Spark异常：worker中的Python版本3.4与驱动程序3.5中的版本不同

我正在使用 Amazon EC2，并且我将主服务器和开发服务器合二为一。我还有另一个针对单个工人的实例。

我对此很陌生，但我已经设法使 Spark 在独立模式下工作。现在我正在尝试集群。 master 和worker 处于活动状态（我可以看到它们的webUI 并且它们正在运行）。

我有 Spark 2.0，并且安装了最新的 Anaconda 4.1.1，它附带了 Python 3.5.2。在worker和master中，如果我去pyspark并执行os.version_info，我将得到3.5.2，我还正确设置了所有环境变量（如stackoverflow和google上的其他帖子所示）（例如，PYSPARK_PYTHON） 。

无论如何，任何地方都没有 3.4 版本的 python。所以我想知道如何解决这个问题。

我通过运行以下命令收到错误：

rdd = sc.parallelize([1,2,3])
rdd.count()    

count() 方法发生错误：

16/08/13 18:44:31 ERROR Executor: Exception in task 1.0 in stage 2.0 (TID 17)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 123, in main
    ("%d.%d" % sys.version_info[:2], version))
Exception: Python in worker has different version 3.4 than that in driver 3.5, PySpark cannot run with different minor versions

at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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)
16/08/13 18:44:31 ERROR Executor: Exception in task 1.1 in stage 2.0 (TID 18)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 123, in main
    ("%d.%d" % sys.version_info[:2], version))
Exception: Python in worker has different version 3.4 than that in driver 3.5, PySpark cannot run with different minor versions
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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)

由于您已经使用 Anaconda，因此您可以简单地创建一个具有所需 Python 版本的环境：

conda create --name foo python=3.4
source activate foo

python --version
## Python 3.4.5 :: Continuum Analytics, Inc

并将其用作PYSPARK_DRIVER_PYTHON:

export PYSPARK_DRIVER_PYTHON=/path/to/anaconda/envs/foo/bin/python