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Posted to reviews@spark.apache.org by zhengruifeng <gi...@git.apache.org> on 2017/08/30 02:05:37 UTC
[GitHub] spark pull request #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer inc...
GitHub user zhengruifeng opened a pull request:
https://github.com/apache/spark/pull/19084
[SPARK-20711][ML]MultivariateOnlineSummarizer incorrect min/max for NaN value
## What changes were proposed in this pull request?
current impl of min/max ignore `NaN`
for a column only containing `NaN`, `Double.MaxValue` will be returned for `min` and `Double.MinValue` will be returned for `max`
min/max for column containing `NaN` should return `NaN`
## How was this patch tested?
existing tests
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/zhengruifeng/spark min_max
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/19084.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 #19084
----
commit f6c75b918dd4fd8848fc22989309e317fc101dc6
Author: Zheng RuiFeng <ru...@foxmail.com>
Date: 2017-08-30T02:01:55Z
create pr
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19084
**[Test build #81240 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/81240/testReport)** for PR 19084 at commit [`f6c75b9`](https://github.com/apache/spark/commit/f6c75b918dd4fd8848fc22989309e317fc101dc6).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19084
**[Test build #84466 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/84466/testReport)** for PR 19084 at commit [`80df3c6`](https://github.com/apache/spark/commit/80df3c69ac58ae5f4190b0b62dd2bdb1cef15260).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Sum...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/19084#discussion_r195429701
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala ---
@@ -117,11 +113,56 @@ class MinMaxScaler @Since("1.5.0") (@Since("1.5.0") override val uid: String)
@Since("2.0.0")
override def fit(dataset: Dataset[_]): MinMaxScalerModel = {
transformSchema(dataset.schema, logging = true)
- val input: RDD[OldVector] = dataset.select($(inputCol)).rdd.map {
- case Row(v: Vector) => OldVectors.fromML(v)
+
--- End diff --
Rather than copy all that code, I wonder if that utility class can just be modified to selectively handle NaN differently?
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on the issue:
https://github.com/apache/spark/pull/19084
@srowen Could you please give a final review? Thanks
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[GitHub] spark pull request #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Sum...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on a diff in the pull request:
https://github.com/apache/spark/pull/19084#discussion_r154897263
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala ---
@@ -117,11 +113,56 @@ class MinMaxScaler @Since("1.5.0") (@Since("1.5.0") override val uid: String)
@Since("2.0.0")
override def fit(dataset: Dataset[_]): MinMaxScalerModel = {
transformSchema(dataset.schema, logging = true)
- val input: RDD[OldVector] = dataset.select($(inputCol)).rdd.map {
- case Row(v: Vector) => OldVectors.fromML(v)
+
--- End diff --
`Statistics.colStats(input)` uses `MultivariateOnlineSummarizer` to compute the max/min which will ignore `Double.NaN`.
I change the behavior of NaN handling in `MultivariateOnlineSummarizer` in this PR, so I have to make another impl of `MinMaxScaler` to keep it behavior.
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19084
Merged build finished. Test FAILed.
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/19084
I tend to agree, because this is how the JDK and Scala behave too. Numpy as well. But not Python, curiously.
I also agree that the existing "handleInvalid" functionality probably needs to be considered. I'm not as sure how that's supposed to interact with this.
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19084
**[Test build #81240 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/81240/testReport)** for PR 19084 at commit [`f6c75b9`](https://github.com/apache/spark/commit/f6c75b918dd4fd8848fc22989309e317fc101dc6).
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on the issue:
https://github.com/apache/spark/pull/19084
`MinMaxScalerSuite` fails because `MinMaxScaler` need the behavior of ignoring `NaN`. So I think there are 2 options:
1, `MultivariateOnlineSummarizer/Summarizer` support param `handleInvaild`;
2, use aggregator instead of `MultivariateOnlineSummarizer` in `MinMaxScaler`
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19084
**[Test build #84466 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/84466/testReport)** for PR 19084 at commit [`80df3c6`](https://github.com/apache/spark/commit/80df3c69ac58ae5f4190b0b62dd2bdb1cef15260).
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19084
Merged build finished. Test PASSed.
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on the issue:
https://github.com/apache/spark/pull/19084
ping @WeichenXu123 @srowen
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[GitHub] spark pull request #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Sum...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng closed the pull request at:
https://github.com/apache/spark/pull/19084
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19084
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[GitHub] spark issue #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Summarizer...
Posted by AmplabJenkins <gi...@git.apache.org>.
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https://github.com/apache/spark/pull/19084
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[GitHub] spark pull request #19084: [SPARK-20711][ML]MultivariateOnlineSummarizer/Sum...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/19084#discussion_r154894819
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala ---
@@ -117,11 +113,56 @@ class MinMaxScaler @Since("1.5.0") (@Since("1.5.0") override val uid: String)
@Since("2.0.0")
override def fit(dataset: Dataset[_]): MinMaxScalerModel = {
transformSchema(dataset.schema, logging = true)
- val input: RDD[OldVector] = dataset.select($(inputCol)).rdd.map {
- case Row(v: Vector) => OldVectors.fromML(v)
+
--- End diff --
Is this code a copy of Statistics.colStats(input) ? how does it differ?
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