[GitHub] [spark] AmplabJenkins removed a comment on issue #24428: [SPARK-27532][Doc] Correct the default value in the Documentation for "spark.redaction.regex"

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[GitHub] [spark] shivusondur opened a new pull request #24428: [SPARK-27532][Doc] Correct the default value in the Documentation for "spark.redaction.regex"

2019-04-20 Thread GitBox
shivusondur opened a new pull request #24428: [SPARK-27532][Doc] Correct the 
default value in the Documentation for "spark.redaction.regex"
URL: https://github.com/apache/spark/pull/24428
 
 
   ## What changes were proposed in this pull request?
   
   Corrected the default value in the Documentation for "spark.redaction.regex" 
   
   ## How was this patch tested?
   
   NA
   


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[GitHub] [spark] wangyum closed pull request #24422: [SPARK-27524][BUILD] Remove the parquet-provided support

2019-04-20 Thread GitBox
wangyum closed pull request #24422: [SPARK-27524][BUILD] Remove the 
parquet-provided support
URL: https://github.com/apache/spark/pull/24422
 
 
   


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[GitHub] [spark] felixcheung commented on issue #24422: [SPARK-27524][BUILD] Remove the parquet-provided support

2019-04-20 Thread GitBox
felixcheung commented on issue #24422: [SPARK-27524][BUILD] Remove the 
parquet-provided support
URL: https://github.com/apache/spark/pull/24422#issuecomment-485209159
 
 
   I don't know that's confusing? ML model is persisted in parquet format.


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[GitHub] [spark] AmplabJenkins commented on issue #24427: [SPARK-27531] Improve `EXPLAIN DESC TABLE` to show the input parameters of the command.

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[GitHub] [spark] dilipbiswal opened a new pull request #24427: [SPARK-27531] Improve explain output of describe table command to show the inputs to the command.

2019-04-20 Thread GitBox
dilipbiswal opened a new pull request #24427: [SPARK-27531] Improve explain 
output of describe table command to show the inputs to the command.
URL: https://github.com/apache/spark/pull/24427
 
 
   ## What changes were proposed in this pull request?
   Currently "EXPLAIN DESC TABLE" is special cased and outputs a single row 
relation as following. This is not consistent with how we handle explain 
processing for other commands. 
   
   Current output:
   ```
   spark-sql> EXPLAIN DESCRIBE TABLE t1;
   == Physical Plan ==
   *(1) Scan OneRowRelation[]
   ```
   After change:
   ```
   spark-sql> EXPLAIN DESC EXTENDED t
   == Physical Plan ==
   Execute DescribeTableCommand
  +- DescribeTableCommand `t`, true
   ```
   ## How was this patch tested?
   Added new tests in SQLQueryTestSuite.


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[GitHub] [spark] AmplabJenkins commented on issue #24426: [SPARK-26970][PYTHON] Add Spark ML interaction transformer to PySpark

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[GitHub] [spark] AmplabJenkins commented on issue #24426: [SPARK-26970][PYTHON] Add Spark ML interaction transformer to PySpark

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[GitHub] [spark] SparkQA commented on issue #24387: [SPARK-27473][SQL] Support filter push down for status fields in binary file data source

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[GitHub] [spark] mengxr commented on issue #24387: [SPARK-27473][SQL] Support filter push down for status fields in binary file data source

2019-04-20 Thread GitBox
mengxr commented on issue #24387: [SPARK-27473][SQL] Support filter push down 
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URL: https://github.com/apache/spark/pull/24387#issuecomment-485151324
 
 
   LGTM pending Jenkins. @cloud-fan Do you want to make a pass?


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[GitHub] [spark] Andrew-Crosby opened a new pull request #24426: [SPARK-26970][PYTHON] Add Spark ML interaction transformer to PySpark

2019-04-20 Thread GitBox
Andrew-Crosby opened a new pull request #24426: [SPARK-26970][PYTHON] Add Spark 
ML interaction transformer to PySpark
URL: https://github.com/apache/spark/pull/24426
 
 
   ## What changes were proposed in this pull request?
   
   Adds the Spark ML Interaction transformer to PySpark
   
   (I've set the version added to 1.6.0 to match the Scala code. Not certain if 
that's the right thing to do.)
   
