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Posted to reviews@spark.apache.org by holdenk <gi...@git.apache.org> on 2018/03/26 19:10:36 UTC
[GitHub] spark pull request #20907: [WIP][SPARK-11237][ML] Add pmml export for k-mean...
GitHub user holdenk opened a pull request:
https://github.com/apache/spark/pull/20907
[WIP][SPARK-11237][ML] Add pmml export for k-means in Spark ML
## What changes were proposed in this pull request?
Adding PMML export to Spark ML's KMeans Model.
## How was this patch tested?
New unit test for Spark ML PMML export based on the old Spark MLlib unit test.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/holdenk/spark SPARK-11237-Add-PMML-Export-for-KMeans
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/20907.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 #20907
----
commit 4431407de2f2138ffe054ef31ea4306c6bb32577
Author: Holden Karau <ho...@...>
Date: 2018-03-26T18:47:13Z
Switch KMeans to GeneralMLWriter and add the internal writer.
commit 25d6f77c6700c45925f68ee044fa7d136e83b37e
Author: Holden Karau <ho...@...>
Date: 2018-03-26T19:08:46Z
Add PMML export for KMeans model
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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[GitHub] spark issue #20907: [SPARK-11237][ML] Add pmml export for k-means in Spark M...
Posted by viirya <gi...@git.apache.org>.
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/20907
One question I have is, how do users know if a model (e.g. KMeansModel after this change) supports pmml & internal formats? I did a search on the current docs, but didn't find any info.
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[GitHub] spark issue #20907: [SPARK-11237][ML] Add pmml export for k-means in Spark M...
Posted by viirya <gi...@git.apache.org>.
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/20907
LGTM
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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**[Test build #88766 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/88766/testReport)** for PR 20907 at commit [`e2dbe15`](https://github.com/apache/spark/commit/e2dbe15fa945a63a045558ad8f10239510b166f2).
* This patch **fails to build**.
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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[GitHub] spark pull request #20907: [WIP][SPARK-11237][ML] Add pmml export for k-mean...
Posted by holdenk <gi...@git.apache.org>.
Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/20907#discussion_r178382724
--- Diff: mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala ---
@@ -202,6 +207,26 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultR
testEstimatorAndModelReadWrite(kmeans, dataset, KMeansSuite.allParamSettings,
KMeansSuite.allParamSettings, checkModelData)
}
+
+ test("pmml export") {
+ val clusterCenters = Array(
+ MLlibVectors.dense(1.0, 2.0, 6.0),
+ MLlibVectors.dense(1.0, 3.0, 0.0),
+ MLlibVectors.dense(1.0, 4.0, 6.0))
+ val oldKmeansModel = new MLlibKMeansModel(clusterCenters)
+ val kmeansModel = new KMeansModel("", oldKmeansModel)
+ def checkModel(pmml: PMML): Unit = {
+ // Check the header descripiton is what we expect
+ assert(pmml.getHeader.getDescription === "k-means clustering")
+ // check that the number of fields match the single vector size
+ assert(pmml.getDataDictionary.getNumberOfFields === clusterCenters(0).size)
+ // This verify that there is a model attached to the pmml object and the model is a clustering
+ // one. It also verifies that the pmml model has the same number of clusters of the spark
+ // model.
+ val pmmlClusteringModel = pmml.getModels.get(0).asInstanceOf[ClusteringModel]
+ assert(pmmlClusteringModel.getNumberOfClusters === clusterCenters.length)
+ }
--- End diff --
Oh yeah :( Thanks for catching that.
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20907
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[GitHub] spark pull request #20907: [WIP][SPARK-11237][ML] Add pmml export for k-mean...
Posted by holdenk <gi...@git.apache.org>.
Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/20907#discussion_r178384426
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala ---
@@ -185,6 +187,47 @@ class KMeansModel private[ml] (
}
}
+/** Helper class for storing model data */
+private case class ClusterData(clusterIdx: Int, clusterCenter: Vector)
+
+
+/** A writer for KMeans that handles the "internal" (or default) format */
+private class InternalKMeansModelWriter extends MLWriterFormat with MLFormatRegister {
+
+ override def format(): String = "internal"
+ override def stageName(): String = "org.apache.spark.ml.clustering.KMeansModel"
+
+ override def write(path: String, sparkSession: SparkSession,
+ optionMap: mutable.Map[String, String], stage: PipelineStage): Unit = {
+ val instance = stage.asInstanceOf[KMeansModel]
+ val sc = sparkSession.sparkContext
+ // Save metadata and Params
+ DefaultParamsWriter.saveMetadata(instance, path, sc)
+ // Save model data: cluster centers
+ val data: Array[ClusterData] = instance.clusterCenters.zipWithIndex.map {
+ case (center, idx) =>
+ ClusterData(idx, center)
--- End diff --
Wait no this shouldn't change anything, were saving this with a DataFrame and the schema is the same.
See the schema from 1: `res3: org.apache.spark.sql.types.StructType = StructType(StructField(clusterIdx,IntegerType,false), StructField(clusterCenter,org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7,true))` and the new one `org.apache.spark.sql.types.StructType = StructType(StructField(clusterIdx,IntegerType,false), StructField(clusterCenter,org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7,true))`
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
Posted by holdenk <gi...@git.apache.org>.
Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/20907
cc @BryanCutler @sethah @MLnick
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[GitHub] spark issue #20907: [SPARK-11237][ML] Add pmml export for k-means in Spark M...
Posted by dbtsai <gi...@git.apache.org>.
Github user dbtsai commented on the issue:
https://github.com/apache/spark/pull/20907
LGTM too! +1 on the documentation which can be a followup PR. Merged into master, and thanks.
DB Tsai | Siri Open Source Technologies | Apple, Inc
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[GitHub] spark pull request #20907: [WIP][SPARK-11237][ML] Add pmml export for k-mean...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/20907#discussion_r178425007
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala ---
@@ -185,6 +187,47 @@ class KMeansModel private[ml] (
}
}
+/** Helper class for storing model data */
+private case class ClusterData(clusterIdx: Int, clusterCenter: Vector)
+
+
+/** A writer for KMeans that handles the "internal" (or default) format */
+private class InternalKMeansModelWriter extends MLWriterFormat with MLFormatRegister {
+
+ override def format(): String = "internal"
+ override def stageName(): String = "org.apache.spark.ml.clustering.KMeansModel"
+
+ override def write(path: String, sparkSession: SparkSession,
+ optionMap: mutable.Map[String, String], stage: PipelineStage): Unit = {
+ val instance = stage.asInstanceOf[KMeansModel]
+ val sc = sparkSession.sparkContext
+ // Save metadata and Params
+ DefaultParamsWriter.saveMetadata(instance, path, sc)
+ // Save model data: cluster centers
+ val data: Array[ClusterData] = instance.clusterCenters.zipWithIndex.map {
+ case (center, idx) =>
+ ClusterData(idx, center)
--- End diff --
👍
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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[GitHub] spark pull request #20907: [WIP][SPARK-11237][ML] Add pmml export for k-mean...
Posted by holdenk <gi...@git.apache.org>.
Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/20907#discussion_r177845432
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala ---
@@ -185,6 +187,47 @@ class KMeansModel private[ml] (
}
}
+/** Helper class for storing model data */
+private case class ClusterData(clusterIdx: Int, clusterCenter: Vector)
+
+
+/** A writer for KMeans that handles the "internal" (or default) format */
+private class InternalKMeansModelWriter extends MLWriterFormat with MLFormatRegister {
+
+ override def format(): String = "internal"
+ override def stageName(): String = "org.apache.spark.ml.clustering.KMeansModel"
+
+ override def write(path: String, sparkSession: SparkSession,
+ optionMap: mutable.Map[String, String], stage: PipelineStage): Unit = {
+ val instance = stage.asInstanceOf[KMeansModel]
+ val sc = sparkSession.sparkContext
+ // Save metadata and Params
+ DefaultParamsWriter.saveMetadata(instance, path, sc)
+ // Save model data: cluster centers
+ val data: Array[ClusterData] = instance.clusterCenters.zipWithIndex.map {
+ case (center, idx) =>
+ ClusterData(idx, center)
--- End diff --
I'm not 100% sure. I'll manually test we can load the old format first.
