[GitHub] [beam] iindyk commented on a change in pull request #12420: Extending ApproximateQuantiles functionality to deal with non-uniform weights.

[GitBox <gi...@apache.org>]

iindyk commented on a change in pull request #12420:
URL: https://github.com/apache/beam/pull/12420#discussion_r468937732



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File path: sdks/python/apache_beam/transforms/stats.py
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@@ -263,30 +265,38 @@ class Globally(PTransform):
 
     Args:
       num_quantiles: number of elements in the resulting quantiles values list.
+      weighted: (optional) if set to True, the transform returns weighted
+        quantiles. The input PCollection is then expected to contain tuples of
+        input values with the corresponding weight.
       key: (optional) Key is  a mapping of elements to a comparable key, similar
         to the key argument of Python's sorting methods.
       reverse: (optional) whether to order things smallest to largest, rather
         than largest to smallest
     """
-    def __init__(self, num_quantiles, key=None, reverse=False):
+    def __init__(self, num_quantiles, weighted=False, key=None, reverse=False):

Review comment:
       Ah, yes, of course.




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