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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/03/22 06:45:22 UTC
[GitHub] [spark] huaxingao opened a new pull request #27978:
[SPARK-31127][ML] Implement abstract Selector
huaxingao opened a new pull request #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978
### What changes were proposed in this pull request?
Implement abstract Selector. Put the common code among ```ANOVASelector```, ```ChiSqSelector```, ```FValueSelector``` and ```VarianceThresholdSelector``` to Selector.
### Why are the changes needed?
code reuse
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Existing tests
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Implement abstract Selector
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Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
SparkQA commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-602829652
**[Test build #120214 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/120214/testReport)** for PR 27978 at commit [`ba29708`](https://github.com/apache/spark/commit/ba297085d165648896854d06921cd7ee3bb4896b).
* This patch **fails PySpark pip packaging tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] srowen commented on a change in pull request #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
srowen commented on a change in pull request #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#discussion_r396108095
##########
File path: project/MimaExcludes.scala
##########
@@ -38,7 +38,11 @@ object MimaExcludes {
lazy val v31excludes = v30excludes ++ Seq(
// [SPARK-31077] Remove ChiSqSelector dependency on mllib.ChiSqSelectorModel
// private constructor
- ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this")
+ ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this"),
+ // [SPARK-31127] Implement abstract Selector
+ ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel"),
Review comment:
Weird: this class is still there, right? is this still definitely a MiMa error? I'm trying to figure out if we're missing something here that causes an incompatible change.
This would only go into 3.1 right?
The refactoring looks OK; hard to evaluate it all.
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[GitHub] [spark] SparkQA commented on issue #27978: [SPARK-31127][ML]
Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
SparkQA commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-602179043
**[Test build #120156 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/120156/testReport)** for PR 27978 at commit [`5779708`](https://github.com/apache/spark/commit/57797087801cb4cea92abf56b72cc96ef2c77c8b).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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Implement abstract Selector
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Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
SparkQA commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-602849591
**[Test build #120219 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/120219/testReport)** for PR 27978 at commit [`ba29708`](https://github.com/apache/spark/commit/ba297085d165648896854d06921cd7ee3bb4896b).
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[GitHub] [spark] zhengruifeng commented on issue #27978: [SPARK-31127][ML]
Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
zhengruifeng commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-604857001
It seems that you still need to override setters and getters in subclasses, like
```scala
override def setNumTopFeatures(value: Int): this.type = super.setNumTopFeatures(value)
```
It seems that the main benefit is to avoid copying the transfrom part in subclasses, at the cost of adding several abstract classes. So what about just resuing the transfrom function among selection models?
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Implement abstract Selector
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Implement abstract Selector
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Implement abstract Selector
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[GitHub] [spark] huaxingao commented on a change in pull request #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
huaxingao commented on a change in pull request #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#discussion_r396115293
##########
File path: project/MimaExcludes.scala
##########
@@ -38,7 +38,11 @@ object MimaExcludes {
lazy val v31excludes = v30excludes ++ Seq(
// [SPARK-31077] Remove ChiSqSelector dependency on mllib.ChiSqSelectorModel
// private constructor
- ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this")
+ ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this"),
+ // [SPARK-31127] Implement abstract Selector
+ ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel"),
Review comment:
This is for 3.1 only.
The first two MiMa errors are because of type hierarchy change.
```
[error] * the type hierarchy of class org.apache.spark.ml.feature.ChiSqSelectorModel is different in current version. Missing types {org.apache.spark.ml.feature.ChiSqSelectorParams}
```
The 3rd MiMa error is due to return type change.
```
[error] * method fit(org.apache.spark.sql.Dataset)org.apache.spark.ml.feature.ChiSqSelectorModel in class org.apache.spark.ml.feature.ChiSqSelector has a different result type in current version, where it is org.apache.spark.ml.feature.SelectorModel rather than org.apache.spark.ml.feature.ChiSqSelectorModel
```
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[GitHub] [spark] zhengruifeng edited a comment on issue #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
zhengruifeng edited a comment on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-604857001
It seems that you still need to override setters and getters in subclasses, like
```scala
override def setNumTopFeatures(value: Int): this.type = super.setNumTopFeatures(value)
```
It seems that the main benefit is to avoid copying 1, the transfrom part in subclasses, and 2, choosing features by test results, at the cost of adding several abstract classes. So what about just resuing thoes functions among selection models?
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Implement abstract Selector
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Implement abstract Selector
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**[Test build #120168 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/120168/testReport)** for PR 27978 at commit [`359c92d`](https://github.com/apache/spark/commit/359c92d8430d8d1fc761334e638027631da601c6).
* This patch passes all tests.
