Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19588
@hhbyyh comments addressed. Thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19621
Jenkins, test this please.
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GitHub user WeichenXu123 reopened a pull request:
https://github.com/apache/spark/pull/19350
[SPARK-22126][ML] Fix model-specific optimization support for ML tuning
## What changes were proposed in this pull request?
Push down fitting parallelization code from
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19641
retest this please.
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19586
We can config the class to register by config
`spark.kryo.classesToRegister`, does it need to add into spark code
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19586
and in `ml`, if we want to register class before running algos, Some other
classes like `LabeledPoint`, `Instance` also need registered.
and there're some class temporary defined in
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19208#discussion_r148926895
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -117,6 +123,12 @@ class CrossValidator @Since("1.2.0"
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19661
So why do you include the class such as
`org.apache.spark.ml.feature.Instance`.
You can look into a lot of algos, in `ml` package (not `mllib`), still use
something like `RDD[Instance
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19661
And I don't know whether these class dependency injection into spark-core
lib is reasonable ...
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17000
@MLnick It looks like VF-LBFGS has a different scenario. In VF algos, the
vectors will be too large to store in driver memory, so we slice the vectors
into different machines (stored by `RDD
GitHub user WeichenXu123 opened a pull request:
https://github.com/apache/spark/pull/19666
[SPARK-22451][ML] Reduce decision tree aggregate size for unordered
features from O(2^numCategories) to O(numCategories)
## What changes were proposed in this pull request?
We do not
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/16864
@jiangxb1987 yes I agree to close it.
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19208#discussion_r149269770
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala ---
@@ -101,6 +101,20 @@ class TrainValidationSplit @Since("
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19666#discussion_r149274660
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala ---
@@ -976,6 +930,44 @@ private[spark] object RandomForest extends
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19666
@smurching I guess if iterating over gray code will have higher time
complexity O(n * 2^n), (Not very sure, maybe there's some high efficient
algos?) , the recursive traverse in my PR
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19020
LGTM. thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19662
Looks reasonable, have you check other places which have similar issue ?
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19685#discussion_r149554146
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -289,9 +289,11 @@ class ALSModel private[ml] (
private
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19685
Have you made some test to check the performance difference for this ?
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19666
@facaiy Thanks for your review! I put more explanation on the design
purpose of `traverseUnorderedSplits`. But, if you have better solution, no
hesitate to tell me
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19666
Also cc @smurching Thanks!
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19666#discussion_r149561550
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala ---
@@ -741,17 +678,43 @@ private[spark] object RandomForest extends
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19565
ok I agree this change. @jkbradley Can you take a look ?
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19666#discussion_r149567340
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala ---
@@ -631,6 +614,42 @@ class RandomForestSuite extends
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19662#discussion_r149567769
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala ---
@@ -126,4 +126,25 @@ class VectorAssemblerSuite
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19156#discussion_r149854985
--- Diff: mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala ---
@@ -94,46 +97,86 @@ object Summarizer extends Logging {
* - min
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19156#discussion_r149855295
--- Diff: mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala ---
@@ -197,14 +240,14 @@ private[ml] object SummaryBuilderImpl extends
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19156#discussion_r149893125
--- Diff: mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala ---
@@ -94,46 +97,86 @@ object Summarizer extends Logging {
* - min
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19156#discussion_r149941345
--- Diff: mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala ---
@@ -94,46 +98,87 @@ object Summarizer extends Logging {
* - min
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19156#discussion_r149956415
--- Diff: mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala ---
@@ -527,27 +570,28 @@ private[ml] object SummaryBuilderImpl extends
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19666
@facaiy Your idea looks also reasonable. So we can use the condition
"exclude the first bin" to do the pruning (filter out the other half symmetric
splits). This condition looks si
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/15770
LGTM. ping @yanboliang
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18624#discussion_r150170451
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
---
@@ -286,40 +288,119 @@ object
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/18624
But, I agree the issue @MLnick mentioned, the code now looks convoluted,
can you try to simplify it ?
