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Github user mengxr commented on the pull request:
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@hhbyyh Sorry that I just saw #11954. Please see my comments on the JIRA.
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Github user andrewor14 commented on the pull request:
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Thanks for the reviews. Latest commit should pass tests.
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Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/12271#discussion_r59423143
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveSqlParser.scala
---
@@ -121,84 +123,114 @@ class HiveSqlAstBuilder extends Spar
Github user olarayej commented on the pull request:
https://github.com/apache/spark/pull/11569#issuecomment-209030552
@felixcheung @shivaram This is done. Shall we merge?
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Github user yhuai commented on the pull request:
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LGTM
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@shivaram @falaki @felixcheung @rxin @sun-rui Any thoughts on this?
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LGTM
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--- Diff:
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@@ -121,84 +123,114 @@ class HiveSqlAstBuilder extends SparkSqlA
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/interface.scala
---
@@ -218,14 +219,35 @@ case class CatalogTable(
tableT
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lgtm
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Github user asfgit closed the pull request at:
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Github user marmbrus commented on the pull request:
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Thanks, merging to master.
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala ---
@@ -275,23 +277,64 @@ final class DataFrameWriter private[sql](df:
DataFra
Github user andrewor14 commented on the pull request:
https://github.com/apache/spark/pull/961#issuecomment-209024020
@ouyangshourui this is not at all the same issue. Please file a JIRA with
your stack trace and mark the affected version as 2.0
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Github user mengxr commented on the pull request:
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LGTM. Merged into master. Thanks!
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Github user sitalkedia commented on the pull request:
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@davies - Thanks for the review. I have addressed all the comments, please
let me know how it looks.
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Github user yhuai commented on a diff in the pull request:
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--- Diff:
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@@ -218,14 +219,35 @@ case class CatalogTable(
tableT
Github user rxin commented on the pull request:
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OK updated.
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GitHub user mengxr opened a pull request:
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[SPARK-14563] [ML] use a random table name instead of __THIS__ in
SQLTransformer
## What changes were proposed in this pull request?
Use a random table name instead of `__THIS__` in SQLTran
Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/12247#discussion_r59419309
--- Diff:
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@@ -129,8 +129,17 @@ trait SchemaRelationProvider {
* Implemented b
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Github user zsxwing commented on the pull request:
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The Python APIs looks great.
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
---
@@ -620,6 +620,12 @@ class DatasetSuite extends QueryTest with
SharedSQLConte
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GitHub user dongjoon-hyun opened a pull request:
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[MINOR][SQL] Re-enable `explode()` and `json_tuple()` testcases in
ExpressionToSQLSuite
## What changes were proposed in this pull request?
Since [SPARK-12719: SQL Generation support
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--- Diff:
common/network-common/src/main/java/org/apache/spark/network/client/TransportClientFactory.java
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@@ -149,25 +148,31 @@ public TransportClient c
Github user brkyvz commented on the pull request:
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cc @zsxwing
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Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/12312#issuecomment-209011439
Hi, @rxin . Sorry for late response.
I added comments and changed the testcase name according to your comments.
Thank you for review!
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Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/11989#issuecomment-209008233
@yongtang Sorry that I just found this was merged. I think it might be
better to use `Int.parseInt` and `parseDouble` instead of regexes, which is
less robust. For examp
Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/12312#discussion_r59412120
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/LikeSimplificationSuite.scala
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@@ -61,6 +61,20 @@ class LikeSimplific
Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff:
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---
@@ -529,6 +530,9 @@ object LikeSimplification extend
Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/12280#issuecomment-209004510
Thank you, @rxin and @srowen !
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cc @sameeragarwal
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[SPARK-14562] [SQL] improve constraints propagation in Union
## What changes were proposed in this pull request?
Currently, Union only takes intersect of the constraints from it's
children,
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Github user nongli commented on a diff in the pull request:
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lgtm
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Github user Kinghack commented on the pull request:
https://github.com/apache/spark/pull/9306#issuecomment-208981407
since latest version of jets3t does not build into latest spark. Is it
possible for now that I could access s3 file from regions that supports
AWS4-HMAC-SHA256 only?
Github user holdenk commented on the pull request:
https://github.com/apache/spark/pull/12079#issuecomment-208974760
@BryanCutler / @yongtang That sounds reasonable :)
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> @holdenk @BryanCutler we could merge this and #12308, and then update the
param to be shared (if we can do the different doc thing?).
I think that will be
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Github user holdenk commented on the pull request:
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@viirya - I think having consistent accumulators only be consistent inside
some of the Spark operations might be a little confusing, although that's also
where I starte
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Github user viirya commented on the pull request:
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I am thinking that if we can support the semantics that the accumulator
updates in anyone RDD will not be recounted. Is it already enough? So we don't
need to complicate
Github user hhbyyh commented on the pull request:
https://github.com/apache/spark/pull/12325#issuecomment-208952622
Good idea. Thanks. I'll update the title.
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Github user MLnick commented on the pull request:
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Not strictly necessary to have a JIRA, but is this essentially a follow up
to [SPARK-14154] (https://issues.apache.org/jira/browse/SPARK-14154)? In which
case maybe just
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LGTM. Merged to master. Thanks @yongtang and also @sethah for reviewing!
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Github user squito commented on the pull request:
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+1 on "data property" instead of consistent
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LGTM
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retest this please
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Github user hash-X commented on the pull request:
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@hhbyyh
WOW, I have been finding how to impute missing values in spark project
lately. LGTM. Thank you.
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