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Github user shivaram commented on the issue:
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Yeah I am not sure `mvnormalmixEM` is very descriptive. @junyangq Any
opinions on the name here ?
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Github user NarineK commented on the issue:
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yes, @shivaram , that will be one way to do.
Basically, adding a new public function to `RelationalGroupedDataset` which
will return the column names.
If it is fine from SQL perspective,
Github user GraceH commented on a diff in the pull request:
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Github user GraceH commented on the issue:
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Thanks all. I have added the unit test in JDBCWriterSuite. Any further
comment, please feel free to let me know.
BTW, or we can point the user to check JDBCOptions for further
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Github user yinxusen commented on the issue:
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@felixcheung I add some aliases for spark.lda related functions. However, I
am not quite understand it. From
[here](https://cran.r-project.org/web/packages/roxygen2/vignettes/rd.html) I
can see
Github user dongjoon-hyun commented on the issue:
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Hi, @rxin .
I added test files for window functions for SQLQueryTestSuite and removed
the old `WindowQuerySuite.scala`. Could you review this again?
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@shivaram Sure. I will add unit tests.
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Github user viirya commented on the issue:
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@gatorsmile I've made some changes. I will update this soon.
The optimized plan for the query is:
Join Inner
:- Join Inner
: :- CommonSubquery [a#226, b#227,
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Github user junyangq commented on a diff in the pull request:
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--- Diff: R/pkg/R/mllib.R ---
@@ -632,3 +642,159 @@ setMethod("predict", signature(object =
"AFTSurvivalRegressionModel"),
function(object,
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Github user yanboliang commented on the issue:
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@nicklavers Please also change seed for ```GaussianMixture``` doctest in
```python/pyspark/ml/clustering.py```. And check whether we need to change seed
for ```KMeans``` doctest. Thanks.
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GitHub user clockfly opened a pull request:
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[SPARK-16955][SQL] Fix analysis error when using ordinal in ORDER BY or
GROUP BY
## What changes were proposed in this pull request?
This PR adds two unresolved expressions to represent
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Github user SaintBacchus commented on the issue:
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I will re-run this case, and dig into why the executor will double register.
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Can we have this like
[SparkSubmitAction](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L55)
that extends `Enumeration`?
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Github user felixcheung commented on the issue:
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so there are a few competing implementation in R and `mlp` might not be a
super relevant name. @shivaram @mengxr any thought on `spark.mlp` here?
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--- Diff: R/pkg/R/mllib.R ---
@@ -533,6 +626,26 @@ setMethod("write.ml", signature(object =
"KMeansModel", path = "character"),
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--- Diff: R/pkg/R/mllib.R ---
@@ -414,6 +421,92 @@ setMethod("predict", signature(object = "KMeansModel"),
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--- Diff: R/pkg/R/mllib.R ---
@@ -487,7 +580,7 @@ setMethod("write.ml", signature(object =
"NaiveBayesModel", path = "character"),
#' @rdname
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--- Diff: R/pkg/R/DataFrame.R ---
@@ -2121,7 +2121,7 @@ setMethod("arrange",
})
#' @rdname arrange
-#' @name orderBy
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--- Diff: R/pkg/R/mllib.R ---
@@ -53,6 +53,13 @@ setClass("AFTSurvivalRegressionModel",
representation(jobj = "jobj"))
#' @note KMeansModel since
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@@ -292,6 +299,85 @@ setMethod("summary", signature(object =
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Github user yinxusen commented on the issue:
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@felixcheung Yes. Sorry I missed the email.
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--- Diff: R/pkg/R/mllib.R ---
@@ -292,6 +299,83 @@ setMethod("summary", signature(object =
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return(list(apriori =
Github user skonto commented on a diff in the pull request:
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@@ -358,6 +376,109 @@ private[mesos] trait
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Github user zsxwing commented on the issue:
https://github.com/apache/spark/pull/14561
Agreed with @jerryshao. @lshmouse could you submit the whole refactoring
PR in order to show why this one is necessary? It's better to not refactor
stable code paths unless there is a strong
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return(list(apriori =
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return(list(apriori =
Github user shivaram commented on the issue:
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@wangmiao1981 Thanks for the PR. Could we add a couple of test cases for
this ? It'll also help me understand what is the expected behavior -- one of
them could be for `collect` with decimals and
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Github user clockfly commented on the issue:
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I think a proper fix will be marking ordinal unresolved, the ordinal can
exists in group by or order by expression.
Then we can make sure the ResolveAggregateFunctions and other analyzer
Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/14392
btw, I think it'll be great to get some feedback on the naming of this.
As per SPARK-14831, should we go with a more Spark specific name like
`gaussianmixture` rather than a R one? How well
Github user clockfly commented on the issue:
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I think the root cause is that the Aggregate operator is treated as
resolved if even it has group by ordinals.
For example:
```
'Filter ('a > 0)
+- Aggregate [2], [count(1)
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GitHub user robert3005 opened a pull request:
https://github.com/apache/spark/pull/14615
make toJSON not go through rdd form but operate on dataset always
## What changes were proposed in this pull request?
Don't convert toRdd when doing toJSON
## How was this
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Github user dongjoon-hyun commented on the issue:
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I see. Then, I'll include only that today.
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Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/12930
Do we still need this?
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Github user clockfly commented on the issue:
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@dongjoon-hyun The exception was muted by line:
https://github.com/apache/spark/pull/14546/files#diff-57b3d87be744b7d79a9beacf8e5e5eb2R1257
If you add some log message, you wils find
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Github user zsxwing commented on the issue:
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Closing this one. Just found another issue with the current implementation
and will reopen in the future
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GitHub user wangmiao1981 opened a pull request:
https://github.com/apache/spark/pull/14613
[SPARK-16883][SparkR]:SQL decimal type is not properly cast to number when
collecting SparkDataFrame
## What changes were proposed in this pull request?
(Please fill in changes
GitHub user zero323 opened a pull request:
https://github.com/apache/spark/pull/14614
[SPARK-17027][ML] Avoid integer overflow in PolynomialExpansion.getPolySize
## What changes were proposed in this pull request?
Replaces custom choose function with
Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/14571
Oh, I think you are working on that transition somewhere else.
BTW, what about other tests? If you have a plan to enrich
SQLQueryTestSuite, I prefer to do all of them in a single PR during
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Github user yhuai commented on the issue:
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Done
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Github user rxin commented on the issue:
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Do you think you can create a test file for window functions in the new
SQLQueryTestSuite along with this fix?
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