I've install a cluster with one node on a amazon machine thanks to ambari. I'm trying to use spark from an other machine thanks to pySpark.
This is my code :
from pyspark import SparkConf, SparkContext
conf = SparkConf().setAppName('hello').setMaster('spark://MYIP:7077')
sc = SparkContext(conf=conf)
The problem is that I have a connection refused when I run the program :
WARN StandaloneAppClient$ClientEndpoint: Failed to connect to master "MYIP"
So, I tried this command to start the master : ./sbin/start-master.sh
And now, I have this error :
17/07/27 12:07:15 WARN StandaloneAppClient$ClientEndpoint: Failed to connect to master XX.XXX.XXX.XX:7077
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:100)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:108)
at org.apache.spark.deploy.client.StandaloneAppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1$$anon$1.run(StandaloneAppClient.scala:106)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.RuntimeException: java.io.StreamCorruptedException: invalid stream header: 01000C31
This is not a problem of port because the port 7077 is open.
I don't find any answer for that problem on the forum, do you have any idea ?