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19588#discussion_r150445283
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala ---
@@ -37,7 +38,25 @@ import org.apache.spark.sql.types.{StructField
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/17972#discussion_r150470524
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -129,7 +129,7 @@ private[recommendation] trait ALSModelParams
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19525#discussion_r150486465
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/linalg/JsonMatrixConverter.scala ---
@@ -0,0 +1,79 @@
+/*
+ * Licensed to the Apache
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19525#discussion_r150482756
--- Diff:
mllib-local/src/main/scala/org/apache/spark/ml/linalg/Matrices.scala ---
@@ -476,6 +476,10 @@ class DenseMatrix @Since("
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19666
OK. I will waiting @smurching to merge split parts of #19433 get merged
first, and then I will update this PR.
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19208#discussion_r150731403
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala ---
@@ -177,7 +202,9 @@ class TrainValidationSplit @Since("
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17972
Have you checked other algorithms which can also apply this parameter ?
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19208
I manually tested backwards compatibility and it works fine. I paste the
test code for `CrossValidator` here.
Run following code in spark-2.2 shell first:
```
import
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19208
Jenkins, test this please.
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19588#discussion_r150760733
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala ---
@@ -311,22 +346,39 @@ class VectorIndexerModel private[ml
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19588#discussion_r150761099
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala ---
@@ -311,22 +346,39 @@ class VectorIndexerModel private[ml
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19588#discussion_r150771136
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala ---
@@ -311,22 +342,39 @@ class VectorIndexerModel private[ml
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19588
Sure, I will add python api after this is merged.
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19621
@viirya @MLnick Thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19588
Python API jira created here:
https://issues.apache.org/jira/browse/SPARK-22521
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GitHub user WeichenXu123 opened a pull request:
https://github.com/apache/spark/pull/19753
[SPARK-22521][ML] VectorIndexerModel support handle unseen categories via
handleInvalid: Python API
## What changes were proposed in this pull request?
Add python api for
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19588#discussion_r151055221
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala ---
@@ -311,22 +346,39 @@ class VectorIndexerModel private[ml
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19621
I want to ask, for option `StringIndexer.frequencyDesc`, in the case
existing two labels which have the same frequency, which of them will be put in
the front ?
If this is not specified
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19753
@smurching The getter/setter is included in the super class
`HasHandleInvalid`. I can add test for it.
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19753#discussion_r151311569
--- Diff: python/pyspark/ml/feature.py ---
@@ -2565,22 +2575,28 @@ class VectorIndexer(JavaEstimator, HasInputCol,
HasOutputCol, JavaMLReadable, Ja
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19753#discussion_r151311832
--- Diff: python/pyspark/ml/feature.py ---
@@ -2565,22 +2575,28 @@ class VectorIndexer(JavaEstimator, HasInputCol,
HasOutputCol, JavaMLReadable, Ja
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19627
My local test passed. This test failure looks like test system issue.
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19152
@marktab You should close merged PR. Thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17819
ok to test.
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19229
@viirya I guess the reason is, the old PR version:
`df.withColumn(..).withColumn(..).withColumn(..)`, the long df chain
prevent the shuffle re-using... but now you merge them into one step
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19229
Great! That's it. thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17819
@viirya Yes. But if there is some better design I will be happy to listen.
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17819
@viirya It is possible I think. A similar example is, `HasRegParam` trait,
do not put `setRegParam` in trait but moved into concrete estimator/transformer
class, should be the same reason
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19229
Looks not the reason. maybe issues somewhere else. Let me run test later.
Thanks!
But there is some small issues in test:
Don't include gen data time:
```
val
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19229
@viirya I run the code, you're right, most of time cost on the executedPlan
generation (The old version code). thanks!
