Github user aray commented on the issue:
https://github.com/apache/spark/pull/21699
Using either `Column` or `String` type was actually in my original PR:
https://github.com/apache/spark/pull/7841
@rxin later modified the api to only take a `String` prior to the release
as part
Github user aray commented on the issue:
https://github.com/apache/spark/pull/21187
LGTM thanks for doing this!
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/19629
diff LGTM
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Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18306#discussion_r143345713
--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -562,6 +563,8 @@ class SparkContext(config: SparkConf) extends Logging
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/19226#discussion_r138917350
--- Diff: python/pyspark/serializers.py ---
@@ -343,6 +343,8 @@ def _load_stream_without_unbatching(self, stream):
key_batch_stream
Github user aray commented on the issue:
https://github.com/apache/spark/pull/19226
@holdenk I'm not going to be able to solve this tonight (short of just
removing the failing test).
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/19226
It's actually this one that is failing
https://github.com/aray/spark/blob/0d64a6d11237383c2a6ea21275dc9daa5cc8d634/python/pyspark/tests.py#L964
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/19226
[SPARK-21985][PySpark] PairDeserializer is broken for double-zipped RDDs
## What changes were proposed in this pull request?
This removes the mostly unnecessary test that each individual
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16121
I'll take a look, sorry about that.
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Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18306#discussion_r136436631
--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -562,6 +563,8 @@ class SparkContext(config: SparkConf) extends Logging
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18818#discussion_r136421644
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
---
@@ -582,6 +582,7 @@ class CodegenContext
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/19080#discussion_r136419947
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala
---
@@ -284,24 +241,17 @@ case class RangePartitioning
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18306
ping @zsxwing
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/18818
ping @viirya @gatorsmile
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GitHub user aray reopened a pull request:
https://github.com/apache/spark/pull/18786
[SPARK-21584][SQL][SparkR] Update R method for summary to call new
implementation
## What changes were proposed in this pull request?
SPARK-21100 introduced a new `summary` method
Github user aray closed the pull request at:
https://github.com/apache/spark/pull/18786
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/18786
closing and reopening to trigger AppVeyor test that timed out
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/18818
@viirya @gatorsmile I have addressed your comments, could you take another
look.
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Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18818#discussion_r133116720
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
---
@@ -465,7 +475,7 @@ abstract class BinaryComparison
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18818
retest this please
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/18786
I'm pushing for it to stay as is because it's the more logical layout of
the data: min=0%, 25%, 50%, 75%, max=100%. It's also more consistent with
summary of native R dataframes (and for Python
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18306
@zsxwing can you take another look at this?
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/18786
@rxin Any thoughts on whether it's ok to change the output of `summary` in
R in a non "additive" way?
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Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18818#discussion_r131913185
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
---
@@ -453,6 +453,14 @@ case class Or(left: Expression
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18818#discussion_r131808912
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
---
@@ -453,6 +453,14 @@ case class Or(left: Expression
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18818#discussion_r131656840
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/types/AbstractDataType.scala
---
@@ -79,18 +79,6 @@ private[sql] class TypeCollection(private val
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18835
Thanks, I see it now.
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Github user aray closed the pull request at:
https://github.com/apache/spark/pull/18835
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18835
[SPARK-21628][BUILD] Explicitly specify Java version in maven compiler
plugin so IntelliJ imports project correctly
## What changes were proposed in this pull request?
Explicitly specify
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18786
No the changes to `summary` are not additive, it inserts 25%, 50%, and 75%
percentiles before max (the last row). People that want the previous behavior
can use `describe`. Or if they are trying
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18818
[SPARK-21110][SQL] Structs, arrays, and other orderable datatypes should be
usable in inequalities
## What changes were proposed in this pull request?
Allows `BinaryComparison` operators
GitHub user aray reopened a pull request:
https://github.com/apache/spark/pull/18786
[SPARK-21584][SQL][SparkR] Update R method for summary to call new
implementation
## What changes were proposed in this pull request?
SPARK-21100 introduced a new `summary` method
Github user aray closed the pull request at:
https://github.com/apache/spark/pull/18786
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18800
[SPARK-21330][SQL] Bad partitioning does not allow to read a JDBC table
with extreme values on the partition column
## What changes were proposed in this pull request?
An overflow
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18786#discussion_r130620399
--- Diff: R/pkg/R/DataFrame.R ---
@@ -2973,15 +2974,51 @@ setMethod("describe",
dataFrame(sdf)
})
+
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18786#discussion_r130618566
--- Diff: R/pkg/tests/fulltests/test_sparkSQL.R ---
@@ -2500,8 +2500,15 @@ test_that("describe() and summarize() on a
DataFrame", {
ex
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18786
[SPARK-21584][SQL][SparkR] Update R method for summary to call new
implementation
## What changes were proposed in this pull request?
SPARK-21100 introduced a new `summary` method
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18697
@viirya We could certainly make that improvement. I believe it would be a
fairly trivial change to this PR if we were just considering expressions that
have the same canonical representation. However
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18697#discussion_r130396904
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala ---
@@ -65,6 +65,10 @@ abstract class SparkPlan extends QueryPlan[SparkPlan
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18762
retest this please
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18762
[SPARK-21566][SQL][Python] Python method for summary
## What changes were proposed in this pull request?
Adds the recently added `summary` method to the python dataframe interface
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18697
ping @rxin can someone look at this correctness fix?
