Structured Streaming partition logic with respect to storage and fileformat

[Sachin Aggarwal]

when we use readStream to read data as Stream, how spark decides the no of
RDD and partition within each RDD with respect to storage and file format.

val dsJson = sqlContext.readStream.json("/Users/sachin/testSpark/inputJson")

val dsCsv = sqlContext.readStream.option("header","true").csv(
"/Users/sachin/testSpark/inputCsv")

val ds = sqlContext.readStream.text("/Users/sachin/testSpark/inputText")
val dsText = ds.as[String].map(x =>(x.split(" ")(0),x.split("
")(1))).toDF("name","age")

val dsParquet =
sqlContext.readStream.format("parquet").parquet("/Users/sachin/testSpark/inputParquet")



-- 

Thanks & Regards

Sachin Aggarwal
7760502772

Possible contribution to MLlib

[Simon NANTY]

Hi all,

In my team, we are currently developing a fork of spark MLlib extending K-means 
method such that it is possible to set its own distance function. In this 
implementation, it could be possible to directly pass, in argument of the 
K-means train function, a distance function whose signature is: 
(VectorWithNorm, VectorWithNorm) => Double.

We have found the Jira instance SPARK-11665 proposing to support new distances 
in bisecting K-means. There has also been the Jira instance SPARK-3219 
proposing to add Bregman divergences as distance functions, but it has not been 
added to MLlib. Therefore, we are wondering if such an extension of MLlib 
K-means algorithm would be appreciated by the community and would have chances 
to get included in future spark releases.

Regards,

Simon Nanty

Re: [VOTE] Release Apache Spark 1.6.2 (RC2)

[Pete Robbins]

The PR (https://github.com/apache/spark/pull/13055) to fix
https://issues.apache.org/jira/browse/SPARK-15262 was applied to 1.6.2
however this fix caused another issue
https://issues.apache.org/jira/browse/SPARK-15606 the fix for which (
https://github.com/apache/spark/pull/13355) has not been backported to the
1.6 branch so I'm now seeing the same failure in 1.6.2

Cheers,

On Mon, 20 Jun 2016 at 05:25 Reynold Xin  wrote:

> Please vote on releasing the following candidate as Apache Spark version
> 1.6.2. The vote is open until Wednesday, June 22, 2016 at 22:00 PDT and
> passes if a majority of at least 3+1 PMC votes are cast.
>
> [ ] +1 Release this package as Apache Spark 1.6.2
> [ ] -1 Do not release this package because ...
>
>
> The tag to be voted on is v1.6.2-rc2
> (54b1121f351f056d6b67d2bb4efe0d553c0f7482)
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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-1186/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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 1.6.1.
>
> 
> == What justifies a -1 vote for this release? ==
> 
> This is a maintenance release in the 1.6.x series.  Bugs already present
> in 1.6.1, missing features, or bugs related to new features will not
> necessarily block this release.
>
>
>
>

Re: Structured Streaming partition logic with respect to storage and fileformat

[Jörn Franke]

Based on the underlying Hadoop FileFormat. This one does it mostly based on 
blocksize. You can change this though.

> On 21 Jun 2016, at 12:19, Sachin Aggarwal  wrote:
> 
> 
> when we use readStream to read data as Stream, how spark decides the no of 
> RDD and partition within each RDD with respect to storage and file format.
> 
> val dsJson = sqlContext.readStream.json("/Users/sachin/testSpark/inputJson")
> 
> val dsCsv = 
> sqlContext.readStream.option("header","true").csv("/Users/sachin/testSpark/inputCsv")
> val ds = sqlContext.readStream.text("/Users/sachin/testSpark/inputText")
> val dsText = ds.as[String].map(x =>(x.split(" ")(0),x.split(" 
> ")(1))).toDF("name","age")
> 
> val dsParquet = 
> sqlContext.readStream.format("parquet").parquet("/Users/sachin/testSpark/inputParquet")
> 
> 
> -- 
> 
> Thanks & Regards
> 
> Sachin Aggarwal
> 7760502772

Re: Question about Bloom Filter in Spark 2.0

[Reynold Xin]

SPARK-12818 is about building a bloom filter on existing data. It has
nothing to do with the ORC bloom filter, which can be used to do predicate
pushdown.


On Tue, Jun 21, 2016 at 7:45 PM, BaiRan  wrote:

> Hi all,
>
> I have a question about bloom filter implementation in Spark-12818 issue.
> If I have a ORC file with bloom filter metadata, how can I utilise it by
> Spark SQL?
> Thanks.
>
> Best,
> Ran
>

Re: [VOTE] Release Apache Spark 2.0.0 (RC1)

[Sean Owen]

While I'd officially -1 this while there are still many blockers, this
should certainly be tested as usual, because they're mostly doc and
"audit" type issues.

