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[GitHub] [spark] zero323 opened a new pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
zero323 opened a new pull request #30285:
URL: https://github.com/apache/spark/pull/30285
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This PR proposes migration of `pyspark.ml` to NumPy documentation style.
### Why are the changes needed?
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To improve documentation style.
### Does this PR introduce _any_ user-facing change?
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Yes, this changes both rendered HTML docs and console representation (SPARK-33243).
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`dev/lint-python` and manual inspection.
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[GitHub] [spark] zero323 commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
zero323 commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520215823
##########
File path: python/pyspark/ml/fpm.py
##########
@@ -408,19 +429,26 @@ def getSequenceCol(self):
"""
return self.getOrDefault(self.sequenceCol)
- @since("2.4.0")
def findFrequentSequentialPatterns(self, dataset):
"""
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`
-
.. versionadded:: 2.4.0
+
+ Parameters
+ ----------
+ dataset : :py:class:`pyspark.sql.DataFrame`
+ A dataframe containing a sequence column which is
+ `ArrayType(ArrayType(T))` type, T is the item type for the input dataset.
+
+ Returns
+ -------
+ pyspark.sql.dataframe.DataFrame
Review comment:
Thanks @huaxingao. I'll wait to see if you have any other comments and open [a follow up](https://github.com/apache/spark/compare/master...zero323:SPARK-33251-FOLLOW-UP).
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[GitHub] [spark] huaxingao commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
huaxingao commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520193081
##########
File path: python/pyspark/ml/base.py
##########
@@ -81,21 +87,38 @@ def _fit(self, dataset):
"""
Fits a model to the input dataset. This is called by the default implementation of fit.
- :param dataset: input dataset, which is an instance of :py:class:`pyspark.sql.DataFrame`
- :returns: fitted model
+
+ Parameters
+ ----------
+ dataset : :py:class:`pyspark.sql.DataFrame`
+ input dataset, which is an instance of :py:class:`pyspark.sql.DataFrame`
Review comment:
nit: remove the which clause?
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##########
File path: python/pyspark/ml/base.py
##########
@@ -34,13 +34,19 @@ class _FitMultipleIterator(object):
iterator. This class handles the simple case of fitMultiple where each param map should be
fit independently.
- :param fitSingleModel: Function: (int => Model) which fits an estimator to a dataset.
+ Parameters
+ ----------
+ fitSingleModel
Review comment:
maybe `fitSingleModel` -> `fitSingleModel : callable` or just `fitSingleModel : function`
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cc @huaxingao, @zhengruifeng, @viirya, @BryanCutler, can you take a cursory look when you guys fine some time?
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Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520027022
##########
File path: python/pyspark/ml/feature.py
##########
@@ -278,14 +292,24 @@ def approxSimilarityJoin(self, datasetA, datasetB, threshold, distCol="distCol")
if the :py:attr:`outputCol` exists, it will use that. This allows caching of the
transformed data when necessary.
- :param datasetA: One of the datasets to join.
- :param datasetB: Another dataset to join.
- :param threshold: The threshold for the distance of row pairs.
- :param distCol: Output column for storing the distance between each pair of rows. Use
- "distCol" as default value if it's not specified.
- :return: A joined dataset containing pairs of rows. The original rows are in columns
- "datasetA" and "datasetB", and a column "distCol" is added to show the distance
- between each pair.
+ Parameters
+ ----------
+ datasetA : :py:class:`pyspark.sql.DataFrame`
+ One of the datasets to join.
+ datasetA : :py:class:`pyspark.sql.DataFrame`
Review comment:
datasetA -> datasetB
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* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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Awesome @zero323! I will take a look in the following few ays.
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[GitHub] [spark] viirya commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r519525099
##########
File path: python/pyspark/ml/base.py
##########
@@ -34,13 +34,19 @@ class _FitMultipleIterator(object):
iterator. This class handles the simple case of fitMultiple where each param map should be
fit independently.
- :param fitSingleModel: Function: (int => Model) which fits an estimator to a dataset.
+ Parameters
+ ----------
+ fitSingleModel
+ Callable[[int], Transformer]which fits an estimator to a dataset.
Review comment:
Callable[[int], Transformer]which -> Callable[[int], Transformer] which?
