GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/13771
[SPARK-13748][PYSPARK][DOC] Add the description for explictly setting None
for a named argument for ROW
## What changes were proposed in this pull request?
It seems allowed
Github user HyukjinKwon closed the pull request at:
https://github.com/apache/spark/pull/13725
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13759
cc @cloud-fan Could you please take a look maybe? I remember renaming
`SqlNewHadoopRDDState` to `InputFileNameHolder` was reviewed by you.
---
If your project is set up for it, you can reply
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13725
I am closing this as this is merged. Thank you @mengxr again!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/13759
[SPARK-16044][SQL] input_file_name() returns empty strings in data sources
based on NewHadoopRDD
## What changes were proposed in this pull request?
This PR makes `input_file_name
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13771
Hi @davies, it seems related codes were written by you. Would this be a
meaningful change?
---
If your project is set up for it, you can reply to this email and have your
reply appear
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/13866#discussion_r68209882
--- Diff:
streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
---
@@ -18,10 +18,12 @@
package
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/12268
@rxin I see. Actually, I added a benchmark for this change in the JIRA.
So.. would this be okay if I do as below:
1. Get rid of `StringIteratorReader`
2. Refactoring (maybe
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/12268
Sure.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13759
Thank you @rxin! Would this be sensible if this one is backported to 1.6.2?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13759
@rxin Sure!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so
Github user HyukjinKwon closed the pull request at:
https://github.com/apache/spark/pull/12268
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13640
Thanks!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13640
cc @rxin do you mind if I ask to review this please?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/10750#discussion_r49681620
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
---
@@ -480,10 +480,120 @@ private[sql] object
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10750#issuecomment-171513363
If we keep going to solve in `DataSourceStrategy` in this way, I think we
should resolve the operators for other datasources. For this, dealing with
`Cast` [SPARK
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/10750#discussion_r49679753
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
---
@@ -480,10 +480,120 @@ private[sql] object
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10750#issuecomment-171513129
Since `source.Filter` is shared with Parquet, ORC and etc., I think this
might have to resolve the arithmetic operators in `DataSourceStrategy` itself
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10750#issuecomment-171517766
@huaxingao please change the title not to end with â¦
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10750#issuecomment-171527726
@viirya Yes, I think so. But the reason why I did not give a try for this
is, `expression._` is being rapidly changed, which could affect to update codes
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10750#issuecomment-171515046
Actually, I also suggested the way similar with this in
[SPARK-9182](https://issues.apache.org/jira/browse/SPARK-9182). If we keep
adding filters in this way
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172442044
Sure. Do you think it would be great if JSON datasource has that one as
well?
---
If your project is set up for it, you can reply to this email and have your
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172435937
@falaki Ah, right.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/10800
[SPARK-12668] Renaming CSV options to be similar to Pandas and R
https://issues.apache.org/jira/browse/SPARK-12668
Spark CSV datasource has been being merged (file in
[SPARK-12420
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172441735
Sorry that I misunderstood the issue patch. For `codec` I was thinking it
was removed intendedly.
---
If your project is set up for it, you can reply
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172459208
Hm.. Could you know anything about the test `test different encoding`? This
is ignored and when I test this, this emits exception below.
```
00:17
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172463923
Ah.. `CSVParameters` is not serializable but was trying to pass it out of
driver side
---
If your project is set up for it, you can reply to this email and have
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/10805
[SPARK-12871][SQL] Support to specify the option for compression codec.
https://issues.apache.org/jira/browse/SPARK-12871
This PR added an option to support to specify compression codec
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172714365
This style failure is occuring in
`sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala`
which I did not change and it is fine in ny local
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172706793
Hm.. @rxin Can I make it like `JSONOptions` in a separate PR?
Now the object of this class is being passed so it should be serializable.
So, I think I should
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10805#issuecomment-17234
Although `CSVCompressionCodecs` might be shared with JSON datasource, I
will make that share this at the separate PR for JSON.
---
If your project is set up
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10800#issuecomment-172729369
I am not too sure why I am hitting this issue though, but I just corrected
some imports in an alphabetical order at `SparkStrategies` and `InnerJoinSuite
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10805#issuecomment-172747397
I will resolve conflicts and update this soon.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10805#issuecomment-172766510
Supported shorten names for compression codecs are below (case insensitive):
`bzip2` -> `org.apache.hadoop.io.compress.BZip2Codec`
`g
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/10805#discussion_r50053254
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVParameters.scala
---
@@ -71,6 +71,8 @@ private[sql] case class
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/10800#discussion_r50052445
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVParameters.scala
---
@@ -44,9 +44,11 @@ private[sql] case class
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13845
Sure! Thank you!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so
Github user HyukjinKwon closed the pull request at:
https://github.com/apache/spark/pull/13845
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
Again, I think the error message is not related with this change. I will
retest this and meanwhile try to build in my local.
---
If your project is set up for it, you can reply to this email
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
Hm... am I doing something wrong here?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/13942
[SPARK-16250][PYSPARK] Can't use escapeQuotes option in
DataFrameWriter.csv()
## What changes were proposed in this pull request?
This PR corrects `DataFrameWriter.csv()` to use
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13806
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/13912
[SPARK-16216][SQL] CSV data source does not write date and timestamp
correctly
## What changes were proposed in this pull request?
This PR corrects CSV data sources in order to write
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13912
Hm.. Anyway do you think I should close this and deal with JSON one? I
can't decide.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13912
Thank you for your comment @srowen !
I did this for two reasons. Firstly, it can't write and read back the dates
or timestamps but it might have to be converted manually by users
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13845
@JoshRosen Could you take a look by any change please?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13910
Get ready to receive a comment suggesting following
https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark..
