$ docker pull tchaumeny/spark

$ docker run --name spark-master -dit tchaumeny/spark
$ docker exec spark-master spark-1.6.0/sbin/start-master.sh

$ docker run --name spark-worker --link spark-master -dit tchaumeny/spark
$ docker exec spark-worker spark-1.6.0/sbin/start-slave.sh spark://spark-master:7077

$ docker exec -it spark-master spark-1.6.0/bin/pyspark

Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 1.6.0
      /_/

Using Python version 2.7.6 (default, Jun 22 2015 17:58:13)
SparkContext available as sc, SQLContext available as sqlContext.
>>> from operator import add
>>> from random import random
>>>
>>> N = 10**7
>>>
>>> def sample(p):
...     x, y = random(), random()
...     return 1 if x*x + y*y < 1 else 0
... 
>>> count = sc.parallelize(xrange(N)).map(sample).reduce(add)

>>> print("Pi is roughly %f" % (4.0 * count / N))
Pi is roughly 3.141773