Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14124
@viirya Thanks for your comment! Actually, that's I want to have some
feedback for from @marmbrus .
It seems forcing to a nullable schema all is already happening when you
read/write da
Github user lins05 commented on a diff in the pull request:
https://github.com/apache/spark/pull/13248#discussion_r70198232
--- Diff: python/pyspark/ml/stat/distribution.py ---
@@ -0,0 +1,267 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+#
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/13778#discussion_r70198204
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/objects/objects.scala
---
@@ -346,14 +346,47 @@ case class LambdaVariable(val
Github user dongjoon-hyun closed the pull request at:
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Github user dongjoon-hyun commented on the issue:
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Hmm. Okay, I didn't prevent all.
I see. I'll close.
Thank you for decision, @cloud-fan .
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Github user cloud-fan commented on the issue:
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```
case Union(children) if children.forall(x =>
x.isInstanceOf[InsertIntoTable] ||
x.isInstanceOf[InsertIntoHadoopFsRelationCommand]) =>
```
This doesn't indicate a muliti-insert righ
Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/14048
Ah, I see. You mean Union of `INSERT INTO`s, right?
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Github user dongjoon-hyun commented on the issue:
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This PR fixes that with minimal efforts.
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/14034
you missed one comment :
https://github.com/apache/spark/pull/14034/files#r70183958 :)
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Github user SparkQA commented on the issue:
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Github user dongjoon-hyun commented on the issue:
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Ur, what do you mean?
> With your patch, we can still create union queries with side effect which
will be executed eagerly.
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Github user dongjoon-hyun commented on the issue:
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The current one looks like this.
```
case Union(children) if children.forall(x =>
x.isInstanceOf[InsertIntoTable] ||
x.isInstanceOf[InsertIntoHadoopFsRelationCommand]) =>
```
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Github user cloud-fan commented on the issue:
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should we wait for https://github.com/apache/spark/pull/14071?
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Github user cloud-fan commented on a diff in the pull request:
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Github user viirya commented on a diff in the pull request:
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--- Diff:
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@@ -346,14 +346,47 @@ case class LambdaVariable(val
Github user cloud-fan commented on a diff in the pull request:
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Github user cloud-fan commented on the issue:
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LGTM, pending jenkins
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retest this please
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Github user viirya commented on a diff in the pull request:
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Github user viirya commented on a diff in the pull request:
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--- Diff:
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@@ -346,14 +346,47 @@ case class LambdaVariable(val
Github user cloud-fan commented on the issue:
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It's good to elimiante the inconsistency, but I don't think there is an
easy fix. With your patch, we can still create union queries with side effect
which will be executed eagerly. We use `Union`
Github user techaddict commented on the issue:
https://github.com/apache/spark/pull/13990
@rxin no need, I will update this today.
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Github user viirya commented on the issue:
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@HyukjinKwon Your patch solves this inconsistency by forcing schema as
nullable at all. However, looks like the parquet case is for compatibility, is
this the same for json?
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/13778#discussion_r70196570
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/objects/objects.scala
---
@@ -346,14 +346,47 @@ case class LambdaVariable(
Github user lw-lin commented on the issue:
https://github.com/apache/spark/pull/14118
I think @HyukjinKwon has made a good point: it's kind of strange null
strings can be written out, but can not be read back as nulls.
So for `StringType`:
nulls writ
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/13778
@cloud-fan I just checked the python UDT. In python side, we will serialize
the python UDT to binary. The python UDT passed to java includes the binary.
Then in python side, in the worker we will des
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14124
I am a bit confused if we are allowed to read JSON (via `json(jsonRDD:
RDD[String])` API) with schema having fields set `false` in `nullable`.
If it is meant to be not allowed, this issue wil
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/14034#discussion_r70194607
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -660,18 +660,51 @@ class SQLQuerySuite extends QueryTest with
SharedSQL
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/14034#discussion_r70194599
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/StatisticsSuite.scala ---
@@ -31,4 +33,46 @@ class StatisticsSuite extends QueryTest with
SharedSQ
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/14034#discussion_r70194595
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/StatisticsSuite.scala ---
@@ -31,4 +33,46 @@ class StatisticsSuite extends QueryTest with
SharedSQ
Github user gatorsmile commented on the issue:
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@HyukjinKwon No matter whether this PR is merged or not, I still think we
should fix the above issue. Silent conversion does not look good to me.
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Github user maropu commented on the issue:
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ping @rxin
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Github user maropu commented on the issue:
https://github.com/apache/spark/pull/13852
Yes. Currently, we have three functions with `supportPartial=false`:
`hive_udaf`, `collect`, and window functions. The former two functions cannot
support this because we do not have byte-backed muta
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Github user AmplabJenkins commented on the issue:
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Can one of the admins verify this patch?
