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springboot集成spark并使用spark-sql的方法

发布时间:2022-02-19 17:00:58 来源:亿速云 阅读:1201 作者:iii 栏目:开发技术

这篇文章主要介绍“springboot集成spark并使用spark-sql的方法”的相关知识,小编通过实际案例向大家展示操作过程,操作方法简单快捷,实用性强,希望这篇“springboot集成spark并使用spark-sql的方法”文章能帮助大家解决问题。

首先添加相关依赖:

<?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>
  <parent>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-parent</artifactId>
    <version>1.5.6.RELEASE</version>
    <relativePath />
  </parent>
  <groupId>com.cord</groupId>
  <artifactId>spark-example</artifactId>
  <version>1.0-SNAPSHOT</version>
  <name>spark-example</name>
  <!-- FIXME change it to the project's website -->
  <url>http://www.example.com</url>
  <properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
    <java.version>1.8</java.version>
    <scala.version>2.10.3</scala.version>
    <maven.compiler.source>1.8</maven.compiler.source>
    <maven.compiler.target>1.8</maven.compiler.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.plugins.shade.resource.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.plugins.shade.resource.AppendingTransformer">
                            <resource>META-INF/spring.schemas</resource>
                        </transformer>
                        <transformer
                                implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
                        <transformer
                                implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                            <mainClass>com.cord.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 run(String... 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 -> {
            return row.getLong(0);
        }).collect();
        result.stream().forEach(System.out::println);
}

执行方式:

spark-submit \
    --class com.cord.StartApplication  \
    --executor-memory 4G \
    --num-executors 8 \
    --master yarn-client \
/data/cord/spark-example-1.0-SNAPSHOT.jar

关于“springboot集成spark并使用spark-sql的方法”的内容就介绍到这里了,感谢大家的阅读。如果想了解更多行业相关的知识,可以关注亿速云行业资讯频道,小编每天都会为大家更新不同的知识点。

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