[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user MLnick commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221836656 LGTM, merged to master/branch-2.0. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user wangmiao1981 commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221681098 @MLnick Done. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user wangmiao1981 commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221670964 @MLnick Sure. I will do it soon. Now, I am debugging a R bug. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user MLnick commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221668080 @wangmiao1981 could you do the same for the `OneVsRestExample`? ie remove `DataFrame` type annotation and import. You can do that in this PR. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user wangmiao1981 commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221345524 @jerryshao We are going through the examples one by one now. In last a few weeks, we have many of these fixed. The intention is making the examples as consistent and easy as possible for users who are new to ML. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user MLnick commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221270507 I disagree that it's "too trivial to fix" for this specific case, because (i) it actually makes the example code included in the ML User Guide inconsistent with **all** other example code in the guide, and (ii) it doesn't work if you try to copy-paste it into the spark-shell (these guide examples should really work for that case). Also, no other User Guide example code (for Scala) explicitly imports `DataFrame` - as you can see that import is not part of the `include_example` section that goes into the User Guide (nor should it be). But it's a fair point to fix any other examples - `OneVsRestExample` is the only other one I found that should be fixed up. There are others (such as the "application" examples for random forest, linear regression etc), but they are not in the user guide so it doesn't matter much for those. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user jerryshao commented on the pull request:
https://github.com/apache/spark/pull/13266#issuecomment-221259849
Since you already did this copy, why not copy this line `import
org.apache.spark.sql.{DataFrame, SparkSession}`? IMHO, I think it is too
trivial to fix. Also if you want to fix it, I guess other examples also might
have such explicit type declaration, why not do a whole fix?
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user MLnick commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221187975 I agree in normal cases we could leave it as it's not a "bug" per se. In this case however, as the examples are intended to be runnable as copy-pastes into spark-shell, we should fix this. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/13266#discussion_r64340139
--- Diff:
examples/src/main/scala/org/apache/spark/examples/ml/BinarizerExample.scala ---
@@ -31,7 +31,7 @@ object BinarizerExample {
.getOrCreate()
// $example on$
val data = Array((0, 0.1), (1, 0.8), (2, 0.2))
-val dataFrame: DataFrame = spark.createDataFrame(data).toDF("label",
"feature")
+val dataFrame = spark.createDataFrame(data).toDF("label", "feature")
--- End diff --
Since you're removing the type annotation, you can remove the import of
`DataFrame` also.
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user wangmiao1981 commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221168009 @jerryshao We have several similar bugs fixed. I am doing QA for ML 2.0 document now. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
Github user jerryshao commented on the pull request: https://github.com/apache/spark/pull/13266#issuecomment-221154991 I'm wondering is it a bug need to be fixed? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
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[GitHub] spark pull request: [SPARK-15492][ML][DOC]:Binarization scala exam...
GitHub user wangmiao1981 opened a pull request:
https://github.com/apache/spark/pull/13266
[SPARK-15492][ML][DOC]:Binarization scala example copy & paste to
spark-shell error
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
The Binarization scala example val dataFrame : Dataframe =
spark.createDataFrame(data).toDF("label", "feature"), which can't be pasted in
the spark-shell as Dataframe is not imported. Compared with other examples,
this explicit type is not required.
So I removed Dataframe in the code.
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration
tests, manual tests)
Manually tested
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/wangmiao1981/spark unit
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/13266.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 #13266
commit df29feb9644e3617eff3f561998f26e0977f23ed
Author: wm...@hotmail.com
Date: 2016-05-23T21:48:15Z
remove type Dataframe
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