Installation and use of Spark standalone

Installation: 1. Download http://d3kbcqa49mib13.cloudfront.net/spark-2.0.1-bin-hadoop2.6.tgz 2. Install Master to 192.168.8.94 machine to extract files and run start-master.sh bash start-master.sh in Sbin can be opened on the following page after normal installation:
3. Install worker./bin/spark-class org.apache.spark.deploy.worker.Worker spark://192.168.8.94:7077-c 4-m 2g-c parameter represents the number of cores. The-m parameter represents the memory size.
Installation Complete
Use: 1. Run the Pyspark shell, such as: Run the Pyspark Shell to allocate 6 CPUs, 2 CPUs per actuator, can be by the following command: Pyspark--master spark://192.168.8.94:7077--tota L-executor-cores 6--executor-cores 2 operation result: Welcome to ____ __/__/__ ___ _____//__ _\ \ _/_ '/__/' _//__/. __/\_ , _/_//_/\_\ version 2.0.2/_/
Using Python version 2.6.6 (r266:84292, Jul 15:22:56) sparksession available as ' spark '. >>> 2.spark-submit submit tasks such as submitting a task, allocating 6 CPUs, 2 CPUs per actuator, can be ordered by the following command [gcadmin006@cnhbase111 ~]$ spark-submit--master spark://172.17.13.111:7077--total-executor-cores 6--executor-cores 2 hbase_to_cloudhbase_prodesc.py