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/16577
Closing since it does not look like there is any interest in changing this.
Thanks everyone!
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Github user aray closed the pull request at:
https://github.com/apache/spark/pull/16577
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/18697
retest this please
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/18697
Plan for the example query before the patch (with partitioning as suffix):
```
*HashAggregate(keys=[parent#228], functions=[], output=[level2#274])
hashpartitioning(parent#228, 5
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18697
[SPARK-16683][SQL] Repeated joins to same table can leak attributes via
partitioning
## What changes were proposed in this pull request?
In some complex queries where the same table
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18306
ping @rxin @marmbrus @zsxwing @felixcheung can anyone look at this?
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Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18307#discussion_r125053122
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -2205,37 +2205,170 @@ class Dataset[T] private[sql](
* // max 92.0
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18307
@rxin @felixcheung Thanks for the feedback, I revamped this PR to leave
`describe` unchanged and added two new methods `describeExtended` and
`describeAdvanced` (the latter is used to implement all
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18306
@zsxwing @marmbrus @rxin This is ready for review. I have changed the
approach so that queries from all SparkSession's are stopped. I was not able to
use a SparkListener as @zsxwing suggested or even
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18307
@rxin Yes it slows things down quite a bit. Informal testing on 10M row 2
column synthetic data puts this implementation at around 10s vs 0.5s in
2.2-rc4. I can speed it up some by doing only a single
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/18306#discussion_r122112073
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala
---
@@ -690,6 +690,7 @@ class SparkSession private(
* @since 2.0.0
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18307
[SPARK-21100][SQL] describe should give quartiles similar to Pandas
## What changes were proposed in this pull request?
Modify the describe method to include quartiles (25th, 50th, and 75th
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18306
[SPARK-21029][SS] All StreamingQuery should be stopped when the
SparkSession is stopped
## What changes were proposed in this pull request?
Adds method to `StreamingQueryManager` that stops
Github user aray commented on the issue:
https://github.com/apache/spark/pull/18001
Yes, it does not work without
```
Andrews-MacBook-Pro:spark-2.1.1-bin-hadoop2.7 andrew$ jupyter --version
4.0.6
Andrews-MacBook-Pro:spark-2.1.1-bin-hadoop2.7 andrew
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/18001
[SPARK-20769][Doc] Incorrect documentation for using Jupyter notebook
## What changes were proposed in this pull request?
SPARK-13973 incorrectly removed the required
Github user aray commented on the issue:
https://github.com/apache/spark/pull/17348
LGTM
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/16483
@thunterdb The extra step -- as implemented -- is only at the end as that
gives the same result as doing it after every iteration but without the extra
overhead.
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Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/16483#discussion_r106548090
--- Diff:
graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala ---
@@ -68,26 +69,34 @@ class PageRankSuite extends SparkFunSuite
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/16483#discussion_r106546448
--- Diff: graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala
---
@@ -322,13 +335,12 @@ object PageRank extends Logging {
def
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16483
@rxin can anyone else review this? It would be nice to get this correctness
fix into 2.2.
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/17226
@HyukjinKwon There is an inconsistency/regression but its not being
introduced in this PR, its already there. Take an example without null as a
pivot column value like below. The only difference
Github user aray commented on the issue:
https://github.com/apache/spark/pull/17226
@HyukjinKwon we're not introducing a regression in this PR by fixing the
NPE, the answer given by 1.6 was incorrect under any interpenetration. Again,
there is a completely separate issue of what
Github user aray commented on the issue:
https://github.com/apache/spark/pull/17226
BTW for 3 above if we decide it should be 0, we can add an initial value
for `PivotFirst` to make the fix.
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/17226
There are three things going on here in your one example.
