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這篇文章主要講解了“如何解決eclipse spark提交遠程任務(wù)異?!?,文中的講解內(nèi)容簡單清晰,易于學(xué)習(xí)與理解,下面請大家跟著小編的思路慢慢深入,一起來研究和學(xué)習(xí)“如何解決eclipse spark提交遠程任務(wù)異?!卑桑?/p>
java.lang.IllegalStateException: Library directory scala-2.11\jars' does not exist; make sure Spark is built.
package my.test; import java.io.IOException; import org.apache.spark.deploy.SparkSubmit; import com.huangyueran.spark.utils.Constant; public class Main { public static void main(String[] args) throws IOException { System.setProperty("HADOOP_USER_NAME", "hadoop"); System.setProperty("user.name", "hadoop"); //System.setProperty("HADOOP_CONF_DIR", "C:\\eclipse-workspace\\SparkDemo\\src\\main\\resources"); //System.setProperty("HADOOP_CONF_DIR", "C:\\my\\soft\\hadoop\\hadoop-2.8.5\\hadoop-2.8.5\\etc\\hadoop"); System.out.println("------------"+System.getenv("HADOOP_CONF_DIR")); System.out.println("------------"+System.getenv("HADOOP_HOME")); String appName = "wordCount-yarn-cluster"; String className = "my.test.WordCount"; String path = "C:\\eclipse-workspace\\SparkDemo\\target\\SparkDemo-1.0-SNAPSHOT.jar"; path = Constant.HDFS_FILE_PREX +"/user/zzm/SparkDemo-1.0-SNAPSHOT.jar"; String [] arg0=new String[]{ // "--jars",Constant.HDFS_FILE_PREX +"/user/zzm/spark-lib", "--master","yarn",//ip端口 "--deploy-mode","cluster", "--name",appName, "--class",className,//運行主類main //"--spark.yarn.archive",Constant.HDFS_FILE_PREX + "/user/zzm/spark-lib", "--executor-memory","2G", "--total-executor-cores","10", "--executor-cores","2", path,//在linux上的包 可改為hdfs上面的路徑 // "LR", "20180817111111", "66"//jar中的參數(shù),注意這里的參數(shù)寫法 }; SparkSubmit.main(arg0); } }
需要配置spark和hadoop得本地環(huán)境才能本地提交yarn cluster
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