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LGTM pending tests
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--- Diff: python/pyspark/__init__.py ---
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indent_p = re.compile(r'\n( +)')
def deco(f):
+
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The executor here may be a little misleading. It means the python worker
rather than the spark executor.
Python worker get its env from PythonRDD and PythonRDD get th
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/StreamTest.scala ---
@@ -95,20 +89,18 @@ trait StreamTest extends QueryTest with Timeouts {
/
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retest this please.
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/StreamTest.scala ---
@@ -67,12 +67,6 @@ import org.apache.spark.util.Utils
*/
trait StreamTest
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def awai
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[SPARK-14833][SQL][STREAMING][TEST] Refactor StreamTests to test for source
fault-tolerance correctly.
## What changes were proposed in this pull request?
Current StreamTest allows testing of
Github user yhuai commented on the pull request:
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LGTM
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looks good except 1 minor doc comment
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Github user HyukjinKwon commented on the pull request:
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@viirya @davies Could I ask your thought on this? I can make a JIRA for
this.
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Merging in master.
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cc @liancheng to take another look
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[SPARK-14832][SQL][STREAMING]
## What changes were proposed in this pull request?
When creating a file stream using sqlContext.write.stream(), existing files
are scanned twice for finding th
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/r/MapPartitionsRWrapper.scala
---
@@ -0,0 +1,62 @@
+/*
+ * Licensed to the Apac
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Github user jodersky commented on the pull request:
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Fair enough, test:compile is alright too. I would just avoid compile:compile
On Apr 21, 2016 5:48 PM, "Reynold Xin" wrote:
> hm most people don't run packa
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/12493#discussion_r60677594
--- Diff: R/pkg/inst/worker/worker.R ---
@@ -84,6 +84,10 @@ broadcastElap <- elapsedSecs()
# as number of partitions to create.
numPartitions <-
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/12493#discussion_r60677525
--- Diff: R/pkg/R/generics.R ---
@@ -439,6 +439,10 @@ setGeneric("covar_samp", function(col1, col2)
{standardGeneric("covar_samp") })
#' @export
setGe
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--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala
---
@@ -259,4 +261,78 @@ class InsertIntoHiveTableSuite extends
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Github user zhengruifeng commented on the pull request:
https://github.com/apache/spark/pull/12578#issuecomment-213184521
@rxin It is said in
[JIRA](https://issues.apache.org/jira/browse/SPARK-10496) that window function
is not efficient for a large number of rows in this problem. @jk
Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/DataFrame.R ---
@@ -1137,11 +1137,22 @@ setMethod("summarize",
#' @rdname dapply
#' @name dapply
#' @export
+#' @exam
Github user rxin commented on the pull request:
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hm most people don't run package and just compile or test:compile, so
adding it there would reduce the gain.
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Github user marmbrus commented on the pull request:
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Yeah, if there are problems we don't have to do that, but `val df =
spark.read.json(...)` is pretty nice
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@mathieulongtin
I think it might be more sensible that SQL in OPTIONS clause supports
`null` and some other types such as long, double and boolean. It
[looks]
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Merging in master.
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Github user dongjoon-hyun commented on the pull request:
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Hi, @rxin and @marmbrus .
How do you think about the updated PR? It's just first update.
If there is something to do more, please let me know.
Thank you
Github user andrewor14 commented on the pull request:
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LGTM2
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Github user jodersky commented on the pull request:
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Hmm, maybe you need to add the project or config too? As in "set
lintOnCompile in project in Config := true"? Sbt isn't too friendly when
setting command line options
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@@ -414,8 +414,42 @@ class Analyzer(
}
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}
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LGTM. Merged into master. Thanks!
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}
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--- Diff:
mllib/src/main/scala/org/apache/spark/ml/r/NaiveBayesWrapper.scala ---
@@ -74,4 +83,41 @@ private[r] object NaiveBayesWrapper {
.fit(data
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`cacheSize1` and `cacheSize2` are both the size after cleaning. The
difference is that, `cacheSize1` is the size after cleaned the data with line
object reference, `c
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Github user cloud-fan commented on the pull request:
https://github.com/apache/spark/pull/12575#issuecomment-213169619
Can you add a test case to expose this bug?
And I think a better way to fix this bug is to remove the alias only
project, but not stop the optimization.
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Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/12573#discussion_r60675421
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/r/NaiveBayesWrapper.scala ---
@@ -74,4 +83,41 @@ private[r] object NaiveBayesWrapper {
.fit
Github user holdenk commented on the pull request:
https://github.com/apache/spark/pull/6848#issuecomment-213169287
@koertkuipers now days we try and provide a description for our pull
request (sometimes it can be copied from the JIRA) for the eventual commit
message - it might be goo
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12589#issuecomment-213168922
**[Test build #56616 has
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/56616/consoleFull)**
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[`45783de`](https://gi
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/11569#discussion_r60675031
--- Diff: R/pkg/R/DataFrame.R ---
@@ -2465,6 +2465,110 @@ setMethod("drop",
base::drop(x)
})
+#' This function c
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/6848#issuecomment-213168019
Merged build finished. Test PASSed.
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Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/12402#issuecomment-213167994
The current plan of supporting gaussiansDF for now and gaussians later (in
Python) sounds good. @wangmiao1981 Thanks for the updates; I had some more
comments.
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Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/12402#discussion_r60674866
--- Diff: python/pyspark/ml/clustering.py ---
@@ -20,9 +20,150 @@
from pyspark.ml.wrapper import JavaEstimator, JavaModel
from pyspark.ml.param.sh
Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/12402#discussion_r60674864
--- Diff: python/pyspark/ml/clustering.py ---
@@ -20,9 +20,150 @@
from pyspark.ml.wrapper import JavaEstimator, JavaModel
from pyspark.ml.param.sh
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/6848#issuecomment-213168022
Test PASSed.
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Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/12402#discussion_r60674858
--- Diff: python/pyspark/ml/clustering.py ---
@@ -20,9 +20,150 @@
from pyspark.ml.wrapper import JavaEstimator, JavaModel
from pyspark.ml.param.sh
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12527#issuecomment-213167863
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