But can you append benchmark comparison with `RDD.aggregate` ve
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18924#discussion_r139470472
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -462,31 +462,44 @@ final class OnlineLDAOptimizer extends
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18924#discussion_r139467949
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -462,31 +462,44 @@ final class OnlineLDAOptimizer extends
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19229
@viirya No, keep the dataframe version code. But I only want to confirm how
much performance gap between this and RDD version. (for possible improvements
in the future, because in similar test
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/16774
OK. I will separate a PR. Thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17819
@viirya Scala `with trait` is a complex mechanism and `trait` isn't
equivalent to java's `interface`. Scala compiler will precompile and generate
many other codes, so java-side c
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19208
@smurching Thanks! I will update later. And note that I will separate part
of this PR to a new PR (the separated part will be a bugfix for #16774
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17819
@viirya Oh, I am not saying the compatibility against old version scala
application. What I say is about new version `Bucketizer`, when spark user use
java language(not scala language), call
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17819
Yes you can only move `setInputCols` into the outer class to resolve this
issue. But I prefer merge it together. I think we can unify the `transform`
method. (First we check param `inputCol
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19229
Oh. That's what have done in the old PR #18902 .(Because the RDD version
(not in master branch, only personal impl here (sorry for put wrong link, the
code link is here:
https://githu
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19186
@zhengruifeng You should write a design doc succinctly and link to jira
first. After we reach agreement with the design this PR can move forward.
Thanks
GitHub user WeichenXu123 opened a pull request:
https://github.com/apache/spark/pull/19278
[SPARK-22060][ML] Fix CrossValidator/TrainValidationSplit param
persist/load bug
## What changes were proposed in this pull request?
Currently the param of CrossValidator
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19278
cc @BryanCutler Thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/12066
@yanboliang Are you still working on this ?
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19106
Jenkins, test this please.
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19278#discussion_r139854853
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -283,6 +282,8 @@ object CrossValidatorModel extends
MLReadable
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19278#discussion_r139854872
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala ---
@@ -122,7 +123,7 @@ class TrainValidationSplit @Since("
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19278#discussion_r139854984
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -212,14 +213,12 @@ object CrossValidator extends
MLReadable
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19278#discussion_r139855087
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -303,16 +304,16 @@ object CrossValidatorModel extends
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19278
@BryanCutler The reason I add `skipParams` is that, if we don't use
`DefaultParamReader.getAndSetParams`, we have to hardcoding all params which
are very troublesome. And every time we ad
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19208
@smurching I will update this PR after #19278 merged. Because now this PR
depend on that one. Thanks!
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/17819
@MLnick Yea, you're right, only move `setXXX` to concrete class also work
fine. The root cause is the `setXXX` return type. But I think the multi /
single logic can be merged, because s
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19229
@viirya Thanks very much! Although the perf gap exists (when numCols is
large), it won't block this PR. I will create a JIRA to track
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18924#discussion_r140111453
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -503,17 +518,15 @@ final class OnlineLDAOptimizer extends
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19288
OK I agree.
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Github user WeichenXu123 commented on the issue:
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ping @srowen Any other comments ?
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/14325
You should override `override def evaluate(dataset: Dataset[_])` (without
the label param).
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/14325
ping @gatorsmile Add this to test.
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https://github.com/apache/spark/pull/18924#discussion_r140188363
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -503,17 +518,15 @@ final class OnlineLDAOptimizer extends
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18924#discussion_r140249325
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -503,17 +518,15 @@ final class OnlineLDAOptimizer extends
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19278#discussion_r140398857
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
---
@@ -160,11 +160,13 @@ class TrainValidationSplitSuite
Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19278#discussion_r140398933
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala ---
@@ -159,12 +159,15 @@ class CrossValidatorSuite
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19279
cc @srowen Can you help close this ?
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/13794
cc @srowen Can you help close this ? We won't need this feature for now.
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Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19122#discussion_r140402700
--- Diff: python/pyspark/ml/tests.py ---
@@ -836,6 +836,27 @@ def test_save_load_simple_estimator(self):
loadedModel
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19278
@jkbradley Sure I tested the backwards compatibility. Part of the reason I
changed into `DefaultParamReader.getAndSetParams` is for backwards
compatibility
Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/19156
@cloud-fan Can you help review the part of code which related to SQL
interface ?
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