---
If your project is set up for it, you can reply to this email
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13912
@srowen How about leaving them as timestamps long values but write them as
formatted strings only when `dateFormat` is given?
---
If your project is set up for it, you can reply to this email
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/13912#discussion_r68498245
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVRelation.scala
---
@@ -195,18 +202,50 @@ private[sql] class
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13912
I understand the problem without a timezone but.. hm.. to be honest, I have
seen a lot of cases of reading and writing times without a timezone (e.g. by
Microsoft Excel).
---
If your project
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/13912#discussion_r68511688
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVRelation.scala
---
@@ -195,18 +202,50 @@ private[sql] class
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/13912#discussion_r68511969
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVRelation.scala
---
@@ -195,18 +202,50 @@ private[sql] class
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13915
Oh, this was queued up in my local to submit a PR. I will leave a comment
just to note that this complies
https://github.com/databricks/scala-style-guide#variable-naming-convention
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13912
@srowen Hm.. I just wonder if I should correct JSON data source to be
consistent with this meaning these below:
1. Default is to write time as numeric timestamps
2. Supports both
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/13917
[MINOR][SQL][TEST] checkAnswer does not print the rows being compared in a
correct order
## What changes were proposed in this pull request?
This PR corrects the order of rows being
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13517
cc @davies and @rxin I addressed the comments. Thanks!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does
Github user HyukjinKwon closed the pull request at:
https://github.com/apache/spark/pull/13917
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13917
Sorry, this will prints wrong items when the order is different. Closing
this.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13912
@rxin, Could you please take a look?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13944
(I think it would be even nicer if this PR follows
https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark)
---
If your project is set up for it, you can reply to this email
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10502#issuecomment-182688789
@yhuai Would you look through this please?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/11169
[SPARK-13260][SQL] count(*) does not work with CSV data source
https://issues.apache.org/jira/browse/SPARK-13260
This is a quicky fix for `count(*)`.
When the `requiredColumns
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11169#issuecomment-183119538
cc @rxin @falaki
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11169#issuecomment-183158218
@rxin Can we maybe merge this for now and then take the optimisation into
account in another PR?
This optimisation would apply to all the pruned scan
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11169#issuecomment-183146848
This
[CSVRelation.scala#L193-L199](https://github.com/HyukjinKwon/spark/blob/SPARK-13260/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11169#issuecomment-183146606
I think I should have described this in more details. This works identical
with the original CSV datasource.
When the parsing mode is drop-malformed
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10502#issuecomment-180324662
I will resolve the conflict on Monday.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10980#issuecomment-176739657
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/10980
[SPARK-12997][SQL] Use cast expression to perform type cast in csv
https://issues.apache.org/jira/browse/SPARK-12997
CSVTypeCast.castTo should probably be removed, and just replace its
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/11005#discussion_r51493048
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
---
@@ -455,31 +458,31 @@ class JDBCSuite extends SparkFunSuite
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11005#issuecomment-178233988
cc @liancheng
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11016#issuecomment-179678080
cc @rxin
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11016#issuecomment-179685723
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/11020#discussion_r51534298
--- Diff: sql/core/src/test/resources/cars-malformed.csv ---
@@ -0,0 +1,5 @@
+year,make,model,comment,blank
--- End diff --
Sure
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11020#issuecomment-178442040
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/11023
[SPARK-13137][SQL] NullPoingException in schema inference for CSV when the
first line is empty
https://issues.apache.org/jira/browse/SPARK-13137
This PR adds a filter in schema
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11005#issuecomment-178420517
As @maropu said, for me I also agree with him but some may think
differently as mentioned
[here](https://github.com/apache/spark/pull/10750#issuecomment-175400704
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/11020
[SPARK-13114][SQL] Add a test for tokens more than the fields in schema
https://issues.apache.org/jira/browse/SPARK-13114
This PR adds a test for tokens more than the fields in schema
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/11016
[SPARK-13108][SQL] Validate ascii compatible encodings
https://issues.apache.org/jira/browse/SPARK-13108
CSV datasource currently does not support non-ascii compatible encodings
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11023#issuecomment-178468002
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11270#issuecomment-187607865
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11270#issuecomment-187603526
I made some tests `ignored` for testing default data source and also
commented some pyspark tests instead of setting `unittest.skip()` as they
include some
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10980#issuecomment-188103804
I am closing this.
BTW, I think the issue itself is a little bit questionable at the end. If
we can apply the same rules for casting, then it would
Github user HyukjinKwon closed the pull request at:
https://github.com/apache/spark/pull/10980
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10980#issuecomment-188094839
@falaki Do you think we should close this?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10980#issuecomment-188094727
@falaki As far as I understood, I am trying to use the existing casting
tools in Spark by using`Cast()`.
However, it ended up with additional cases
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/10502#issuecomment-189119103
@yhuai No problem. Then, please inform me when I am supposed to do
something else.
---
If your project is set up for it, you can reply to this email and have your
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11384#issuecomment-189118328
cc @rxin
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/11384
[SPARK-13503][SQL] Support to specify the (writing) option for compression
codec for TEXT
## What changes were proposed in this pull request?
This PR makes the TEXT datasource can
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11389#issuecomment-189979099
@rxin Actually, do you think we need the `compression` option for Parquet
and ORC as well (although I am not going to deal with them in this PR even if
we need
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11389#issuecomment-189987175
@rxin Sure.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11016#issuecomment-190018739
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11389#issuecomment-190031556
retest this please
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11389#issuecomment-190033580
Hm... It looks a bit weird. `ParquetHadoopFsRelationSuite` the tests about
types ("test all data types - ...") keep failing. This is also happening at
o
301 - 400 of 12622 matches
Mail list logo
