spring-boot集成spark并使⽤spark-sql ⾸先添加相关依赖：
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="/POM/4.0.0" xmlns:xsi="/2001/XMLSchema-instance"
xsi:schemaLocation="/POM/4.0.0 /xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>1.5.6.RELEASE</version>
<relativePath />
</parent>
<groupId&d</groupId>
<artifactId>spark-example</artifactId>
<version>1.0-SNAPSHOT</version>
<name>spark-example</name>
<!-- FIXME change it to the project's website -->
<url>ample</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
&porting.outputEncoding>UTF-8</porting.outputEncoding>
<java.version>1.8</java.version>
<scala.version>2.10.3</scala.version>
<mavenpiler.source>1.8</mavenpiler.source>
springboot原理视频<mavenpiler.target>1.8</mavenpiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter</artifactId>
<version>1.5.6.RELEASE</version>
<exclusions>
<exclusion>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-logging</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.6.1</version>
<scope>provided</scope>
<exclusions>
<exclusion>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
</exclusion>
<exclusion>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.10</artifactId>
<version>1.6.1</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_2.10</artifactId>
<version>1.6.1</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
<scope>provided</scope>
</dependency>
<!-- yarn-cluster模式 -->
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.22</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
<version>1.5.6.RELEASE</version>
</dependency>
</dependencies>
<configuration>
<keepDependenciesWithProvidedScope>false</keepDependenciesWithProvidedScope>
<createDependencyReducedPom>false</createDependencyReducedPom>
<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.source.AppendingTransformer">
<resource>META-INF/spring.handlers</resource>
</transformer>
<transformer
implementation="org.springframework.boot.maven.PropertiesMergingResourceTransformer">                            <resource>META-INF/spring.factories</resource>
</transformer>
<transformer
implementation="org.apache.maven.source.AppendingTransformer">
<resource>META-INF/spring.schemas</resource>
</transformer>
<transformer
implementation="org.apache.maven.source.ServicesResourceTransformer" />                        <transformer
implementation="org.apache.maven.source.ManifestResourceTransformer">                            <mainClass&d.StartApplication</mainClass>
</transformer>
</transformers>
</configuration>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
需要注意的是依赖中排除掉的⽇志模块，以及特殊的打包⽅式
定义配置类:
SparkContextBean.class
@Configuration
public class SparkContextBean {
private String appName = "sparkExp";
private String master = "local";
@Bean
@ConditionalOnMissingBean(SparkConf.class)
public SparkConf sparkConf() throws Exception {
SparkConf conf = new SparkConf().setAppName(appName).setMaster(master);
return conf;
}
@Bean
@ConditionalOnMissingBean
public JavaSparkContext javaSparkContext() throws Exception {
return new JavaSparkContext(sparkConf());
}
@Bean
@ConditionalOnMissingBean
public HiveContext hiveContext() throws Exception {
return new HiveContext(javaSparkContext());
}
......
}
启动类：
StartApplication.class
@SpringBootApplication
public class StartApplication implements CommandLineRunner {
@Autowired
private HiveContext hc;
public static void main(String[] args) {
SpringApplication.run(StartApplication.class, args);
}
@Override
public void args) throws Exception {
DataFrame df = hc.sql("select count(1) from LCS_DB.STAFF_INFO");        List<Long> result = df.javaRDD().map((Function<Row, Long>) row -> {            Long(0);
}).collect();
result.stream().forEach(System.out::println);
}
}
执⾏⽅式：
spark-submit \
--d.StartApplication  \
--executor-memory 4G \
--num-executors 8 \
--master yarn-client \
/data/cord/spark-example-1.0-SNAPSHOT.jar
参考链接：

版权声明：本站内容均来自互联网，仅供演示用，请勿用于商业和其他非法用途。如果侵犯了您的权益请与我们联系QQ:729038198，我们将在24小时内删除。