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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* This patch passes all tests.
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[GitHub] spark pull request #20907: [SPARK-11237][ML] Add pmml export for k-means in ...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
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[GitHub] spark pull request #20907: [WIP][SPARK-11237][ML] Add pmml export for k-mean...
Posted by BryanCutler <gi...@git.apache.org>.
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/20907#discussion_r178204492
--- Diff: mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala ---
@@ -202,6 +207,26 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultR
testEstimatorAndModelReadWrite(kmeans, dataset, KMeansSuite.allParamSettings,
KMeansSuite.allParamSettings, checkModelData)
}
+
+ test("pmml export") {
+ val clusterCenters = Array(
+ MLlibVectors.dense(1.0, 2.0, 6.0),
+ MLlibVectors.dense(1.0, 3.0, 0.0),
+ MLlibVectors.dense(1.0, 4.0, 6.0))
+ val oldKmeansModel = new MLlibKMeansModel(clusterCenters)
+ val kmeansModel = new KMeansModel("", oldKmeansModel)
+ def checkModel(pmml: PMML): Unit = {
+ // Check the header descripiton is what we expect
+ assert(pmml.getHeader.getDescription === "k-means clustering")
+ // check that the number of fields match the single vector size
+ assert(pmml.getDataDictionary.getNumberOfFields === clusterCenters(0).size)
+ // This verify that there is a model attached to the pmml object and the model is a clustering
+ // one. It also verifies that the pmml model has the same number of clusters of the spark
+ // model.
+ val pmmlClusteringModel = pmml.getModels.get(0).asInstanceOf[ClusteringModel]
+ assert(pmmlClusteringModel.getNumberOfClusters === clusterCenters.length)
+ }
--- End diff --
Isn't this missing a call to `testPMMLWrite`?
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[GitHub] spark pull request #20907: [WIP][SPARK-11237][ML] Add pmml export for k-mean...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/20907#discussion_r177322828
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala ---
@@ -185,6 +187,47 @@ class KMeansModel private[ml] (
}
}
+/** Helper class for storing model data */
+private case class ClusterData(clusterIdx: Int, clusterCenter: Vector)
+
+
+/** A writer for KMeans that handles the "internal" (or default) format */
+private class InternalKMeansModelWriter extends MLWriterFormat with MLFormatRegister {
+
+ override def format(): String = "internal"
+ override def stageName(): String = "org.apache.spark.ml.clustering.KMeansModel"
+
+ override def write(path: String, sparkSession: SparkSession,
+ optionMap: mutable.Map[String, String], stage: PipelineStage): Unit = {
+ val instance = stage.asInstanceOf[KMeansModel]
+ val sc = sparkSession.sparkContext
+ // Save metadata and Params
+ DefaultParamsWriter.saveMetadata(instance, path, sc)
+ // Save model data: cluster centers
+ val data: Array[ClusterData] = instance.clusterCenters.zipWithIndex.map {
+ case (center, idx) =>
+ ClusterData(idx, center)
--- End diff --
doesn't this type change `Data` -> `ClusterData` change the schema of the output parquet file?
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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[GitHub] spark issue #20907: [WIP][SPARK-11237][ML] Add pmml export for k-means in Sp...
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* This patch passes all tests.
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[GitHub] spark issue #20907: [SPARK-11237][ML] Add pmml export for k-means in Spark M...
Posted by holdenk <gi...@git.apache.org>.
Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/20907
Yup, this is ready. If you think its good feel free to merge it otherwise I'll merge it during my regular Friday review time :)
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