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Posted to reviews@spark.apache.org by mgaido91 <gi...@git.apache.org> on 2018/02/06 15:16:53 UTC
[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
GitHub user mgaido91 opened a pull request:
https://github.com/apache/spark/pull/20520
[SPARK-23344][PYTHON][ML] Add distanceMeasure param to KMeans
## What changes were proposed in this pull request?
SPARK-22119 introduced a new parameter for KMeans, ie. `distanceMeasure`. The PR adds it also to the Python interface.
## How was this patch tested?
added UTs
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mgaido91/spark SPARK-23344
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/20520.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 #20520
----
commit 65da587cb32bbf002fbdd54353e49399a8b9de3f
Author: Marco Gaido <ma...@...>
Date: 2018-02-06T15:14:27Z
[SPARK-23344][PYTHON][ML] Add distanceMeasure param to KMeans
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by AmplabJenkins <gi...@git.apache.org>.
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20520
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by mgaido91 <gi...@git.apache.org>.
Github user mgaido91 commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167082120
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
--- End diff --
it was just to test that this method is working. Do you think it is better to switch to what you suggested?
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20520
**[Test build #87270 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/87270/testReport)** for PR 20520 at commit [`cbdbe12`](https://github.com/apache/spark/commit/cbdbe121e4be7199e11457e4ff3f94e9b0a10c34).
* This patch passes all tests.
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* This patch adds no public classes.
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/20520
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by BryanCutler <gi...@git.apache.org>.
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167089401
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
--- End diff --
It probably a little more common to put the param in the constructor, which should be tested also. you put `setDistanceMeasure` in `test_kmeans_param` which seems better, not a big deal though
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/20520
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by BryanCutler <gi...@git.apache.org>.
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167308210
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
+ model = kmeans.fit(df)
+ result = model.transform(df).rdd.collectAsMap()
+ self.assertTrue(result[Vectors.dense([1.0, 1.0])] == result[Vectors.dense([10.0, 10.0])])
--- End diff --
yes, the order is preserved so you can do the same as doctest.
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by BryanCutler <gi...@git.apache.org>.
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167048301
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
--- End diff --
minor, but why not just `kmeans = KMeans(k=3, distanceMeasure="cosine", seed=1)`?
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/20520
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20520
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20520
**[Test build #87112 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/87112/testReport)** for PR 20520 at commit [`65da587`](https://github.com/apache/spark/commit/65da587cb32bbf002fbdd54353e49399a8b9de3f).
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by mgaido91 <gi...@git.apache.org>.
Github user mgaido91 commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167081534
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
+ model = kmeans.fit(df)
+ result = model.transform(df).rdd.collectAsMap()
+ self.assertTrue(result[Vectors.dense([1.0, 1.0])] == result[Vectors.dense([10.0, 10.0])])
--- End diff --
sorry but I can't really understand what you are thinking about: here I compare that the prediction for two points contains the same value. Since the value is not known in advance I cannot just check if the dataframe is equal to something predefined. Am I missing something?
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by BryanCutler <gi...@git.apache.org>.
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167089783
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
+ model = kmeans.fit(df)
+ result = model.transform(df).rdd.collectAsMap()
+ self.assertTrue(result[Vectors.dense([1.0, 1.0])] == result[Vectors.dense([10.0, 10.0])])
--- End diff --
I meant something like this, similar to how its done in the KMeans pydoc
```
>>> transformed = model.transform(df).select("features", "prediction")
>>> rows = transformed.collect()
>>> rows[0].prediction == rows[1].prediction
True
>>> rows[2].prediction == rows[3].prediction
```
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/20520
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by AmplabJenkins <gi...@git.apache.org>.
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by BryanCutler <gi...@git.apache.org>.
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167048075
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
+ model = kmeans.fit(df)
+ result = model.transform(df).rdd.collectAsMap()
+ self.assertTrue(result[Vectors.dense([1.0, 1.0])] == result[Vectors.dense([10.0, 10.0])])
--- End diff --
It's a little awkward to collectAsMap and compare like this, why not just regular collect and compare with `data` above?
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by mgaido91 <gi...@git.apache.org>.
Github user mgaido91 commented on the issue:
https://github.com/apache/spark/pull/20520
cc @BryanCutler @holdenk @jkbradley @srowen
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
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[GitHub] spark pull request #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure par...
Posted by mgaido91 <gi...@git.apache.org>.
Github user mgaido91 commented on a diff in the pull request:
https://github.com/apache/spark/pull/20520#discussion_r167165450
--- Diff: python/pyspark/ml/tests.py ---
@@ -1620,6 +1621,23 @@ def test_kmeans_summary(self):
self.assertEqual(s.k, 2)
+class KMeansTests(SparkSessionTestCase):
+
+ def test_kmeans_cosine_distance(self):
+ data = [(Vectors.dense([1.0, 1.0]),), (Vectors.dense([10.0, 10.0]),),
+ (Vectors.dense([1.0, 0.5]),), (Vectors.dense([10.0, 4.4]),),
+ (Vectors.dense([-1.0, 1.0]),), (Vectors.dense([-100.0, 90.0]),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ kmeans = KMeans(k=3, seed=1)
+ kmeans.setDistanceMeasure("cosine")
+ model = kmeans.fit(df)
+ result = model.transform(df).rdd.collectAsMap()
+ self.assertTrue(result[Vectors.dense([1.0, 1.0])] == result[Vectors.dense([10.0, 10.0])])
--- End diff --
@BryanCutler is it guaranteed that the ordering is not changed? And is the ordering deterministic? I did it like this and now how you suggest because I thought that the ordering is not guaranteed, am I wrong?
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by AmplabJenkins <gi...@git.apache.org>.
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[GitHub] spark issue #20520: [SPARK-23344][PYTHON][ML] Add distanceMeasure param to K...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20520
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* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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