On Wed, Jun 22, 2016 at 2:26 AM, Reynold Xin  wrote:
> Please vote on releasing the following candidate as Apache Spark version
> 2.0.0. The vote is open until Friday, June 24, 2016 at 19:00 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-rc1
> (0c66ca41afade6db73c9aeddd5aed6e5dcea90df).
>
> This release candidate resolves ~2400 issues:
> https://s.apache.org/spark-2.0.0-rc1-jira
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc1-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-1187/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc1-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
For additional commands, e-mail: dev-h...@spark.apache.org

[VOTE] Release Apache Spark 2.0.0 (RC1)

[Reynold Xin]

Please vote on releasing the following candidate as Apache Spark version
2.0.0. The vote is open until Friday, June 24, 2016 at 19:00 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-rc1
(0c66ca41afade6db73c9aeddd5aed6e5dcea90df).

This release candidate resolves ~2400 issues:
https://s.apache.org/spark-2.0.0-rc1-jira

The release files, including signatures, digests, etc. can be found at:
http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc1-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-1187/

The documentation corresponding to this release can be found at:
http://people.apache.org/~pwendell/spark-releases/spark-2.0.0-rc1-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.

Question about Bloom Filter in Spark 2.0

[BaiRan]

Hi all,

I have a question about bloom filter implementation in Spark-12818 issue. If I 
have a ORC file with bloom filter metadata, how can I utilise it by Spark SQL?
Thanks.

Best,
Ran

Re: Structured Streaming partition logic with respect to storage and fileformat

[Sachin Aggarwal]

what will the scenario in case of s3 and  local file system?

On Tue, Jun 21, 2016 at 4:36 PM, Jörn Franke  wrote:

> Based on the underlying Hadoop FileFormat. This one does it mostly based
> on blocksize. You can change this though.
>
> On 21 Jun 2016, at 12:19, Sachin Aggarwal 
> wrote:
>
>
> when we use readStream to read data as Stream, how spark decides the no of
> RDD and partition within each RDD with respect to storage and file format.
>
> val dsJson = sqlContext.readStream.json(
> "/Users/sachin/testSpark/inputJson")
>
> val dsCsv = sqlContext.readStream.option("header","true").csv(
> "/Users/sachin/testSpark/inputCsv")
>
> val ds = sqlContext.readStream.text("/Users/sachin/testSpark/inputText")
> val dsText = ds.as[String].map(x =>(x.split(" ")(0),x.split(" 
> ")(1))).toDF("name","age")
>
> val dsParquet = 
> sqlContext.readStream.format("parquet").parquet("/Users/sachin/testSpark/inputParquet")
>
>
>
> --
>
> Thanks & Regards
>
> Sachin Aggarwal
> 7760502772
>
>


-- 

Thanks & Regards

Sachin Aggarwal
7760502772

Re: Possible contribution to MLlib

[Jeff Zhang]

I think it is valuable to make the distance function pluggable and also
provide some builtin distance function. This might be also useful for other
algorithms besides KMeans.

On Tue, Jun 21, 2016 at 7:48 PM, Simon NANTY 
wrote:

> Hi all,
>
>
>
> In my team, we are currently developing a fork of spark MLlib extending
> K-means method such that it is possible to set its own distance function.
> In this implementation, it could be possible to directly pass, in argument
> of the K-means train function, a distance function whose signature is:
> (VectorWithNorm, VectorWithNorm) => Double.
>
>
>
> We have found the Jira instance SPARK-11665 proposing to support new
> distances in bisecting K-means. There has also been the Jira instance
> SPARK-3219 proposing to add Bregman divergences as distance functions, but
> it has not been added to MLlib. Therefore, we are wondering if such an
> extension of MLlib K-means algorithm would be appreciated by the community
> and would have chances to get included in future spark releases.
>
>
>
> Regards,
>
>
>
> Simon Nanty
>
>
>



-- 
Best Regards

Jeff Zhang

Jar for Spark developement

[tesm...@gmail.com]

Hi,

Beginner in Spark development. Took time to configure Eclipse + Scala. Is
there any tutorial that can help beginners.

Still struggling to find Spark JAR files for development. There is no lib
folder in my Spark distribution (neither in pre-built nor in custom built..)


Regards,

Re: [VOTE] Release Apache Spark 1.6.2 (RC2)

[Sean Owen]

Nice one, yeah indeed I was doing an incremental build. Not a blocker.
I'll have a look into the others, though I suspect they're problems
with tests rather than production code.