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[GitHub] [spark] huaxingao commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
huaxingao commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520210072
##########
File path: python/pyspark/ml/fpm.py
##########
@@ -408,19 +429,26 @@ def getSequenceCol(self):
"""
return self.getOrDefault(self.sequenceCol)
- @since("2.4.0")
def findFrequentSequentialPatterns(self, dataset):
"""
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`
-
.. versionadded:: 2.4.0
+
+ Parameters
+ ----------
+ dataset : :py:class:`pyspark.sql.DataFrame`
+ A dataframe containing a sequence column which is
+ `ArrayType(ArrayType(T))` type, T is the item type for the input dataset.
+
+ Returns
+ -------
+ pyspark.sql.dataframe.DataFrame
Review comment:
nit: `pyspark.sql.DataFrame`?
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[GitHub] [spark] HyukjinKwon commented on pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #30285:
URL: https://github.com/apache/spark/pull/30285#issuecomment-724370387
Merged to master.
Thanks all!
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[GitHub] [spark] viirya commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520032889
##########
File path: python/pyspark/ml/stat.py
##########
@@ -363,13 +390,21 @@ def metrics(*metrics):
- normL2: the Euclidean norm for each coefficient.
- normL1: the L1 norm of each coefficient (sum of the absolute values).
- :param metrics:
- metrics that can be provided.
- :return:
- an object of :py:class:`pyspark.ml.stat.SummaryBuilder`
+ .. versionadded:: 2.4.0
- Note: Currently, the performance of this interface is about 2x~3x slower then using the RDD
+ Notes
+ -----
+ Currently, the performance of this interface is about 2x~3x slower then using the RDD
Review comment:
then -> than
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[GitHub] [spark] zero323 commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
zero323 commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520215823
##########
File path: python/pyspark/ml/fpm.py
##########
@@ -408,19 +429,26 @@ def getSequenceCol(self):
"""
return self.getOrDefault(self.sequenceCol)
- @since("2.4.0")
def findFrequentSequentialPatterns(self, dataset):
"""
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`
-
.. versionadded:: 2.4.0
+
+ Parameters
+ ----------
+ dataset : :py:class:`pyspark.sql.DataFrame`
+ A dataframe containing a sequence column which is
+ `ArrayType(ArrayType(T))` type, T is the item type for the input dataset.
+
+ Returns
+ -------
+ pyspark.sql.dataframe.DataFrame
Review comment:
Thanks @huaxingao. I'll wait to see if you have any other comments and open a follow up.
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URL: https://github.com/apache/spark/pull/30285#issuecomment-723429186
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[GitHub] [spark] SparkQA commented on pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #30285:
URL: https://github.com/apache/spark/pull/30285#issuecomment-724045694
**[Test build #130791 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/130791/testReport)** for PR 30285 at commit [`4bf8e35`](https://github.com/apache/spark/commit/4bf8e35e2306c69342b23e9e9b6fb45706923019).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] huaxingao commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
huaxingao commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520241117
##########
File path: python/pyspark/ml/fpm.py
##########
@@ -408,19 +429,26 @@ def getSequenceCol(self):
"""
return self.getOrDefault(self.sequenceCol)
- @since("2.4.0")
def findFrequentSequentialPatterns(self, dataset):
"""
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`
-
.. versionadded:: 2.4.0
+
+ Parameters
+ ----------
+ dataset : :py:class:`pyspark.sql.DataFrame`
+ A dataframe containing a sequence column which is
+ `ArrayType(ArrayType(T))` type, T is the item type for the input dataset.
+
+ Returns
+ -------
+ pyspark.sql.dataframe.DataFrame
Review comment:
I finished the review. please go ahead with your follow-up. I should have submitted all the comments at the same time instead of doing single comment.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #30285: [SPARK-33251][PYTHON][DOCS] Migration to NumPy documentation style in ML (pyspark.ml.*)
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #30285:
URL: https://github.com/apache/spark/pull/30285#discussion_r520222655
##########
File path: python/pyspark/ml/fpm.py
##########
@@ -408,19 +429,26 @@ def getSequenceCol(self):
"""
return self.getOrDefault(self.sequenceCol)
- @since("2.4.0")
def findFrequentSequentialPatterns(self, dataset):
"""
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`
-
.. versionadded:: 2.4.0
+
+ Parameters
+ ----------
+ dataset : :py:class:`pyspark.sql.DataFrame`
+ A dataframe containing a sequence column which is
+ `ArrayType(ArrayType(T))` type, T is the item type for the input dataset.
+
+ Returns
+ -------
+ pyspark.sql.dataframe.DataFrame
Review comment:
Ohh @huaxingao sorry I thought you finished the review. Sure, feel free to go ahead for a followup.
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