[JIRA] (SPARK-546) Support full outer join and multiple join in a single shuffle

2016-07-20 Thread Anonymous (JIRA) 
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[JIRA] (SPARK-546) Support full outer join and multiple join in a single shuffle

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[JIRA] (SPARK-546) Support full outer join and multiple join in a single shuffle

2016-07-20 Thread Anonymous (JIRA) 
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Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Reynold Xin 
+1

On Wednesday, July 20, 2016, Krishna Sankar  wrote:

> +1 (non-binding, of course)
>
> 1. Compiled OS X 10.11.5 (El Capitan) OK Total time: 24:07 min
>  mvn clean package -Pyarn -Phadoop-2.7 -DskipTests
> 2. Tested pyspark, mllib (iPython 4.0)
> 2.0 Spark version is 2.0.0
> 2.1. statistics (min,max,mean,Pearson,Spearman) OK
> 2.2. Linear/Ridge/Lasso Regression OK
> 2.3. Classification : Decision Tree, Naive Bayes OK
> 2.4. Clustering : KMeans OK
>Center And Scale OK
> 2.5. RDD operations OK
>   State of the Union Texts - MapReduce, Filter,sortByKey (word count)
> 2.6. Recommendation (Movielens medium dataset ~1 M ratings) OK
>Model evaluation/optimization (rank, numIter, lambda) with
> itertools OK
> 3. Scala - MLlib
> 3.1. statistics (min,max,mean,Pearson,Spearman) OK
> 3.2. LinearRegressionWithSGD OK
> 3.3. Decision Tree OK
> 3.4. KMeans OK
> 3.5. Recommendation (Movielens medium dataset ~1 M ratings) OK
> 3.6. saveAsParquetFile OK
> 3.7. Read and verify the 3.6 save(above) - sqlContext.parquetFile,
> registerTempTable, sql OK
> 3.8. result = sqlContext.sql("SELECT
> OrderDetails.OrderID,ShipCountry,UnitPrice,Qty,Discount FROM Orders INNER
> JOIN OrderDetails ON Orders.OrderID = OrderDetails.OrderID") OK
> 4.0. Spark SQL from Python OK
> 4.1. result = sqlContext.sql("SELECT * from people WHERE State = 'WA'") OK
> 5.0. Packages
> 5.1. com.databricks.spark.csv - read/write OK (--packages
> com.databricks:spark-csv_2.10:1.4.0)
> 6.0. DataFrames
> 6.1. cast,dtypes OK
> 6.2. groupBy,avg,crosstab,corr,isNull,na.drop OK
> 6.3. All joins,sql,set operations,udf OK
> [Dataframe Operations very fast from 11 secs to 3 secs, to 1.8 secs, to
> 1.5 secs! Good work !!!]
> 7.0. GraphX/Scala
> 7.1. Create Graph (small and bigger dataset) OK
> 7.2. Structure APIs - OK
> 7.3. Social Network/Community APIs - OK
> 7.4. Algorithms : PageRank of 2 datasets, aggregateMessages() - OK
>
> Cheers
> 
>
> On Tue, Jul 19, 2016 at 7:35 PM, Reynold Xin  > wrote:
>
>> Please vote on releasing the following candidate as Apache Spark version
>> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes
>> if a majority of at least 3 +1 PMC votes are cast.
>>
>> [ ] +1 Release this package as Apache Spark 2.0.0
>> [ ] -1 Do not release this package because ...
>>
>>
>> The tag to be voted on is v2.0.0-rc5
>> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>>
>> This release candidate resolves ~2500 issues:
>> https://s.apache.org/spark-2.0.0-jira
>>
>> The release files, including signatures, digests, etc. can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/
>>
>> Release artifacts are signed with the following key:
>> https://people.apache.org/keys/committer/pwendell.asc
>>
>> The staging repository for this release can be found at:
>> https://repository.apache.org/content/repositories/orgapachespark-1195/
>>
>> The documentation corresponding to this release can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/
>>
>>
>> =
>> How can I help test this release?
>> =
>> If you are a Spark user, you can help us test this release by taking an
>> existing Spark workload and running on this release candidate, then
>> reporting any regressions from 1.x.
>>
>> ==
>> What justifies a -1 vote for this release?
>> ==
>> Critical bugs impacting major functionalities.
>>
>> Bugs already present in 1.x, missing features, or bugs related to new
>> features will not necessarily block this release. Note that historically
>> Spark documentation has been published on the website separately from the
>> main release so we do not need to block the release due to documentation
>> errors either.
>>
>>
>

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Dongjoon Hyun 
+1 (non-binding)

- MD5/SHA/GPG matched.
- Test passed on Ubuntu (16.04) +  Oracle JDK (1.7.0_80) + R(3.2.3)
  * build/mvn -Phive -Phadoop-2.7 -Pyarn clean package
  * python python/run-tests.py
  * R/install-dev.sh & R/run-tests.sh

Cheers!

