Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/4520#discussion_r24507150
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -282,6 +279,29 @@ class Analyzer(catalog: Catalog,
Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/4520#discussion_r24507183
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -282,6 +279,29 @@ class Analyzer(catalog: Catalog,
Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/4520#discussion_r24507245
--- Diff: sql/core/src/test/resources/log4j.properties ---
@@ -37,7 +37,10 @@ log4j.appender.FA.Threshold = INFO
# Some packages are noisy
Github user chenghao-intel commented on the pull request:
https://github.com/apache/spark/pull/4520#issuecomment-73911621
LGTM in general except some of the minor issues.
My original thought on this, is adding a new `Project` on top of the
`MultiInstanceRelation`(if it
Github user SparkQA commented on the pull request:
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--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala ---
@@ -248,7 +249,7 @@ private[hive] object HadoopTableReader extends
Github user mengxr commented on a diff in the pull request:
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
Github user mengxr commented on a diff in the pull request:
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--- Diff: docs/mllib-dimensionality-reduction.md ---
@@ -157,6 +157,23 @@ val pc: Matrix = mat.computePrincipalComponents(10) //
Principal components are
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/4304#discussion_r24511400
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
Github user adrian-wang commented on the pull request:
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ok to test.
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Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/4521#discussion_r24512284
--- Diff: python/pyspark/sql.py ---
@@ -605,6 +605,10 @@ def _infer_type(obj):
dataType = _type_mappings.get(type(obj))
if dataType is
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/4521#issuecomment-73920542
@dondrake After adding a comment, I think it's ready to go.
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Github user andrewor14 commented on the pull request:
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ok to test. Thanks for working on this!
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Github user mengxr commented on a diff in the pull request:
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
Github user mengxr commented on a diff in the pull request:
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
Github user mengxr commented on a diff in the pull request:
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
Github user mengxr commented on a diff in the pull request:
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--- Diff: docs/mllib-feature-extraction.md ---
@@ -370,3 +370,58 @@ data2 = labels.zip(normalizer2.transform(features))
{% endhighlight %}
/div
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/4304#discussion_r24511414
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/feature/PCASuite.scala ---
@@ -0,0 +1,47 @@
+/*
+ * Licensed to the Apache Software Foundation
Github user mengxr commented on a diff in the pull request:
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF)
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--- Diff: docs/mllib-dimensionality-reduction.md ---
@@ -157,6 +157,23 @@ val pc: Matrix = mat.computePrincipalComponents(10) //
Principal components are
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Github user yhuai commented on the pull request:
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ok to test
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Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/4527#issuecomment-73925301
Also, can you add performance numbers?
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Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/4533#issuecomment-73907037
Looking at the implementation, the driver does query one partition at a
time for the number of elements it thinks it needs and continues until it is
satisfied. I'd
Github user darabos commented on the pull request:
https://github.com/apache/spark/pull/4533#issuecomment-73910087
Oh, thanks. I never looked into how `allowLocal` works.
Looks like it results in local execution if the number of affected
partitions is 1
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Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/4527#issuecomment-73924548
Thank you for working on it.
Seems `new SpecificMutableRow(schema.fields.map(_.dataType))` cannot handle
nested structure. I think we need to use the schema to
Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/4533#issuecomment-73925690
Sounds correct. The subsequent tries do try in parallel. So, I suppose
that's pretty good evidence it's parallelized. Unless anyone else speaks up I
think this sentence
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/4528#discussion_r24517268
--- Diff: python/pyspark/sql/context.py ---
@@ -294,9 +303,9 @@ def applySchema(self, rdd, schema):
df =
Github user javadba commented on a diff in the pull request:
https://github.com/apache/spark/pull/4495#discussion_r24521887
--- Diff:
examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
---
@@ -0,0 +1,149 @@
+/*
+ * Licensed to
Github user javadba commented on a diff in the pull request:
https://github.com/apache/spark/pull/4495#discussion_r24521948
--- Diff:
examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
---
@@ -0,0 +1,149 @@
+/*
+ * Licensed to
Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/4528#discussion_r24515956
--- Diff: python/pyspark/sql/context.py ---
@@ -294,9 +303,9 @@ def applySchema(self, rdd, schema):
df =
Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/4528#issuecomment-73929153
For functions taking a table name as an input parameter, can we make the
parameter name consistent in this PR? There are a few places in Python where we
call it `name`.
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Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/4460#issuecomment-73927224
@mengxr Great, that helps me. I took another shot at implementing the above
ideas.
- Is package `org.apache.spark.ml.attribute` reasonable?
- `FeatureType`
Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/4530#issuecomment-73934772
Hive isn't even consistent across versions for this...
Also, SQL has a well defined concept for data missing, `null`. Given that,
I don't think we should use a
Github user javadba commented on a diff in the pull request:
https://github.com/apache/spark/pull/4495#discussion_r24519073
--- Diff:
examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
---
@@ -0,0 +1,149 @@
+/*
+ * Licensed to
Github user javadba commented on a diff in the pull request:
https://github.com/apache/spark/pull/4495#discussion_r24519062
--- Diff:
examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
---
@@ -0,0 +1,149 @@
+/*
+ * Licensed to
Github user markhamstra commented on the pull request:
https://github.com/apache/spark/pull/4534#issuecomment-73936918
Thanks for doing this, but the title of this PR isn't sufficient. It will
become the commit log message, so please update the PR title to adequately
describe what
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/4534#discussion_r24520320
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -1253,9 +1253,9 @@ abstract class RDD[T: ClassTag](
/**
* @return true
Github user markhamstra commented on the pull request:
https://github.com/apache/spark/pull/4534#issuecomment-73940039
@tbertelsen Better, but you still should include SPARK-5744 and add [CORE]
to the PR title.
