Spark SQL的简单java api应用

1、创建IDEA的Maven工程

2、引入依赖
     <?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.motoon</groupId>
<artifactId>SparkSql_Demo</artifactId>
<version>1.0</version>

<properties>
<maven.compiler.source>1.7</maven.compiler.source>
<maven.compiler.target>1.7</maven.compiler.target>
<encoding>UTF-8</encoding>
<scala.version>2.10.6</scala.version>
<scala.compat.version>2.10</scala.compat.version>
</properties>
<dependencies>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.5.2</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.10</artifactId>
<version>1.5.2</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.10</artifactId>
<version>1.5.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.6.2</version>
</dependency>

<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.39</version>
</dependency>
</dependencies>

<build>
<sourceDirectory>src/main/scala</sourceDirectory>
<testSourceDirectory>src/test/scala</testSourceDirectory>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.2.0</version>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
</goals>
<configuration>
<args>
<arg>-make:transitive</arg>
<arg>-dependencyfile</arg>
<arg>${project.build.directory}/.scala_dependencies</arg>
</args>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<version>2.18.1</version>
<configuration>

ee76
<useFile>false</useFile>
<disableXmlReport>true</disableXmlReport>
<includes>
<include>**/*Test.*</include>
<include>**/*Suite.*</include>
</includes>
</configuration>
</plugin>

<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>2.3</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>

</project>
3、编写测试类
      package com.motoon.sparksql

import org.apache.spark.sql.types.{DataTypes, StructType}
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.{Row, SQLContext, functions}

object TestSparkSql {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("TestSparkSql").setMaster("local");
val sc = new SparkContext(conf)
val sqlContext = new SQLContext(sc)
val linesRDD = sc.textFile("hdfs://192.168.61.138:9000/test/people.txt")
val rowRDD = linesRDD.map(line => {
val splits = line.split(" ")
Row(splits(0).trim.toInt,splits(1).trim,splits(2).trim.toInt)
})
val structType = StructType(Array(
DataTypes.createStructField("id",DataTypes.IntegerType,true),
DataTypes.createStructField("name",DataTypes.StringType,true),
DataTypes.createStructField("age",DataTypes.IntegerType,true)
))

val df = sqlContext.createDataFrame(rowRDD,structType)
df.registerTempTable("people")
df.show()
/**
* 接下来对df中的数据进行查询
* 第一个查询年龄的最大值,平均值
* height的总身高
* */
sqlContext.sql("select * from people").show()
sqlContext.sql("select max(age) from people").show()
sc.stop()
}
}