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[SPARK-20395][BUILD] Update Scala to 2.11.11 and zinc to 0.3.15
## What changes were proposed in this pull request?
Update Scala to 2.11.11 and zinc to 0.3.15
## How was this patch
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SPARK-20737 is created to look into cleanup mechanism in a separate JIRA.
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Very gentle ping to @cloud-fan and @mridulm
How do you think about the current change :) ?
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Jenkins, please retest this please
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@viirya Thanks much for your review. I corrected the typo and added some
tests.
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[SPARK-15767][ML][SparkR] Decision Tree wrapper in SparkR
## What changes were proposed in this pull request?
support decision tree in R
## How was this patch tested?
added tes
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Ping @yanboliang
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[SPARK-20728][SQL] Make ORCFileFormat configurable between sql/hive and
sql/core
## What changes were proposed in this pull request?
[SPARK-20682](https://issues.apache.org/jira/brow
Github user viirya commented on a diff in the pull request:
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--- Diff: python/pyspark/ml/feature.py ---
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.
Github user viirya commented on the issue:
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Code changes looks good. But we need to add test for this.
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LGTM
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--- Diff:
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@@ -20,9 +20,12 @@ package org.apache.spark.sql.catalyst.ut
Github user ueshin commented on a diff in the pull request:
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--- Diff:
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@@ -98,6 +101,15 @@ object DateTimeUtils {
sdf
Github user falaki commented on the issue:
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@felixcheung we all know that SparkR (and in general R) API is not perfect
when it comes to ETLing unstructured data. For example we don't have a great
story for nested data, etc. To overcome these l
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@@ -98,6 +101,15 @@ object DateTimeUtils {
sdf
Github user ConeyLiu commented on the issue:
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Yeah, I can test it. You see, the `ALS` is an pratical use case. So,
choose it as a test case more convincing. And I also want to see the
improvement of this `pr` even after merged #17742.
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@@ -98,6 +99,14 @@ object DateTimeUtils {
sdf
Github user zuotingbing commented on the issue:
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Thank you all. Delete the branch.
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Can one of the admins verify this patch?
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GitHub user yanji84 opened a pull request:
https://github.com/apache/spark/pull/17979
[SPARK-19320][MESOS][WIP]allow specifying a hard limit on number of gpus
required in each spark executor when running on mesos
## What changes were proposed in this pull request?
Currently
Github user jtengyp commented on the issue:
https://github.com/apache/spark/pull/17936
I think you@ConeyLiu should directly test the Cartesian phase with the
following patch.
val user = model.userFeatures
val item = model.productFeatures
val start = System.nanoTime()
Github user jtengyp closed the pull request at:
https://github.com/apache/spark/pull/17898
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/17933
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Github user ueshin commented on a diff in the pull request:
https://github.com/apache/spark/pull/17933#discussion_r116396203
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala
---
@@ -98,6 +99,14 @@ object DateTimeUtils {
sdf
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/17924
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Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/17924
Retest this please.
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/17978
(I am not used to ML. I just left a trivial comment for Python.)
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Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/17978#discussion_r116395911
--- Diff: python/pyspark/ml/feature.py ---
@@ -2115,22 +2115,32 @@ class StringIndexer(JavaEstimator, HasInputCol,
HasOutputCol, HasHandleInvalid,
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/17978#discussion_r116395876
--- Diff: python/pyspark/ml/feature.py ---
@@ -2115,22 +2115,32 @@ class StringIndexer(JavaEstimator, HasInputCol,
HasOutputCol, HasHandleInvalid,
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/17848
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/17848
Merged build finished. Test FAILed.
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Github user AmplabJenkins commented on the issue:
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Github user SparkQA commented on the issue:
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