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GitHub user zapletal-martin opened a pull request:
https://github.com/apache/spark/pull/4535
§Spark 5502
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Alternatively you can review and apply
Github user zapletal-martin closed the pull request at:
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Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/4527#issuecomment-73927673
Oh, `enforceCorrectType` will take care inner structures by calling
`asRow`.
It will be great if we can use mutable rows for inner structures as well.
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Github user davies commented on the pull request:
https://github.com/apache/spark/pull/4528#issuecomment-73933395
@yhuai We're trying our best to have the same API between Scala, Java and
Python, but sometimes we can't, because the difference between languages. For
those out of
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Github user helena commented on the pull request:
https://github.com/apache/spark/pull/3631#issuecomment-73938104
@koeninger this is a definite blocker for me, I'm upgrading the connector
to scala 2.11 with a cross build. Let me know if you have time, otherwise I
will get back to
Github user tbertelsen commented on the pull request:
https://github.com/apache/spark/pull/4534#issuecomment-73940991
Sorry. Is is good now?
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Github user markhamstra commented on the pull request:
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perfect
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--- Diff:
examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
---
@@ -0,0 +1,149 @@
+/*
+ * Licensed to
Github user javadba commented on a diff in the pull request:
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@@ -0,0 +1,149 @@
+/*
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Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/4528#discussion_r24518769
--- Diff: python/pyspark/sql/types.py ---
@@ -188,6 +199,8 @@ class IntegerType(PrimitiveType):
The data type representing int values.
Github user javadba commented on a diff in the pull request:
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+/*
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Can one of the admins verify this patch?
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Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/4534#issuecomment-73946196
This works, so it's not quite empty partitions:
```
sc.parallelize(Seq[Int](), 1).isEmpty()
```
This also creates an exception, so it's to do with
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/4530#issuecomment-73932469
This is technically API breaking - and if we want to change it, I think N/A
is a better word. @marmbrus @mengxr ?
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+/*
+ * Licensed to
Github user tbertelsen commented on a diff in the pull request:
https://github.com/apache/spark/pull/4534#discussion_r24521457
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -1253,9 +1253,9 @@ abstract class RDD[T: ClassTag](
/**
* @return
Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/4425#discussion_r24525418
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -69,6 +69,7 @@ class Analyzer(catalog: Catalog,
Github user javadba commented on a diff in the pull request:
https://github.com/apache/spark/pull/4495#discussion_r24518525
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@@ -0,0 +1,149 @@
+/*
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Github user tbertelsen commented on the pull request:
https://github.com/apache/spark/pull/4534#issuecomment-73935576
FYI: The method was introduced in https://github.com/apache/spark/pull/4074
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GitHub user tbertelsen opened a pull request:
https://github.com/apache/spark/pull/4534
Fixing SPARK-5744.
RDD.isEmpty fails when an RDD contains empty partitions.
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Github user tbertelsen commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -1253,9 +1253,9 @@ abstract class RDD[T: ClassTag](
/**
* @return
Github user dondrake commented on the pull request:
https://github.com/apache/spark/pull/4521#issuecomment-73884346
@rxin I updated the title of the pull request.
@davies In regards to inferSchema(), this is a PR for v1.2, I'm going to
submit another PR for 1.3 that will use
Github user GenTang commented on the pull request:
https://github.com/apache/spark/pull/3920#issuecomment-73889175
@davies @MLnick
Perhaps it is not a good place to discuss this, but I tried the script
hbase_outputformat.py in spark 1.2.0 and it caused
Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/4527#discussion_r24503655
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
---
@@ -39,7 +39,19 @@ private[sql] object JsonRDD extends Logging {
GitHub user darabos opened a pull request:
https://github.com/apache/spark/pull/4533
Remove outdated remark about take(n).
Looking at the code, I believe this remark about `take(n)` computing
partitions on the driver is no longer correct. Apologies if I'm wrong.
This came
Github user GenTang commented on a diff in the pull request:
https://github.com/apache/spark/pull/3920#discussion_r24495658
--- Diff:
examples/src/main/scala/org/apache/spark/examples/pythonconverters/HBaseConverters.scala
---
@@ -23,15 +23,27 @@ import
Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/4527#discussion_r24504239
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
---
@@ -39,7 +39,19 @@ private[sql] object JsonRDD extends Logging {
Github user asfgit closed the pull request at:
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--- Diff:
core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala ---
@@ -413,10 +413,13 @@ private[spark] class SparkSubmitArguments(args:
Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/4527#discussion_r24503309
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
---
@@ -39,7 +39,19 @@ private[sql] object JsonRDD extends Logging {
Github user AmplabJenkins commented on the pull request:
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Can one of the admins verify this patch?
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GitHub user zapletal-martin opened a pull request:
https://github.com/apache/spark/pull/4536
[MLLIB][SPARK-5502] User guide for isotonic regression
User guide for isotonic regression added to docs/mllib-regression.md
including code examples for Scala and Java.
You can merge this
Github user helena commented on a diff in the pull request:
https://github.com/apache/spark/pull/4406#discussion_r24527030
--- Diff:
sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
---
@@ -35,7 +37,7 @@ import
Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/4537#issuecomment-73960395
ok to test
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Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/4538#issuecomment-73961331
ok to test
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Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/4536#issuecomment-73961955
@zapletal-martin My bad. It should be `mllib-classification-regression.md`.
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Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/4524#discussion_r24531964
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala
---
@@ -128,6 +128,29 @@ abstract class LogicalPlan extends
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/4524
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Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/4536#discussion_r24532955
--- Diff: data/mllib/sample_isotonic_regression_data.csv ---
@@ -0,0 +1,101 @@
+4710.28,500.00,1.00
--- End diff --
Btw, we can use `.txt`
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