spark git commit: [SAPRK-25011][ML] add prefix to __all__ in fpm.py

[gu...@apache.org]

Repository: spark
Updated Branches:
  refs/heads/master 19a453191 -> ebf33a333


[SAPRK-25011][ML] add prefix to __all__ in fpm.py

## What changes were proposed in this pull request?

jira: https://issues.apache.org/jira/browse/SPARK-25011

add prefix to __all__ in fpm.py

## How was this patch tested?

existing unit test.

Author: Yuhao Yang <yu...@intel.com>

Closes #21981 from hhbyyh/prefixall.


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/ebf33a33
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/ebf33a33
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/ebf33a33

Branch: refs/heads/master
Commit: ebf33a333e9f7ad46f37233eee843e31028a1d62
Parents: 19a4531
Author: Yuhao Yang <yu...@intel.com>
Authored: Fri Aug 3 15:02:41 2018 +0800
Committer: hyukjinkwon <gu...@apache.org>
Committed: Fri Aug 3 15:02:41 2018 +0800

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 python/pyspark/ml/fpm.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/ebf33a33/python/pyspark/ml/fpm.py
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diff --git a/python/pyspark/ml/fpm.py b/python/pyspark/ml/fpm.py
index fd19fd9..f939442 100644
--- a/python/pyspark/ml/fpm.py
+++ b/python/pyspark/ml/fpm.py
@@ -21,7 +21,7 @@ from pyspark.ml.util import *
 from pyspark.ml.wrapper import JavaEstimator, JavaModel, JavaParams, _jvm
 from pyspark.ml.param.shared import *
 
-__all__ = ["FPGrowth", "FPGrowthModel"]
+__all__ = ["FPGrowth", "FPGrowthModel", "PrefixSpan"]
 
 
 class HasMinSupport(Params):
@@ -313,14 +313,15 @@ class PrefixSpan(JavaParams):
     def findFrequentSequentialPatterns(self, dataset):
         """
         .. note:: Experimental
+
         Finds the complete set of frequent sequential patterns in the input sequences of itemsets.
 
         :param dataset: A dataframe containing a sequence column which is
                         `ArrayType(ArrayType(T))` type, T is the item type for the input dataset.
         :return: A `DataFrame` that contains columns of sequence and corresponding frequency.
                  The schema of it will be:
-                  - `sequence: ArrayType(ArrayType(T))` (T is the item type)
-                  - `freq: Long`
+                 - `sequence: ArrayType(ArrayType(T))` (T is the item type)
+                 - `freq: Long`
 
         >>> from pyspark.ml.fpm import PrefixSpan
         >>> from pyspark.sql import Row


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