2.Spark on YARN--不需要启动Spark集群，因为已经在spark的配置文件中配置了hadoop的目录

1. 附录：
2. 不同运行模式的命令不同
3. 1.standalone client模式
4. ./bin/spark-submit --class org.apache.spark.examples.SparkPi--master spark://master:7077 --executor-memory 512m --total-executor-cores 1 ./lib/spark-examples-1.6.0-hadoop2.6.0.jar 100
5. 2.standalone cluster模式
6. ./bin/spark-submit --class org.apache.spark.examples.SparkPi--master spark://spark001:7077 --driver-memory 512m --deploy-mode cluster --supervise --executor-memory 512M --total-executor-cores 1 ./lib/spark-examples-1.6.0-hadoop2.6.0.jar 100
7. 3.on yarn client模式
8. ./bin/spark-submit --class org.apache.spark.examples.SparkPi--master yarn-client --executor-memory 512M--num-executors 1./lib/spark-examples-1.6.-hadoop2.6.0.jar 100
9. 4.on yarn cluster模式
10. ./bin/spark-submit --class org.apache.spark.examples.SparkPi--master yarn-cluster --executor-memory 512m--num-executors 1./lib/spark-examples-1.6.-hadoop2.6.0.jar 100

 

web端口查看Spark的运行