   ## How was this patch tested?
   
   - Added Python doctest
   - Ran the newly added example code
   - Manually confirmed that a PipelineModel that contains an Interaction 
transformer can now be loaded in PySpark


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[GitHub] [spark] mengxr commented on issue #24387: [SPARK-27473][SQL] Support filter push down for status fields in binary file data source

2019-04-20 Thread GitBox
mengxr commented on issue #24387: [SPARK-27473][SQL] Support filter push down 
for status fields in binary file data source
URL: https://github.com/apache/spark/pull/24387#issuecomment-485151267
 
 
   @WeichenXu123 I pushed some changes to your branch that added more tests.


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[GitHub] [spark] SparkQA commented on issue #24387: [SPARK-27473][SQL] Support filter push down for status fields in binary file data source

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[GitHub] [spark] SparkQA commented on issue #24387: [SPARK-27473][SQL] Support filter push down for status fields in binary file data source

2019-04-20 Thread GitBox
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URL: https://github.com/apache/spark/pull/24387#issuecomment-485148134
 
 
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[GitHub] [spark] WeichenXu123 commented on issue #24387: [SPARK-27473][SQL] Support filter push down for status fields in binary file data source

2019-04-20 Thread GitBox
WeichenXu123 commented on issue #24387: [SPARK-27473][SQL] Support filter push 
down for status fields in binary file data source
URL: https://github.com/apache/spark/pull/24387#issuecomment-485148092
 
 
   Thanks @mengxr 's update! Looks good to me.


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[GitHub] [spark] SparkQA commented on issue #24424: [SPARK-27527][SQL][DOCS] Improve descriptions of Timestamp and Date types

2019-04-20 Thread GitBox
SparkQA commented on issue #24424: [SPARK-27527][SQL][DOCS] Improve 
descriptions of Timestamp and Date types
URL: https://github.com/apache/spark/pull/24424#issuecomment-485139257
 
 
   **[Test build #104774 has 
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/104774/testReport)**
 for PR 24424 at commit 
[`a759fa4`](https://github.com/apache/spark/commit/a759fa4672f076c141b6a6df69f07dd5ab6dfd93).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] srowen commented on issue #24270: [SPARK-27343][KAFKA][SS]Avoid hardcoded for spark-sql-kafka-0-10

2019-04-20 Thread GitBox
srowen commented on issue #24270: [SPARK-27343][KAFKA][SS]Avoid hardcoded for 
spark-sql-kafka-0-10
URL: https://github.com/apache/spark/pull/24270#issuecomment-485135378
 
 
   @gaborgsomogyi what do you think at this point?


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[GitHub] [spark] srowen commented on issue #24423: [SPARK-27525][SQL] Exclude commons-httpclient when interacting with different versions of the HiveMetastoreClient

2019-04-20 Thread GitBox
srowen commented on issue #24423: [SPARK-27525][SQL] Exclude commons-httpclient 
when interacting with different versions of the HiveMetastoreClient
URL: https://github.com/apache/spark/pull/24423#issuecomment-485135339
 
 
   Hm, you're saying this makes something _not_ work or is that a typo?
   Why does it fail to download? that seems like the issue. Can we exclude this 
if it's used?


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[GitHub] [spark] beliefer commented on issue #24372: [SPARK-27462][SQL] Enhance insert into hive table that could choose some columns in target table flexibly.

2019-04-20 Thread GitBox
beliefer commented on issue #24372: [SPARK-27462][SQL] Enhance insert into hive 
table that could choose some columns in target table flexibly.
URL: https://github.com/apache/spark/pull/24372#issuecomment-485132519
 
 
   cc @cloud-fan


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[GitHub] [spark] beliefer removed a comment on issue #24372: [SPARK-27462][SQL] Enhance insert into hive table that could choose some columns in target table flexibly.

2019-04-20 Thread GitBox
beliefer removed a comment on issue #24372: [SPARK-27462][SQL] Enhance insert 
into hive table that could choose some columns in target table flexibly.
URL: https://github.com/apache/spark/pull/24372#issuecomment-484741363
 
 
   @srowen @cloud-fan @maropu  @HyukjinKwon 
   Could you help me review this PR? Thanks.