1. Spark 1.6 [first version with pivot] (and Spark 2.0+ with an aggregate
output type unsupported by PivotFirst) gives incorrect
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/17226#discussion_r105324124
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -522,7 +522,7 @@ class Analyzer(
} else
Github user aray commented on the issue:
https://github.com/apache/spark/pull/17226
@HyukjinKwon As stated in 17226#discussion_r105322758 I think we should
open a second JIRA to have the discussion on whether or not count(1) of no
values in a pivot should be filled with 0's
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/17226#discussion_r105322758
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFramePivotSuite.scala ---
@@ -216,4 +216,10 @@ class DataFramePivotSuite extends QueryTest
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/17226
[SPARK-19882][SQL] Pivot with null as a distinct pivot value throws NPE
## What changes were proposed in this pull request?
Allows null values of the pivot column to be included in the pivot
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/15415#discussion_r97168170
--- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala ---
@@ -0,0 +1,251 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/15415#discussion_r97162464
--- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala ---
@@ -0,0 +1,251 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/15415#discussion_r97168311
--- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala ---
@@ -0,0 +1,251 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/15415#discussion_r97166816
--- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala ---
@@ -0,0 +1,251 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF
Github user aray closed the pull request at:
https://github.com/apache/spark/pull/16539
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/16483
@rxin can you take a look?
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16577
[SPARK-19214][SQL] Typed aggregate count output field name should be "count"
## What changes were proposed in this pull request?
Changes the output field name of typed aggreg
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16559
It can already be done with the `posexplode` UDTF like
```
with t as (values (array(1,2,3)), (array(4,5,6)) as (a))
select col from t lateral view posexplode(a) tt where pos = 2
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16555
The title should say 2.
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16539
[SPARK-8855][MLlib][PySpark] Python API for Association Rules
## What changes were proposed in this pull request?
This patch adds a `generateAssociationRules(confidence)` method
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16483
ping @srowen @ankurdave can you take a look at this?
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16483
[SPARK-18847][GraphX] PageRank gives incorrect results for graphs with sinks
## What changes were proposed in this pull request?
Graphs with sinks (vertices with no outgoing edges) don't have
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16271
Yes the improvement is from the sum of magnitudes of initial values being
closer to the (known) sum of the solution. Fiddling with resetProb controls a
completely different thing. The current
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/16271#discussion_r92621591
--- Diff:
graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala ---
@@ -70,10 +70,10 @@ class PageRankSuite extends SparkFunSuite
Github user aray commented on a diff in the pull request:
https://github.com/apache/spark/pull/16240#discussion_r92546082
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SQLImplicits.scala
---
@@ -100,31 +100,76 @@ abstract class SQLImplicits {
// Seqs
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16271
**References**
[Pagerank paper](http://ilpubs.stanford.edu:8090/422/1/1999-66.pdf)
> We need to make an initial assignment of the ranks. This assignment can
be made by one of several strateg
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16271
ping @srowen @dbtsai @rxin @ankurdave @jegonzal
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/16271
Updated the above benchmark code with a log normal random graph on 10,000
vertices the difference is much more drastic.
(take the very bottom of the graph
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16271
[SPARK-18845][GraphX] PageRank has incorrect initialization value that
leads to slow convergence
## What changes were proposed in this pull request?
Change the initial value in all PageRank
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16161
I would be happy to create a seperate PR for adding support for
`mutable.Map` (and `List`) if that is wanted. But there is no _generic_
solution as there is no type that is assignable to both
Github user aray closed the pull request at:
https://github.com/apache/spark/pull/16197
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16197
[SPARK-17760][SQL][Backport] AnalysisException with dataframe pivot when
groupBy column is not attribute
## What changes were proposed in this pull request?
Backport of #16177 to branch-2.0
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16161
Right now it's not supported to have the following:
```
case class Foo(a: Map[Int, Int])
```
(using the scala Predef version of Map)
The
[documented](http://spark.apache.org
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16177
[SPARK-17760][SQL] AnalysisException with dataframe pivot when groupBy
column is not attribute
## What changes were proposed in this pull request?
Fixes AnalysisException for pivot queries
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16161
The approach is to change the deserializer (via
`ScalaReflection#deserializerFor`) to return the more specific type
`scala.collections.immutable.Map` instead of `scala.collections.Map` as it does
now
GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16161
[SPARK-18717][SQL] Make code generation for Scala Map work with
immutable.Map also
## What changes were proposed in this pull request?
Fixes compile errors in generated code when user has
Github user aray commented on the issue:
https://github.com/apache/spark/pull/16121
@davies, @zero323, and @holdenk this is in a good place for review if you
want to take a look.
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Github user aray commented on the issue:
https://github.com/apache/spark/pull/16121
@davies I was trying to make minimal changes to `PairDeserializer`, but you
are right it needs changed also. I'll update the PR shortly.
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GitHub user aray opened a pull request:
https://github.com/apache/spark/pull/16121
[SPARK-16589][PYTHON] Chained cartesian produces incorrect number of records
## What changes were proposed in this pull request?
Fixes a bug in the python implementation of rdd cartesian
Github user aray commented on the issue:
https://github.com/apache/spark/pull/15898
@tejasapatil yes that is the use case where this applies. It's only tested
against whatever version is included in the hadoop2.7+hive build configuration
listed above. Is there anything in particular
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