Dongjoon.


On Tue, Jul 19, 2016 at 7:35 PM, Reynold Xin  wrote:

> Please vote on releasing the following candidate as Apache Spark version
> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes
> if a majority of at least 3 +1 PMC votes are cast.
>
> [ ] +1 Release this package as Apache Spark 2.0.0
> [ ] -1 Do not release this package because ...
>
>
> The tag to be voted on is v2.0.0-rc5
> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>
> This release candidate resolves ~2500 issues:
> https://s.apache.org/spark-2.0.0-jira
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/
>
> Release artifacts are signed with the following key:
> https://people.apache.org/keys/committer/pwendell.asc
>
> The staging repository for this release can be found at:
> https://repository.apache.org/content/repositories/orgapachespark-1195/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/
>
>
> =
> How can I help test this release?
> =
> If you are a Spark user, you can help us test this release by taking an
> existing Spark workload and running on this release candidate, then
> reporting any regressions from 1.x.
>
> ==
> What justifies a -1 vote for this release?
> ==
> Critical bugs impacting major functionalities.
>
> Bugs already present in 1.x, missing features, or bugs related to new
> features will not necessarily block this release. Note that historically
> Spark documentation has been published on the website separately from the
> main release so we do not need to block the release due to documentation
> errors either.
>
>

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Krishna Sankar 
+1 (non-binding, of course)

1. Compiled OS X 10.11.5 (El Capitan) OK Total time: 24:07 min
 mvn clean package -Pyarn -Phadoop-2.7 -DskipTests
2. Tested pyspark, mllib (iPython 4.0)
2.0 Spark version is 2.0.0
2.1. statistics (min,max,mean,Pearson,Spearman) OK
2.2. Linear/Ridge/Lasso Regression OK
2.3. Classification : Decision Tree, Naive Bayes OK
2.4. Clustering : KMeans OK
   Center And Scale OK
2.5. RDD operations OK
  State of the Union Texts - MapReduce, Filter,sortByKey (word count)
2.6. Recommendation (Movielens medium dataset ~1 M ratings) OK
   Model evaluation/optimization (rank, numIter, lambda) with itertools
OK
3. Scala - MLlib
3.1. statistics (min,max,mean,Pearson,Spearman) OK
3.2. LinearRegressionWithSGD OK
3.3. Decision Tree OK
3.4. KMeans OK
3.5. Recommendation (Movielens medium dataset ~1 M ratings) OK
3.6. saveAsParquetFile OK
3.7. Read and verify the 3.6 save(above) - sqlContext.parquetFile,
registerTempTable, sql OK
3.8. result = sqlContext.sql("SELECT
OrderDetails.OrderID,ShipCountry,UnitPrice,Qty,Discount FROM Orders INNER
JOIN OrderDetails ON Orders.OrderID = OrderDetails.OrderID") OK
4.0. Spark SQL from Python OK
4.1. result = sqlContext.sql("SELECT * from people WHERE State = 'WA'") OK
5.0. Packages
5.1. com.databricks.spark.csv - read/write OK (--packages
com.databricks:spark-csv_2.10:1.4.0)
6.0. DataFrames
6.1. cast,dtypes OK
6.2. groupBy,avg,crosstab,corr,isNull,na.drop OK
6.3. All joins,sql,set operations,udf OK
[Dataframe Operations very fast from 11 secs to 3 secs, to 1.8 secs, to 1.5
secs! Good work !!!]
7.0. GraphX/Scala
7.1. Create Graph (small and bigger dataset) OK
7.2. Structure APIs - OK
7.3. Social Network/Community APIs - OK
7.4. Algorithms : PageRank of 2 datasets, aggregateMessages() - OK

Cheers


On Tue, Jul 19, 2016 at 7:35 PM, Reynold Xin  wrote:

