysisException: Table not found: \`bi\_ods\`.\`owms\_m\_locator\`;

![1240 2][]

SQLContext查询异常

解决：

SQLContext sqlContext = new SQLContext(sc);

替换为：

HiveContext hiveContext = new HiveContext(sc);

2. Exception in thread "main" java.lang.SecurityException: class "javax.servlet.FilterRegistration"'s signer information does not match signer information of other classes in the same package

解决：

javax.servlet相关包重复导入引起的

hadoop-client或hadoop-common排除java.servelt等包

<dependency>
    			<groupId>org.apache.hadoop</groupId>
    			<artifactId>hadoop-client</artifactId>
    			<version>2.6.4</version>
    			<exclusions>
    				<exclusion>
    					<groupId>javax.servlet</groupId>
    					<artifactId>*</artifactId>
    				</exclusion>
    			</exclusions>
    		</dependency>

# 五. SQLContext和HiveContext区别和联系 #

Spark SQL程序的主入口是SQLContext类或它的子类。创建一个基本的SQLContext，你只需要SparkContext

除了基本的SQLContext，也可以创建HiveContext。SQLContext和HiveContext区别与联系为：

SQLContext现在只支持SQL语法解析器（SQL-92语法）

HiveContext现在支持SQL语法解析器和HiveSQL语法解析器，默认为HiveSQL语法解析器，用户可以通过配置切换成SQL语法解析器，来运行HiveSQL不支持的语法。

使用HiveContext可以使用Hive的UDF，读写Hive表数据等Hive操作。SQLContext不可以对Hive进行操作。

Spark SQL未来的版本会不断丰富SQLContext的功能，做到SQLContext和HiveContext的功能容和，最终可能两者会统一成一个Context

HiveContext包装了Hive的依赖包，把HiveContext单独拿出来，可以在部署基本的Spark的时候就不需要Hive的依赖包，需要使用HiveContext时再把Hive的各种依赖包加进来。

SQL的解析器可以通过配置spark.sql.dialect参数进行配置。在SQLContext中只能使用Spark SQL提供的”sql“解析器。在HiveContext中默认解析器为”hiveql“，也支持”sql“解析器。

详情见：[SQLContext和HiveContext区别与联系][SQLContext_HiveContext]

代码下载地址：[Java + Spark SQL + Hive + Maven简单实例代码][Java _ Spark SQL _ Hive _ Maven]

[hadoop]: http://blog.csdn.net/a123demi/article/details/70652959
[spark]: http://blog.csdn.net/a123demi/article/details/70653540
[1240]: /images/20220617/5f2bc4a30cec49c3bee09503bee18e84.png
[1240 1]: /images/20220617/d96276ee0000471884c4ed952f8a1dda.png
[1240 2]: /images/20220617/a36e7e9dff13429791e0b6b4b5f9243b.png
[SQLContext_HiveContext]: http://xn--jlq582ax31c.xn--fiqs8s/m/?post=115
[Java _ Spark SQL _ Hive _ Maven]: http://download.csdn.net/detail/a123demi/9825445