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[GitHub] [spark] beliefer removed a comment on issue #24372: [SPARK-27462][SQL] Enhance insert into hive table that could choose some columns in target table flexibly.

2019-04-20 Thread GitBox
beliefer removed a comment on issue #24372: [SPARK-27462][SQL] Enhance insert 
into hive table that could choose some columns in target table flexibly.
URL: https://github.com/apache/spark/pull/24372#issuecomment-484914038
 
 
   @srowen Could you make this PR to test? Thanks.


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
AmplabJenkins removed a comment on issue #24425: [WIP][SPARK-27528][SQL] Use 
Parquet logical type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425#issuecomment-485131329
 
 
   Can one of the admins verify this patch?


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[GitHub] [spark] SparkQA commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
SparkQA commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical 
type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425#issuecomment-485131796
 
 
   **[Test build #104775 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/104775/testReport)**
 for PR 24425 at commit 
[`0edfed2`](https://github.com/apache/spark/commit/0edfed2361c4eb41e851f1c4057c44867c91d3d0).


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
AmplabJenkins removed a comment on issue #24425: [WIP][SPARK-27528][SQL] Use 
Parquet logical type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425#issuecomment-485131531
 
 
   Merged build finished. Test PASSed.


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
AmplabJenkins removed a comment on issue #24425: [WIP][SPARK-27528][SQL] Use 
Parquet logical type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425#issuecomment-485131533
 
 
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[GitHub] [spark] AmplabJenkins commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
AmplabJenkins commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet 
logical type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425#issuecomment-485131531
 
 
   Merged build finished. Test PASSed.


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[GitHub] [spark] AmplabJenkins commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
AmplabJenkins commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet 
logical type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425#issuecomment-485131533
 
 
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[GitHub] [spark] AmplabJenkins commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
AmplabJenkins commented on issue #24425: [WIP][SPARK-27528][SQL] Use Parquet 
logical type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425#issuecomment-485131329
 
 
   Can one of the admins verify this patch?


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[GitHub] [spark] MaxGekk opened a new pull request #24425: [WIP][SPARK-27528][SQL] Use Parquet logical type TIMESTAMP_MICROS by default

2019-04-20 Thread GitBox
MaxGekk opened a new pull request #24425: [WIP][SPARK-27528][SQL] Use Parquet 
logical type TIMESTAMP_MICROS by default
URL: https://github.com/apache/spark/pull/24425
 
 
   ## What changes were proposed in this pull request?
   
   In the PR, I propose to use the `TIMESTAMP_MICROS` logical type for 
timestamps written to parquet files. The type matches semantically to 
Catalyst's `TimestampType`, and stores microseconds since epoch in UTC time 
zone. This will allow to avoid conversions of microseconds to nanoseconds and 
to Julian calendar. Also this will reduce sizes of written parquet files.
   
   ## How was this patch tested?
   
   By existing test suites.


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[GitHub] [spark] tgravescs commented on issue #24371: [SPARK-27176][FOLLOW-UP][SQL] Shade Parquet to sql/core

2019-04-20 Thread GitBox
tgravescs commented on issue #24371: [SPARK-27176][FOLLOW-UP][SQL] Shade 
Parquet to sql/core
URL: https://github.com/apache/spark/pull/24371#issuecomment-485119568
 
 
   Sorry I guess this addresses shading but not hive factorization not working


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[GitHub] [spark] SparkQA commented on issue #24424: [SPARK-27527][SQL][DOCS] Improve descriptions of Timestamp and Date types

2019-04-20 Thread GitBox
SparkQA commented on issue #24424: [SPARK-27527][SQL][DOCS] Improve 
descriptions of Timestamp and Date types
URL: https://github.com/apache/spark/pull/24424#issuecomment-485117285
 
 
   **[Test build #104774 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/104774/testReport)**
 for PR 24424 at commit 
[`a759fa4`](https://github.com/apache/spark/commit/a759fa4672f076c141b6a6df69f07dd5ab6dfd93).


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