[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-17 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
Thank you, @gatorsmile !


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-17 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/20511
  
LGTM 

Thanks! Merged to master. 


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-16 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
Sure. @gatorsmile . I'll create a new PR for Apache Spark 2.4 default 
configuration and a migration guide for 2.3 to 2.4 after this PR is merged.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-16 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/20511
  
I agree on what @omalley said. The new reader based on ORC 1.4 is better 
than the old reader. That is why we chose the new reader as the default at the 
beginning. We also saw the performance improvement in the micro-benchmark. 

However, at the RC3 of Spark 2.3, we realize the new reader introduces the 
regression. After RC3, we reverted many PRs that caused the regressions and 
also rejected many bug fixes that could introduce new regressions. We are very 
conservative when merging the bug fixes in this stage. Thus, I also think the 
suggestion from @marmbrus is very reasonable. That is the strategy we are 
following in the previous Spark releases. 

Regarding this specific case, we did not revert the new reader, but just 
changed the default values. Users can try the new reader. We just want to avoid 
breaking the existing workloads when they upgrade to the upcoming Spark 2.3 
release. In the next Spark 2.4 release, I believe we can feel more confident to 
choose the ORC new reader as the default. 

@dongjoon-hyun Could you submit a PR against the master branch to turn on 
them by default? Also add a migration guide. 


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-16 Thread omalley
Github user omalley commented on the issue:

https://github.com/apache/spark/pull/20511
  
I'm frustrated with the direction this has gone.

The new reader is much better than the old reader, which uses Hive 1.2. ORC 
1.4.3 had a pair of important, but not large or complex fixes. Yet, because of 
those fixes, now the entire new reader is being disabled by default in the 
upcoming Spark 2.2.

In particular, the Hive 1.2 ORC code has the following known problems:
* HIVE-11312 - Char predicate pushdown can filter all rows
* HIVE-13083 - Decimal columns can incorrectly suppress the isNonNull 
stream.
* ORC-101 -  Predicate pushdown on bloom filters use default charset rather 
than UTF8.
* ORC-135 - Predicate pushdown on timestamps doesn't correct for timezones


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-16 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
Thank you. I created [SPARK-23452 Extend test coverage to all ORC 
readers](https://issues.apache.org/jira/browse/SPARK-23452) for that. Maybe, we 
can add more comments during that JIRA task.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-16 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/20511
  
@dongjoon-hyun That also sounds good to me. Always welcome to seeing more 
contributions to help improve the test coverage. Doing our best to improve the 
test coverage and code readability. 

Normally, when the reviewers have questions, (sometimes the questions are 
stupid), that might also mean the codes need more comments/refactoring. This 
can help the future code developers and maintainers. 


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-16 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
@gatorsmile . 
In general, I agree with your idea to have a complete test coverage.
And, I think we can double the test coverage by enabling and disabling the 
vectorization for the whole ORC suites **instead of doing it in a specific test 
case**. How do you think about that? Can we do that kind of refactoring in a 
separate PR after this? If you want, I'll create Apache JIRA issue for that.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-15 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
Thank you, All.
Now, it's ready for review again for Apache Spark 2.4.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-15 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
Sure, I rebased this.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-15 Thread gatorsmile
Github user gatorsmile commented on the issue:

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@dongjoon-hyun Could you rebase this PR? We want to merge it to master. 
Thanks!


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-14 Thread gatorsmile
Github user gatorsmile commented on the issue:

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uh, I missed the previous comment. 


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-14 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/20511
  
Based on our standard, we do not change the dependencies in the minor 
releases. 


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-14 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
I see. Thank you for confirmation, @marmbrus !


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-14 Thread marmbrus
Github user marmbrus commented on the issue:

https://github.com/apache/spark/pull/20511
  
Unfortunately, dependency changes are not typically allowed in patch 
releases.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-14 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
@marmbrus , @sameeragarwal , @gatorsmile , @cloud-fan , @rxin .
Can we have this patch for Apache Spark 2.3.1?


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-14 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
+1.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-14 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/20511
  
Based on what @marmbrus suggested above, given how late it is in the cycle, 
we have to disable the native ORC reader (and also the filter pushdown) in 
2.3.0 to avoid delaying the release, but add to release notes on how to turn 
them on manually. 

In the long term, our strategy is to improve our test coverage in the Spark 
side, instead of relying on the test cases of external data sources. 

cc @dongjoon-hyun @sameeragarwal @cloud-fan @rxin 


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-13 Thread marmbrus
Github user marmbrus commented on the issue:

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Sorry if I'm missing some context here, but our typical process this late 
in the release (we are over a month since the branch was cut) would be to 
disable any new features that still have regressions.  I'm generally not okay 
with any dependency changes this far into QA unless there is no other option.

Should we be considering turning this off so that we can GA Spark 2.3 soon?


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-13 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
Rebased to the master in order to update the migration doc, too.
BTW, the previous failure is irrelevant: 
`org.apache.spark.sql.kafka010.KafkaContinuousSourceTopicDeletionSuite.subscribing
 topic by pattern with topic deletions`.


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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-13 Thread SparkQA
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https://github.com/apache/spark/pull/20511
  
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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

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[GitHub] spark issue #20511: [SPARK-23340][SQL] Upgrade Apache ORC to 1.4.3

2018-02-13 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/20511
  
Title of PR/JIRA is updated, too.


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