您好,登錄后才能下訂單哦!
這篇文章主要介紹“springboot集成spark并使用spark-sql的方法”的相關知識,小編通過實際案例向大家展示操作過程,操作方法簡單快捷,實用性強,希望這篇“springboot集成spark并使用spark-sql的方法”文章能幫助大家解決問題。
首先添加相關依賴:
<?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>
需要注意的是依賴中排除掉的日志模塊,以及特殊的打包方式
定義配置類:
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()); } ...... }
啟動類:
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); }
執行方式:
spark-submit \ --class com.cord.StartApplication \ --executor-memory 4G \ --num-executors 8 \ --master yarn-client \ /data/cord/spark-example-1.0-SNAPSHOT.jar
關于“springboot集成spark并使用spark-sql的方法”的內容就介紹到這里了,感謝大家的閱讀。如果想了解更多行業相關的知識,可以關注億速云行業資訊頻道,小編每天都會為大家更新不同的知識點。
免責聲明:本站發布的內容(圖片、視頻和文字)以原創、轉載和分享為主,文章觀點不代表本網站立場,如果涉及侵權請聯系站長郵箱:is@yisu.com進行舉報,并提供相關證據,一經查實,將立刻刪除涉嫌侵權內容。