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* This patch adds no public classes.
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Implement abstract Selector
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[GitHub] [spark] huaxingao commented on a change in pull request #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
huaxingao commented on a change in pull request #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#discussion_r396624956
##########
File path: project/MimaExcludes.scala
##########
@@ -38,7 +38,11 @@ object MimaExcludes {
lazy val v31excludes = v30excludes ++ Seq(
// [SPARK-31077] Remove ChiSqSelector dependency on mllib.ChiSqSelectorModel
// private constructor
- ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this")
+ ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this"),
+ // [SPARK-31127] Implement abstract Selector
+ ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel"),
Review comment:
Seems I have to override ```fit``` in subclasses.
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Implement abstract Selector
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huaxingao commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-603922940
retest this please
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Implement abstract Selector
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retest this please
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[GitHub] [spark] zhengruifeng commented on issue #27978: [SPARK-31127][ML]
Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
zhengruifeng commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-604859600
What about this plan?
1, adding a method to select features by `SelectionResult` in `object SelectionTestResult`:
```scala
private[ml] object SelectionTestResult {
def select(results: Array[SelectionTestResult], selectorType: String, other params: ...): Array[Int] (or Array[(SelectionTestResult, Int)])
}
```
2, moving transformation function into `object ChiSqSelectorModel`, and then reusing it in other classes
```scala
val newSize = selectedFeatures.length
val func = { vector: Vector =>
vector match {
case SparseVector(_, indices, values) =>
val (newIndices, newValues) = compressSparse(indices, values)
Vectors.sparse(newSize, newIndices, newValues)
case DenseVector(values) =>
Vectors.dense(selectedFeatures.map(values))
case other =>
throw new UnsupportedOperationException(
s"Only sparse and dense vectors are supported but got ${other.getClass}.")
}
}
```
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[GitHub] [spark] zhengruifeng edited a comment on issue #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
zhengruifeng edited a comment on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-604859600
What about this plan?
1, adding a method to select features by `SelectionResult` in `object SelectionTestResult`:
```scala
private[ml] object SelectionTestResult {
def select(results: Array[SelectionTestResult], selectorType: String, other params: ...): Array[Int] (or Array[(SelectionTestResult, Int)])
}
```
2, moving transformation function into `object ChiSqSelectorModel`, and then reusing it in other classes
```scala
val newSize = selectedFeatures.length
val func = { vector: Vector =>
vector match {
case SparseVector(_, indices, values) =>
val (newIndices, newValues) = compressSparse(indices, values)
Vectors.sparse(newSize, newIndices, newValues)
case DenseVector(values) =>
Vectors.dense(selectedFeatures.map(values))
case other =>
throw new UnsupportedOperationException(
s"Only sparse and dense vectors are supported but got ${other.getClass}.")
}
}
```
3, for common params like `selectorType`, adding them into shared params?
In this way, there will be no breaking change
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[GitHub] [spark] zhengruifeng edited a comment on issue #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
zhengruifeng edited a comment on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-604857001
It seems that you still need to override setters and getters in subclasses, like
```scala
override def setNumTopFeatures(value: Int): this.type = super.setNumTopFeatures(value)
```
It seems that the main benefit is to avoid copying 1, the transfrom part in subclasses, and 2, choosing features by test results, at the cost of adding several abstract classes. So what about just thoes functions among selection models?
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zhengruifeng edited a comment on issue #27978: [SPARK-31127][ML] Implement abstract Selector
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What about this plan?
1, adding a method to select features by `SelectionResult` in `object SelectionTestResult`:
```scala
private[ml] object SelectionTestResult {
def select(results: Array[SelectionTestResult], selectorType: String, other params: ...): Array[Int] (or Array[(SelectionTestResult, Int)])
}
```
2, moving transformation function into `object ChiSqSelectorModel`, and then reusing it in other classes
```scala
val newSize = selectedFeatures.length
val func = { vector: Vector =>
vector match {
case SparseVector(_, indices, values) =>
val (newIndices, newValues) = compressSparse(indices, values)
Vectors.sparse(newSize, newIndices, newValues)
case DenseVector(values) =>
Vectors.dense(selectedFeatures.map(values))
case other =>
throw new UnsupportedOperationException(
s"Only sparse and dense vectors are supported but got ${other.getClass}.")
}
}
```
In this way, there will be no breaking change
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zhengruifeng edited a comment on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-604857001
It seems that you still need to override setters and getters in subclasses, like
```scala
override def setNumTopFeatures(value: Int): this.type = super.setNumTopFeatures(value)
```
It seems that the main benefit is to avoid copying 1, the transfrom part in subclasses, and 2, choosing features by test results, at the cost of adding several abstract classes. So what about just resuing the transfrom function among selection models?
