[SPARK-2871] [PySpark] add approx API for RDD

[davies]

RDD.countApprox(self, timeout, confidence=0.95)

    :: Experimental ::
    Approximate version of count() that returns a potentially incomplete
    result within a timeout, even if not all tasks have finished.

    >>> rdd = sc.parallelize(range(1000), 10)
    >>> rdd.countApprox(1000, 1.0)
    1000

RDD.sumApprox(self, timeout, confidence=0.95)

    Approximate operation to return the sum within a timeout
    or meet the confidence.

    >>> rdd = sc.parallelize(range(1000), 10)
    >>> r = sum(xrange(1000))
    >>> (rdd.sumApprox(1000) - r) / r < 0.05

RDD.meanApprox(self, timeout, confidence=0.95)

    :: Experimental ::
    Approximate operation to return the mean within a timeout
    or meet the confidence.

    >>> rdd = sc.parallelize(range(1000), 10)
    >>> r = sum(xrange(1000)) / 1000.0
    >>> (rdd.meanApprox(1000) - r) / r < 0.05
    True

[SparkQA]

QA tests have started for PR 2095 at commit e8c252b.

• This patch merges cleanly.

[SparkQA]

QA tests have finished for PR 2095 at commit e8c252b.

• This patch passes unit tests.
• This patch merges cleanly.
• This patch adds the following public classes (experimental):
  • class BoundedFloat(float):

[JoshRosen]

There's a small possibility that this name could be confusing, since self._jrdd returns a Java RDD of Python objects, whereas self.to_jrdd() returns a JavaRDD of Java objects. I would maybe rename this to something like to_java_object_rdd.

[JoshRosen]

This looks good to me; I had one minor comment about a potentially-confusing internal name, but we can take care of that later as part of a more general Python RDD <-> Java Object RDD utility method refactoring / cleanup.

[JoshRosen]

I've merged this into master. Thanks!