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authorDavies Liu <davies.liu@gmail.com>2014-08-26 13:04:30 -0700
committerJosh Rosen <joshrosen@apache.org>2014-08-26 13:05:35 -0700
commit83d273023b03faa0ceacd69956a132f40d247bc1 (patch)
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[SPARK-2871] [PySpark] add histgram() API
RDD.histogram(buckets) 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). 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]) >>> rdd = sc.parallelize(["ab", "ac", "b", "bd", "ef"]) >>> rdd.histogram(("a", "b", "c")) (('a', 'b', 'c'), [2, 2]) closes #122, it's duplicated. Author: Davies Liu <davies.liu@gmail.com> Closes #2091 from davies/histgram and squashes the following commits: a322f8a [Davies Liu] fix deprecation of e.message 84e85fa [Davies Liu] remove evenBuckets, add more tests (including str) d9a0722 [Davies Liu] address comments 0e18a2d [Davies Liu] add histgram() API (cherry picked from commit 3cedc4f4d78e093fd362085e0a077bb9e4f28ca5) Signed-off-by: Josh Rosen <joshrosen@apache.org>
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