GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2091
[SPARK-2871] [PySpark] add histgram() API
Compute a histogram using the provided buckets. The buckets
are all open to the right except for the last which is closed.
e.g. [1,10,20,50] means the buckets are [1,10) [10,20) [20,50],
which means 1<=x<10, 10<=x<20, 20<=x<=50. And on the input of 1
and 50 we would have a histogram of 1,0,1.
If your histogram is evenly spaced (e.g. [0, 10, 20, 30]),
this can be switched from an O(log n) inseration to O(1) per
element(where n = # buckets), if you set `even` to True.
Buckets must be sorted and not contain any duplicates, must be
at least two elements.
If `buckets` is a number, it will generates buckets which is
evenly spaced between the minimum and maximum of the RDD. For
example, if the min value is 0 and the max is 100, given buckets
as 2, the resulting buckets will be [0,50) [50,100]. buckets must
be at least 1 If the RDD contains infinity, NaN throws an exception
If the elements in RDD do not vary (max == min) always returns
a single bucket.
It will return an tuple of buckets and histogram.
>>> rdd = sc.parallelize(range(51))
>>> rdd.histogram(2)
([0, 25, 50], [25, 26])
>>> rdd.histogram([0, 5, 25, 50])
([0, 5, 25, 50], [5, 20, 26])
>>> rdd.histogram([0, 15, 30, 45, 60], True)
([0, 15, 30, 45, 60], [15, 15, 15, 6])
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/davies/spark histgram
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/2091.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #2091
----
commit 0e18a2d3e98ca940320153b192fa03306cfd8f9a
Author: Davies Liu <[email protected]>
Date: 2014-08-22T04:33:38Z
add histgram() API
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