我有一些问题，以启动一个主Spark集群和工人。我在ubuntu16.04 lts上下载并安装了hadoop2.7.3和spark2.0.0。我用我的slave的ip创建了一个conf/slaves文件，这是我的spark-env.sh

# !/usr/bin/env #bash

export SPARK_DIST_CLASSPATH=$(hadoop classpath)

export SPARK_WORKER_CORES=2

export SPARK_MASTER_IP=192.168.1.6
export SPARK_LOCAL_IP=192.168.1.6

export SPARK_YARN_USER_ENV="JAVA_HOME=/usr/lib/jvm/java-8-oracle/jre"

我用start-master.sh启动了master，一切正常。我试着跑工人时遇到了一些问题。
我试过：

(1) - start-slave.sh spark://192.168.1.6:7077 (from worker)
(2) - start-slaves.sh (from master)
(3) - ./bin/spark-class org.apache.spark.deploy.worker.Worker spark://192.168.1.6:7077 (from worker)

在（1）e（2）中，从机显然已启动，但处于master:8080 it 没有显示。使用（3）会引发以下异常：

16/08/31 14:17:03 INFO worker.Worker: Connecting to master master:7077...
16/08/31 14:17:03 WARN worker.Worker: Failed to connect to master master:7077
org.apache.spark.SparkException: Exception thrown in awaitResult
    at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:77)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:75)
    at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
    at scala.PartialFunction$OrElse.apply(PartialFunction.scala:167)
    at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:83)
    at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:88)
    at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:96)
    at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters$1$$anon$1.run(Worker.scala:216)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: Failed to connect to master/192.168.1.6:7077
    at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:228)
    at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:179)
    at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:197)
    at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:191)
    at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:187)
    ... 4 more
Caused by: java.net.ConnectException: Connection refused: master/192.168.1.6:7077
    at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
    at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
    at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
    at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289)
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
    at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
    at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
    ... 1 more
16/08/31 14:17:40 ERROR worker.Worker: All masters are unresponsive! Giving up.

主进程和工作进程由使用桥接连接安装在同一Windows10主机上的VMWareVM托管。
我还禁用了防火墙。
我能做什么？？
提前谢谢。