> Please vote on releasing the following candidate as Apache Spark version
> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes
> if a majority of at least 3 +1 PMC votes are cast.
>
> [ ] +1 Release this package as Apache Spark 2.0.0
> [ ] -1 Do not release this package because ...
>
>
> The tag to be voted on is v2.0.0-rc5
> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>
> This release candidate resolves ~2500 issues:
> https://s.apache.org/spark-2.0.0-jira
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/
>
> Release artifacts are signed with the following key:
> https://people.apache.org/keys/committer/pwendell.asc
>
> The staging repository for this release can be found at:
> https://repository.apache.org/content/repositories/orgapachespark-1195/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/
>
>
> =
> How can I help test this release?
> =
> If you are a Spark user, you can help us test this release by taking an
> existing Spark workload and running on this release candidate, then
> reporting any regressions from 1.x.
>
> ==
> What justifies a -1 vote for this release?
> ==
> Critical bugs impacting major functionalities.
>
> Bugs already present in 1.x, missing features, or bugs related to new
> features will not necessarily block this release. Note that historically
> Spark documentation has been published on the website separately from the
> main release so we do not need to block the release due to documentation
> errors either.
>
>

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Joseph Gonzalez 
+1

Sent from my iPad

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To unsubscribe e-mail: dev-unsubscr...@spark.apache.org

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Jonathan Kelly 
+1 (non-binding)

On Wed, Jul 20, 2016 at 2:48 PM Michael Allman  wrote:

> I've run some tests with some real and some synthetic parquet data with
> nested columns with and without the hive metastore on our Spark 1.5, 1.6
> and 2.0 versions. I haven't seen any unexpected performance surprises,
> except that Spark 2.0 now does schema inference across all files in a
> partitioned parquet metastore table. Granted, you aren't using a metastore
> table, but maybe Spark does that for partitioned non-metastore tables as
> well.
>
> Michael
>
> > On Jul 20, 2016, at 2:16 PM, Maciej Bryński  wrote:
> >
> > @Michael,
> > I answered in Jira and could repeat here.
> > I think that my problem is unrelated to Hive, because I'm using
> read.parquet method.
> > I also attached some VisualVM snapshots to SPARK-16321 (I think I should
> merge both issues)
> > And code profiling suggest bottleneck when reading parquet file.
> >
> > I wonder if there are any other benchmarks related to parquet
> performance.
> >
> > Regards,
> > --
> > Maciek Bryński
>
>
> -
> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
>
>

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Michael Allman 
I've run some tests with some real and some synthetic parquet data with nested 
columns with and without the hive metastore on our Spark 1.5, 1.6 and 2.0 
versions. I haven't seen any unexpected performance surprises, except that 
Spark 2.0 now does schema inference across all files in a partitioned parquet 
metastore table. Granted, you aren't using a metastore table, but maybe Spark 
does that for partitioned non-metastore tables as well.

Michael

> On Jul 20, 2016, at 2:16 PM, Maciej Bryński  wrote:
> 
> @Michael,
> I answered in Jira and could repeat here.
> I think that my problem is unrelated to Hive, because I'm using read.parquet 
> method.
> I also attached some VisualVM snapshots to SPARK-16321 (I think I should 
> merge both issues)
> And code profiling suggest bottleneck when reading parquet file.
> 
> I wonder if there are any other benchmarks related to parquet performance.
> 
> Regards,
> -- 
> Maciek Bryński


-
To unsubscribe e-mail: dev-unsubscr...@spark.apache.org

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Maciej Bryński 
@Michael,
I answered in Jira and could repeat here.
I think that my problem is unrelated to Hive, because I'm using
read.parquet method.
I also attached some VisualVM snapshots to SPARK-16321 (I think I should
merge both issues)
And code profiling suggest bottleneck when reading parquet file.

I wonder if there are any other benchmarks related to parquet performance.

Regards,
-- 
Maciek Bryński

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Michael Allman 
In reference to https://issues.apache.org/jira/browse/SPARK-16320, the code 
path for reading data from parquet files has been refactored extensively. The 
fact that Maciej was testing performance on a table with 400 partitions makes 
me wonder if my PR for https://issues.apache.org/jira/browse/SPARK-15968 will 
make a difference for repeated queries on partitioned tables. That PR was 
merged into master and backported to 2.0. The commit short hash is d5d2457.