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Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/27978#issuecomment-604145742
**[Test build #120373 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/120373/testReport)** for PR 27978 at commit [`ba29708`](https://github.com/apache/spark/commit/ba297085d165648896854d06921cd7ee3bb4896b).
* 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 #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
huaxingao commented on a change in pull request #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#discussion_r396063627
##########
File path: mllib/src/main/scala/org/apache/spark/ml/feature/ChiSqSelector.scala
##########
@@ -153,103 +46,69 @@ private[feature] trait ChiSqSelectorParams extends Params
*/
@Since("1.6.0")
final class ChiSqSelector @Since("1.6.0") (@Since("1.6.0") override val uid: String)
- extends Estimator[ChiSqSelectorModel] with ChiSqSelectorParams with DefaultParamsWritable {
+ extends PSelector[ChiSqSelectorModel] {
@Since("1.6.0")
def this() = this(Identifiable.randomUID("chiSqSelector"))
/** @group setParam */
@Since("1.6.0")
- def setNumTopFeatures(value: Int): this.type = set(numTopFeatures, value)
+ override def setNumTopFeatures(value: Int): this.type = super.setNumTopFeatures(value)
/** @group setParam */
@Since("2.1.0")
- def setPercentile(value: Double): this.type = set(percentile, value)
+ override def setPercentile(value: Double): this.type = super.setPercentile(value)
/** @group setParam */
@Since("2.1.0")
- def setFpr(value: Double): this.type = set(fpr, value)
+ override def setFpr(value: Double): this.type = super.setFpr(value)
/** @group setParam */
@Since("2.2.0")
- def setFdr(value: Double): this.type = set(fdr, value)
+ override def setFdr(value: Double): this.type = super.setFdr(value)
/** @group setParam */
@Since("2.2.0")
- def setFwe(value: Double): this.type = set(fwe, value)
+ override def setFwe(value: Double): this.type = super.setFwe(value)
/** @group setParam */
@Since("2.1.0")
- def setSelectorType(value: String): this.type = set(selectorType, value)
+ override def setSelectorType(value: String): this.type = super.setSelectorType(value)
/** @group setParam */
@Since("1.6.0")
- def setFeaturesCol(value: String): this.type = set(featuresCol, value)
+ override def setFeaturesCol(value: String): this.type = super.setFeaturesCol(value)
/** @group setParam */
@Since("1.6.0")
- def setOutputCol(value: String): this.type = set(outputCol, value)
+ override def setOutputCol(value: String): this.type = super.setOutputCol(value)
Review comment:
seems I have to override these methods. Otherwise, I have error like this
```
/Users/hgao/myspark/spark/examples/src/main/java/org/apache/spark/examples/ml/JavaChiSqSelectorExample.java:63: error: incompatible types: Selector<ChiSqSelectorModel> cannot be converted to ChiSqSelector
[error] .setOutputCol("selectedFeatures");
[error] ^
[error] (examples/compile:compileIncremental) javac returned nonzero exit code
```
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Implement abstract Selector
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Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
huaxingao commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-604069829
retest this please
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[GitHub] [spark] srowen commented on a change in pull request #27978:
[SPARK-31127][ML] Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
srowen commented on a change in pull request #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#discussion_r396489569
##########
File path: project/MimaExcludes.scala
##########
@@ -38,7 +38,11 @@ object MimaExcludes {
lazy val v31excludes = v30excludes ++ Seq(
// [SPARK-31077] Remove ChiSqSelector dependency on mllib.ChiSqSelectorModel
// private constructor
- ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this")
+ ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel.this"),
+ // [SPARK-31127] Implement abstract Selector
+ ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.ml.feature.ChiSqSelectorModel"),
Review comment:
The first two seem OK; that won't cause an actual source or binary incompatibility (right?) just because there is an additional class in the hierarchy.
The third one doesn't sound quite right. The type should be ChiSqSelectorModel right? do you have to override it in the subclass like you did with methods in ChiSqSelectorModel? the superclass returns this.type which I thought was 'inherited' and would become ChiSqSelectorModel.
Am I right about that at all, and is there a workaround, or is MiMa incorrect somehow and the type is concretely ChiSqSelectorModel? or is this actually how lots of classes work?
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[GitHub] [spark] huaxingao commented on issue #27978: [SPARK-31127][ML]
Implement abstract Selector
Posted by GitBox <gi...@apache.org>.
huaxingao commented on issue #27978: [SPARK-31127][ML] Implement abstract Selector
URL: https://github.com/apache/spark/pull/27978#issuecomment-602846194
retest this please
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