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GitHub user tilumi opened a pull request:
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[SPARK-16280][SQL][WIP] add HistogramNumeric Expression
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70194370
--- Diff: docs/sparkr.md ---
@@ -306,6 +306,64 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset grouping
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/13704#discussion_r70194231
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -2018,6 +2018,8 @@ class Analyzer(
fai
Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/14116
Now, all tests are passed.
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Github user kiszk commented on a diff in the pull request:
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala
---
@@ -479,7 +479,7 @@ case class Cast(child: Expression, dataType
Github user rxin commented on the issue:
https://github.com/apache/spark/pull/13852
Do we have two requirements here?
One is whether an aggregate function supports partial aggregation, and the
other is whether the order should be enforced right ?
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Github user maropu commented on the issue:
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you mean we need two funcs: `supportPartial` and `forceSortAggregate`?
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Github user rxin commented on the issue:
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cc @dongjoon-hyun or @petermaxlee want to take over the pull request and
bring it to completion?
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Github user rxin commented on the issue:
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are we overloading the semantics? I think it's actually useful to have a
supportsPartial, which is what this was for.
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Github user rxin commented on the issue:
https://github.com/apache/spark/pull/13494
@hvanhovell can you take a look at this too?
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14118
IMHO, handling `StringType` at least lets users handling `null`s in
roundtrip in writing and reading. CSV writes `null` according to `nullValue`
[here](https://github.com/apache/spark/blob/38cf8
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/13704#discussion_r70193070
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala
---
@@ -479,7 +479,7 @@ case class Cast(child: Expression, data
GitHub user rxin opened a pull request:
https://github.com/apache/spark/pull/14128
[SPARK-16476] Restructure MimaExcludes for easier union excludes
## What changes were proposed in this pull request?
It is currently fairly difficult to have proper mima excludes when we cut a
ver
Github user asfgit closed the pull request at:
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Github user rxin commented on the issue:
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Thanks - merging in master.
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Github user dongjoon-hyun commented on the issue:
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Thank you for comments! Both comment are tightly related to each other.
I see what is your point. Yep, implicit use of "" string is not a good
idea. I'll fix it again according to the advic
Github user praveendareddy21 commented on a diff in the pull request:
https://github.com/apache/spark/pull/13248#discussion_r70192124
--- Diff: python/pyspark/ml/stat/distribution.py ---
@@ -0,0 +1,267 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or mo
Github user rxin commented on the issue:
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I do feel it'd be useful to be configurable, but go ahead. As you said we
can make it configurable later.
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Github user rxin commented on the issue:
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Thanks for the information. I'm still confused. From an end-user
perspective, do we need to handle StringType there?
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Github user rxin commented on the issue:
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This looks alright.
cc @hvanhovell can you review and merge?
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--- Diff:
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@@ -138,7 +138,7 @@ class CatalogImpl(sparkSession: SparkSession) extends
Github user rxin commented on a diff in the pull request:
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--- Diff:
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---
@@ -423,12 +442,13 @@ class SessionCatalog(
* cont
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Github user HyukjinKwon commented on the issue:
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Oh, I see, before this patch
```
+---+
| a|
+---+
| 1|
| 0|
+---+
```
after this patch
```
++
| a|
++
| 1
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Github user HyukjinKwon commented on the issue:
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Ah, yes it seems a bug to me.. I thought it throws an exception in that
case. Does this PR introduce the problem? (Just curious and to be sure).
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Github user dongjoon-hyun commented on the issue:
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Locally, the last commit passes the R test, too. Now, I think I've finished
my first implementation.
While waiting for #14114 and #14115 , I'll move on other new issues.
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Github user dongjoon-hyun commented on the issue:
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Hi, @rxin .
Could you review this when you have some time?
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After merging this, I'll add the same prevention for `information_schema`,
too.
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Hi, @rxin .
Could you review this again?
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Github user phalodi commented on the issue:
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@srowen @rxin Please review it and give your comments.
 is a change
log of Janino. Updates from 2.7.8 are the followings:
- JANINO-186: Code size error message should include method nam
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Github user phalodi commented on the issue:
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@srowen i make changes as you suggest i remove the table and add a single
below actions table and also change statement to be more clear about non
blocking.
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Github user dongjoon-hyun commented on the issue:
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Thank you, @srowen . It's done!
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https://github.com/apache/spark/pull/14104
@srowen ok no problem so what you suggest should i remove the table and
just add the line below the actions table and give link to scala and java docs?
And the line "Spark provide asynchronous actio
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Thank you for review, @srowen . Currently, the `truncate` option will be
ignored for other non-JDBC sources.
IMO, most of them is **file-based* sources, so they do not need this.
I
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