Maciej, can you rerun your test on your original dataset with a version of 
Spark 2.0 with that commit in it? And run it more than once? And ensure that 
when you compare your query performance for the first query, ensure that you're 
starting with a fresh spark-shell or spark-sql for each so caching is not a 
factor.

As for the issue with initial query performance on a partitioned table or query 
performance on an unpartitioned table being inferior, I can do a quick test to 
see if I can reproduce that issue on our end. Assuming there is a perf 
regression, I may be able to spend some time debugging today. I've spent a 
substantial amount of time debugging and optimizing parquet table query perf in 
Spark, and we've been using 2.0 for at least a month now. Not sure if I'll have 
time to dig that deep, though.

Michael


> On Jul 20, 2016, at 9:23 AM, Marcin Tustin  wrote:
> 
> I refer to Maciej Bryński's (mac...@brynski.pl ) 
> emails of 29 and 30 June 2016 to this list. He said that his benchmarking 
> suggested that Spark 2.0 was slower than 1.6.
> 
> I'm wondering if that was ever investigated, and if so if the speed is back 
> up, or not.
> 
> On Wed, Jul 20, 2016 at 12:18 PM, Michael Allman  > wrote:
> Marcin,
> 
> I'm not sure what you're referring to. Can you be more specific?
> 
> Cheers,
> 
> Michael
> 
>> On Jul 20, 2016, at 9:10 AM, Marcin Tustin > > wrote:
>> 
>> Whatever happened with the query regarding benchmarks? Is that resolved?
>> 
>> On Tue, Jul 19, 2016 at 10:35 PM, Reynold Xin > > wrote:
>> Please vote on releasing the following candidate as Apache Spark version 
>> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes 
>> if a majority of at least 3 +1 PMC votes are cast.
>> 
>> [ ] +1 Release this package as Apache Spark 2.0.0
>> [ ] -1 Do not release this package because ...
>> 
>> 
>> The tag to be voted on is v2.0.0-rc5 
>> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>> 
>> This release candidate resolves ~2500 issues: 
>> https://s.apache.org/spark-2.0.0-jira 
>> 
>> The release files, including signatures, digests, etc. can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/ 
>> 
>> 
>> Release artifacts are signed with the following key:
>> https://people.apache.org/keys/committer/pwendell.asc 
>> 
>> 
>> The staging repository for this release can be found at:
>> https://repository.apache.org/content/repositories/orgapachespark-1195/ 
>> 
>> 
>> The documentation corresponding to this release can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/ 
>> 
>> 
>> 
>> =
>> How can I help test this release?
>> =
>> If you are a Spark user, you can help us test this release by taking an 
>> existing Spark workload and running on this release candidate, then 
>> reporting any regressions from 1.x.
>> 
>> ==
>> What justifies a -1 vote for this release?
>> ==
>> Critical bugs impacting major functionalities.
>> 
>> Bugs already present in 1.x, missing features, or bugs related to new 
>> features will not necessarily block this release. Note that historically 
>> Spark documentation has been published on the website separately from the 
>> main release so we do not need to block the release due to documentation 
>> errors either.
>> 
>> 
>> 
>> Want to work at Handy? Check out our culture deck and open roles 
>> 
>> Latest news  at Handy
>> Handy just raised $50m 
>> 
>>  led by Fidelity
>> 
>> 
> 
> 
> 
> Want to work at Handy? Check out our culture deck and open roles 
> 
> Latest news  at Handy
> Handy just raised $50m 
> 
>  led by Fidelity
> 
>

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Marcin Tustin 
I refer to Maciej Bryński's (mac...@brynski.pl) emails of 29 and 30 June
2016 to this list. He said that his benchmarking suggested that Spark 2.0
was slower than 1.6.

I'm wondering if that was ever investigated, and if so if the speed is back
up, or not.

