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Github user codingjaguar commented on the pull request:
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In last change we deleted `equivalentPredicate` and moved the
functionality to `Expression.semanticEquals`.
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--- Diff:
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@@ -50,27 +50,33 @@ class ParquetFilter
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Github user sun-rui commented on the pull request:
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also could you state in the method description that subset parameter is
optional?
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--- Diff: R/pkg/R/DataFrame.R ---
@@ -1206,10 +1206,15 @@ setMethod("[", signature(x = "DataFrame", i =
"Column"),
#' df[df$age %in% c(19, 30), 1:2]
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Github user dragos closed the pull request at:
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Github user HyukjinKwon commented on the pull request:
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Just a question. Now it looks the PR for the end-to-end docker tests is
merged. Do you think it needs all the tests for all the databases (namely
`MySQLIntegrationS
Github user dragos commented on the pull request:
https://github.com/apache/spark/pull/9824#issuecomment-163141839
@jodersky, I didn't see you PR and opened #10199. I think it makes sense to
push yours and close mine, but it would be good to treat errors and stop
execution in that cas
Github user dragos commented on the pull request:
https://github.com/apache/spark/pull/10199#issuecomment-163141579
Oh, I missed that one. Yes, it's the same. I also show errors if any of the
arguments doesn't parse, and stop execution in that case, but there's no reason
this can't go
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/10221
[SPARK-12236][SQL] JDBC filter tests all pass if filters are not really
pushed down
https://issues.apache.org/jira/browse/SPARK-12236
Currently JDBC filters are not tested properly. All the
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Github user liancheng commented on a diff in the pull request:
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--- Diff:
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@@ -359,10 +359,27 @@ case class LambdaVariable(value: S
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--- Diff: R/pkg/R/DataFrame.R ---
@@ -1209,7 +1209,11 @@ setMethod("[", signature(x = "DataFrame", i =
"Column"),
#' }
setMethod("subset", sign
Github user felixcheung commented on the pull request:
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cool, looks good
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Github user yinxusen commented on the pull request:
https://github.com/apache/spark/pull/10219#issuecomment-163138018
Ping @mengxr, this is for SPARK-11551. Please sign it off if looks good to
you.
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Github user asfgit closed the pull request at:
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GitHub user sun-rui opened a pull request:
https://github.com/apache/spark/pull/10220
[SPARK-12235][SPARKR] Enhance mutate() to support replace existing columns.
Make the behavior of mutate more consistent with that in dplyr, besides
support for replacing existing columns.
1. Th
Github user liancheng commented on the pull request:
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Thanks for working on this! Merging to master. (Actually I thought I've
already merged this one.)
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@@ -50,27 +50,33 @@ class ParquetFilterSu
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Github user BenFradet commented on a diff in the pull request:
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--- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/Encoder.scala ---
@@ -19,20 +19,60 @@ package org.apache.spark.sql
import java.lang.re
Github user liancheng commented on the pull request:
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@yinxusen Well, I'm probably too ignorant to review #10219 :) I'd ping
@mengxr to sign it off.
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Github user yinxusen commented on the pull request:
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@somideshmukh Never mind, I add a new one on behalf of you:
https://github.com/apache/spark/pull/10219 @liancheng if it looks good to you,
please help me merge it afte
Github user yinxusen commented on the pull request:
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ok to test
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GitHub user yinxusen opened a pull request:
https://github.com/apache/spark/pull/10219
[SPARK-11551][DOC] Replace example code in ml-features.md using
include_example
PR on behalf of @somideshmukh, thanks!
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GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/10218
[SPARK-12227][SQL] Support drop multiple columns specified by Column class
in DataFrame API
https://issues.apache.org/jira/browse/SPARK-12227
In this PR, I added the support to drop mu
Github user somideshmukh commented on the pull request:
https://github.com/apache/spark/pull/10002#issuecomment-163128740
Please let me know what needs to be done,I have not worked on python code.
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Sure, I will do it
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/10217
[SPARK-12234] [SparkR] Fix subset error when only set select argument
Fix subset error when only set ```select``` argument.
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Github user liancheng commented on the pull request:
https://github.com/apache/spark/pull/10002#issuecomment-163126528
@yinxusen Maybe you can fork this PR branch and get it merged. You may add
a note in your PR description to remind committers to attribute your PR to
@somideshmukh. W
Github user yinxusen commented on the pull request:
https://github.com/apache/spark/pull/10002#issuecomment-163123743
@somideshmukh Do you still have time work on this? Pleas let me know ASAP
thanks.
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Github user windscope commented on the pull request:
https://github.com/apache/spark/pull/10163#issuecomment-163121275
To improve semanticEquals, we tried to implement a template function
`Expression.splitWithCommutativeOperator[T: Manifest](): Seq[Expression]` so
that we don't need t
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Github user asfgit closed the pull request at:
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Github user davies commented on the pull request:
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LGTM, merging into master and 1.6, thanks!
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Github user davies commented on the pull request:
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Sending to master should be enough, will be pickled into 1.6.
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Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/10201#discussion_r47052792
--- Diff: R/pkg/R/DataFrame.R ---
@@ -2223,3 +2215,43 @@ setMethod("with",
newEnv <- assignNewEnv(data)
eval(substitute(
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/10201#discussion_r47052771
--- Diff: R/pkg/R/generics.R ---
@@ -421,6 +421,10 @@ setGeneric("corr", function(x, ...)
{standardGeneric("corr") })
#' @export
setGeneric("de
Github user jayantshekhar commented on the pull request:
https://github.com/apache/spark/pull/8972#issuecomment-163110967
Still pondering over it and would luv to get inputs here.
Do we create a Param of Vector Array and use it as the initialModel?
clusterCenters in org.apache
Github user felixcheung commented on the pull request:
https://github.com/apache/spark/pull/10191#issuecomment-163110182
looks good.
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Github user felixcheung commented on the pull request:
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sorry that's unrelated to this PR. Opened SPARK-12224 and SPARK-12232
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Github user holdenk commented on the pull request:
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@jkbradley addressed the issues (also cleaned up the rest of the tests in
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GitHub user holdenk opened a pull request:
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[SPARK-10509][PYSPARK] Reduce excessive param boiler plate code
The current python ml params require cut-and-pasting the param setup and
description between the class & ```__init__``` methods. Remo
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