On Wed, Jul 20, 2016 at 12:18 PM, Michael Allman 
wrote:

> Marcin,
>
> I'm not sure what you're referring to. Can you be more specific?
>
> Cheers,
>
> Michael
>
> On Jul 20, 2016, at 9:10 AM, Marcin Tustin  wrote:
>
> Whatever happened with the query regarding benchmarks? Is that resolved?
>
> On Tue, Jul 19, 2016 at 10:35 PM, Reynold Xin  wrote:
>
>> Please vote on releasing the following candidate as Apache Spark version
>> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes
>> if a majority of at least 3 +1 PMC votes are cast.
>>
>> [ ] +1 Release this package as Apache Spark 2.0.0
>> [ ] -1 Do not release this package because ...
>>
>>
>> The tag to be voted on is v2.0.0-rc5
>> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>>
>> This release candidate resolves ~2500 issues:
>> https://s.apache.org/spark-2.0.0-jira
>>
>> The release files, including signatures, digests, etc. can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/
>>
>> Release artifacts are signed with the following key:
>> https://people.apache.org/keys/committer/pwendell.asc
>>
>> The staging repository for this release can be found at:
>> https://repository.apache.org/content/repositories/orgapachespark-1195/
>>
>> The documentation corresponding to this release can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/
>>
>>
>> =
>> How can I help test this release?
>> =
>> If you are a Spark user, you can help us test this release by taking an
>> existing Spark workload and running on this release candidate, then
>> reporting any regressions from 1.x.
>>
>> ==
>> What justifies a -1 vote for this release?
>> ==
>> Critical bugs impacting major functionalities.
>>
>> Bugs already present in 1.x, missing features, or bugs related to new
>> features will not necessarily block this release. Note that historically
>> Spark documentation has been published on the website separately from the
>> main release so we do not need to block the release due to documentation
>> errors either.
>>
>>
>
> Want to work at Handy? Check out our culture deck and open roles
> 
> Latest news  at Handy
> Handy just raised $50m
> 
>  led
> by Fidelity
>
>
>

-- 
Want to work at Handy? Check out our culture deck and open roles 

Latest news  at Handy
Handy just raised $50m 

 led 
by Fidelity

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Michael Allman 
Marcin,

I'm not sure what you're referring to. Can you be more specific?

Cheers,

Michael

> On Jul 20, 2016, at 9:10 AM, Marcin Tustin  wrote:
> 
> Whatever happened with the query regarding benchmarks? Is that resolved?
> 
> On Tue, Jul 19, 2016 at 10:35 PM, Reynold Xin  > wrote:
> Please vote on releasing the following candidate as Apache Spark version 
> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes 
> if a majority of at least 3 +1 PMC votes are cast.
> 
> [ ] +1 Release this package as Apache Spark 2.0.0
> [ ] -1 Do not release this package because ...
> 
> 
> The tag to be voted on is v2.0.0-rc5 
> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
> 
> This release candidate resolves ~2500 issues: 
> https://s.apache.org/spark-2.0.0-jira 
> 
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/ 
> 
> 
> Release artifacts are signed with the following key:
> https://people.apache.org/keys/committer/pwendell.asc 
> 
> 
> The staging repository for this release can be found at:
> https://repository.apache.org/content/repositories/orgapachespark-1195/ 
> 
> 
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/ 
> 
> 
> 
> =
> How can I help test this release?
> =
> If you are a Spark user, you can help us test this release by taking an 
> existing Spark workload and running on this release candidate, then reporting 
> any regressions from 1.x.
> 
> ==
> What justifies a -1 vote for this release?
> ==
> Critical bugs impacting major functionalities.
> 
> Bugs already present in 1.x, missing features, or bugs related to new 
> features will not necessarily block this release. Note that historically 
> Spark documentation has been published on the website separately from the 
> main release so we do not need to block the release due to documentation 
> errors either.
> 
> 
> 
> Want to work at Handy? Check out our culture deck and open roles 
> 
> Latest news  at Handy
> Handy just raised $50m 
> 
>  led by Fidelity
> 
>

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Marcin Tustin 
Whatever happened with the query regarding benchmarks? Is that resolved?

On Tue, Jul 19, 2016 at 10:35 PM, Reynold Xin  wrote:

> Please vote on releasing the following candidate as Apache Spark version
> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes
> if a majority of at least 3 +1 PMC votes are cast.
>
> [ ] +1 Release this package as Apache Spark 2.0.0
> [ ] -1 Do not release this package because ...
>
>
> The tag to be voted on is v2.0.0-rc5
> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>
> This release candidate resolves ~2500 issues:
> https://s.apache.org/spark-2.0.0-jira
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/
>
> Release artifacts are signed with the following key:
> https://people.apache.org/keys/committer/pwendell.asc
>
> The staging repository for this release can be found at:
> https://repository.apache.org/content/repositories/orgapachespark-1195/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/
>
>
> =
> How can I help test this release?
> =
> If you are a Spark user, you can help us test this release by taking an
> existing Spark workload and running on this release candidate, then
> reporting any regressions from 1.x.
>
> ==
> What justifies a -1 vote for this release?
> ==
> Critical bugs impacting major functionalities.
>
> Bugs already present in 1.x, missing features, or bugs related to new
> features will not necessarily block this release. Note that historically
> Spark documentation has been published on the website separately from the
> main release so we do not need to block the release due to documentation
> errors either.
>
>

-- 
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Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Shivaram Venkataraman 
+1

SHA and MD5 sums match for all binaries. Docs look fine this time
around. Built and ran `dev/run-tests` with Java 7 on a linux machine.

No blocker bugs on JIRA and the only critical bug with target as 2.0.0
is SPARK-16633, which doesn't look like a release blocker. I also
checked issues which are marked as Critical affecting version 2.0.0
and the only other ones that seem applicable are SPARK-15703 and
SPARK-16334. Both of them don't look like blockers to me.

Thanks
Shivaram


On Tue, Jul 19, 2016 at 7:35 PM, Reynold Xin  wrote:
> Please vote on releasing the following candidate as Apache Spark version
> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes
> if a majority of at least 3 +1 PMC votes are cast.
>
> [ ] +1 Release this package as Apache Spark 2.0.0
> [ ] -1 Do not release this package because ...
>
>
> The tag to be voted on is v2.0.0-rc5
> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>
> This release candidate resolves ~2500 issues:
> https://s.apache.org/spark-2.0.0-jira
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/
>
> Release artifacts are signed with the following key:
> https://people.apache.org/keys/committer/pwendell.asc
>
> The staging repository for this release can be found at:
> https://repository.apache.org/content/repositories/orgapachespark-1195/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/
>
>
> =
> How can I help test this release?
> =
> If you are a Spark user, you can help us test this release by taking an
> existing Spark workload and running on this release candidate, then
> reporting any regressions from 1.x.
>
> ==
> What justifies a -1 vote for this release?
> ==
> Critical bugs impacting major functionalities.
>
> Bugs already present in 1.x, missing features, or bugs related to new
> features will not necessarily block this release. Note that historically
> Spark documentation has been published on the website separately from the
> main release so we do not need to block the release due to documentation
> errors either.
>

-
To unsubscribe e-mail: dev-unsubscr...@spark.apache.org

Re: [VOTE] Release Apache Spark 2.0.0 (RC5)

2016-07-20 Thread Sean Owen 
+1 at last. Sigs and hashes check out, and compiles and passes tests
with "-Pyarn -Phadoop-2.7 -Phive" on Ubuntu 16 + Java 8.


There are actually only 2 issues still targeted for 2.0.0, which is great:
SPARK-16633 lag/lead does not return the default value when the offset
row does not exist
SPARK-16648 LAST_VALUE(FALSE) OVER () throws IndexOutOfBoundsException

These are not marked blocker, though one is critical. I will assume
these don't block.


The only other JIRA that seems to be "for 2.0" and not resolved is...
https://issues.apache.org/jira/browse/SPARK-16486
... which I suspect is actually just something to be renamed and pushed out.


I did encounter two test failures that weren't reproducible, just FYI:

ExecutorAllocationManagerSuite:
- basic functionality *** FAILED ***
  The code passed to eventually never returned normally. Attempted 613
times over 10.01536211198 seconds. Last failure message:
  Wanted but not invoked:
  executorAllocationClient.killExecutor("2");
  -> at 
org.apache.spark.streaming.scheduler.ExecutorAllocationManagerSuite$$anonfun$2$$anonfun$7.org$apache$spark$streaming$scheduler$ExecutorAllocationManagerSuite$$anonfun$$anonfun$$verifyKilledExec$1(ExecutorAllocationManagerSuite.scala:80)
  Actually, there were zero interactions with this mock.
  . (ExecutorAllocationManagerSuite.scala:61)

StateStoreSuite:
- maintenance *** FAILED ***
  The code passed to eventually never returned normally. Attempted 611
times over 10.007739936 seconds. Last failure message:
StateStoreSuite.this.fileExists(provider, 1L, false) was true earliest
file not deleted. (StateStoreSuite.scala:395)

On Wed, Jul 20, 2016 at 3:35 AM, Reynold Xin  wrote:
> Please vote on releasing the following candidate as Apache Spark version
> 2.0.0. The vote is open until Friday, July 22, 2016 at 20:00 PDT and passes
> if a majority of at least 3 +1 PMC votes are cast.
>
> [ ] +1 Release this package as Apache Spark 2.0.0
> [ ] -1 Do not release this package because ...
>
>
> The tag to be voted on is v2.0.0-rc5
> (13650fc58e1fcf2cf2a26ba11c819185ae1acc1f).
>
> This release candidate resolves ~2500 issues:
> https://s.apache.org/spark-2.0.0-jira
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-bin/
>
> Release artifacts are signed with the following key:
> https://people.apache.org/keys/committer/pwendell.asc
>
> The staging repository for this release can be found at:
> https://repository.apache.org/content/repositories/orgapachespark-1195/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc5-docs/
>
>
> =
> How can I help test this release?
> =
> If you are a Spark user, you can help us test this release by taking an
> existing Spark workload and running on this release candidate, then
> reporting any regressions from 1.x.
>
> ==
> What justifies a -1 vote for this release?
> ==
> Critical bugs impacting major functionalities.
>
> Bugs already present in 1.x, missing features, or bugs related to new
> features will not necessarily block this release. Note that historically
> Spark documentation has been published on the website separately from the
> main release so we do not need to block the release due to documentation
> errors either.
>

-
To unsubscribe e-mail: dev-unsubscr...@spark.apache.org

Snappy initialization issue, spark assembly jar missing snappy classes?

2016-07-20 Thread Eugene Morozov 
Greetings!

We're reading input files with newApiHadoopFile that is configured with
multiline split. Everything's fine, besides
https://issues.apache.org/jira/browse/MAPREDUCE-6549. It looks like the
issue is fixed, but within hadoop 2.7.2. Which means we have to download
spark without hadoop and provide custom version of it. Now we use
spark-1.6.1.

It mostly fine, there is doc how to configure, spark started, but when I
use it it gives me nasty exception about snappy cannot be initialized. I
tried few things - update snappy version inside hadoop, package snappy into
my own application jar, but it works only when I literally copy
snappy-java.jar classes into spark-assembly-1.6.1-hadoop2.2.0.jar. It seems
working for now, but I dislike this approach, because I simply cannot know
what else won't work tomorrow.
It looks like I can just turn off snappy, but I want it, I believe it makes
sense to compress data shuffled and stored around.

Could you suggest any way besides copying these classes inside assembled
spark jar file?


The snappy exception
Job aborted due to stage failure: Task 1 in stage 1.0 failed 4 times, most
recent failure: Lost task 1.3 in stage 1.0 (TID 69,
icomputer.petersburg.epam.com): java.io.IOException:
java.lang.reflect.InvocationTargetException
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1222)
at
org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:165)
at
org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
at
org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
at
org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:88)
at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.reflect.InvocationTargetException
at sun.reflect.GeneratedConstructorAccessor9.newInstance(Unknown Source)
at
sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
at
org.apache.spark.io.CompressionCodec$.createCodec(CompressionCodec.scala:72)
at
org.apache.spark.io.CompressionCodec$.createCodec(CompressionCodec.scala:65)
at org.apache.spark.broadcast.TorrentBroadcast.org
$apache$spark$broadcast$TorrentBroadcast$$setConf(TorrentBroadcast.scala:73)
at
org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:167)
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1219)
... 11 more
Caused by: java.lang.IllegalArgumentException:
java.lang.NoClassDefFoundError: Could not initialize class
org.xerial.snappy.Snappy
at
org.apache.spark.io.SnappyCompressionCodec$.liftedTree1$1(CompressionCodec.scala:171)
at
org.apache.spark.io.SnappyCompressionCodec$.org$apache$spark$io$SnappyCompressionCodec$$version$lzycompute(CompressionCodec.scala:168)
at
org.apache.spark.io.SnappyCompressionCodec$.org$apache$spark$io$SnappyCompressionCodec$$version(CompressionCodec.scala:168)
at
org.apache.spark.io.SnappyCompressionCodec.(CompressionCodec.scala:152)
... 19 more
Caused by: java.lang.NoClassDefFoundError: Could not initialize class
org.xerial.snappy.Snappy
at
org.apache.spark.io.SnappyCompressionCodec$.liftedTree1$1(CompressionCodec.scala:169)
... 22 more
--
Be well!
Jean Morozov