On Tue, Jun 21, 2016 at 6:53 PM, Marcelo Vanzin  wrote:
> On Tue, Jun 21, 2016 at 10:49 AM, Sean Owen  wrote:
>> I'm getting some errors building on Ubuntu 16 + Java 7. First is one
>> that may just be down to a Scala bug:
>>
>> [ERROR] bad symbolic reference. A signature in WebUI.class refers to
>> term eclipse
>> in package org which is not available.
>
> This is probably https://issues.apache.org/jira/browse/SPARK-13780. It
> should only affect incremental builds ("mvn -rf ..." or "mvn -pl
> ..."), not clean builds. Not sure about the other ones.
>
> --
> Marcelo

-
To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org
For additional commands, e-mail: dev-h...@spark.apache.org

Re: [VOTE] Release Apache Spark 1.6.2 (RC2)

[Marcelo Vanzin]

On Tue, Jun 21, 2016 at 10:49 AM, Sean Owen  wrote:
> I'm getting some errors building on Ubuntu 16 + Java 7. First is one
> that may just be down to a Scala bug:
>
> [ERROR] bad symbolic reference. A signature in WebUI.class refers to
> term eclipse
> in package org which is not available.

This is probably https://issues.apache.org/jira/browse/SPARK-13780. It
should only affect incremental builds ("mvn -rf ..." or "mvn -pl
..."), not clean builds. Not sure about the other ones.

-- 
Marcelo

-
To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org
For additional commands, e-mail: dev-h...@spark.apache.org

Re: [VOTE] Release Apache Spark 1.6.2 (RC2)

[Shixiong(Ryan) Zhu]

Hey Pete,

I didn't backport it to 1.6 because it just affects tests in most cases.
I'm sure we also have other places calling blocking methods in the event
loops, so similar issues are still there even after applying this patch.
Hence, I don't think it's a blocker for 1.6.2.

On Tue, Jun 21, 2016 at 2:57 AM, Pete Robbins  wrote:

> The PR (https://github.com/apache/spark/pull/13055) to fix
> https://issues.apache.org/jira/browse/SPARK-15262 was applied to 1.6.2
> however this fix caused another issue
> https://issues.apache.org/jira/browse/SPARK-15606 the fix for which (
> https://github.com/apache/spark/pull/13355) has not been backported to
> the 1.6 branch so I'm now seeing the same failure in 1.6.2
>
> Cheers,
>
> On Mon, 20 Jun 2016 at 05:25 Reynold Xin  wrote:
>
>> Please vote on releasing the following candidate as Apache Spark version
>> 1.6.2. The vote is open until Wednesday, June 22, 2016 at 22:00 PDT and
>> passes if a majority of at least 3+1 PMC votes are cast.
>>
>> [ ] +1 Release this package as Apache Spark 1.6.2
>> [ ] -1 Do not release this package because ...
>>
>>
>> The tag to be voted on is v1.6.2-rc2
>> (54b1121f351f056d6b67d2bb4efe0d553c0f7482)
>>
>> The release files, including signatures, digests, etc. can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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-1186/
>>
>> The documentation corresponding to this release can be found at:
>> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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 1.6.1.
>>
>> 
>> == What justifies a -1 vote for this release? ==
>> 
>> This is a maintenance release in the 1.6.x series.  Bugs already present
>> in 1.6.1, missing features, or bugs related to new features will not
>> necessarily block this release.
>>
>>
>>
>>

Re: [VOTE] Release Apache Spark 1.6.2 (RC2)

[Sean Owen]

I'm getting some errors building on Ubuntu 16 + Java 7. First is one
that may just be down to a Scala bug:

[ERROR] bad symbolic reference. A signature in WebUI.class refers to
term eclipse
in package org which is not available.
It may be completely missing from the current classpath, or the version on
the classpath might be incompatible with the version used when
compiling WebUI.class.
[ERROR] bad symbolic reference. A signature in WebUI.class refers to term jetty
in value org.eclipse which is not available.
It may be completely missing from the current classpath, or the version on
the classpath might be incompatible with the version used when
compiling WebUI.class.

But I'm seeing some consistent timezone-related failures, from core:

UIUtilsSuite:
- formatBatchTime *** FAILED ***
  "2015/05/14 [14]:04:40" did not equal "2015/05/14 [21]:04:40"
(UIUtilsSuite.scala:73)


and several from Spark SQL, like:


- udf_unix_timestamp *** FAILED ***
  Results do not match for udf_unix_timestamp:
  == Parsed Logical Plan ==
  'Project [unresolvedalias(2009-03-20
11:30:01),unresolvedalias('unix_timestamp(2009-03-20 11:30:01))]
  +- 'UnresolvedRelation `oneline`, None

  == Analyzed Logical Plan ==
  _c0: string, _c1: bigint
  Project [2009-03-20 11:30:01 AS _c0#122914,unixtimestamp(2009-03-20
11:30:01,-MM-dd HH:mm:ss) AS _c1#122915L]
  +- MetastoreRelation default, oneline, None

  == Optimized Logical Plan ==
  Project [2009-03-20 11:30:01 AS _c0#122914,1237548601 AS _c1#122915L]
  +- MetastoreRelation default, oneline, None

  == Physical Plan ==
  Project [2009-03-20 11:30:01 AS _c0#122914,1237548601 AS _c1#122915L]
  +- HiveTableScan MetastoreRelation default, oneline, None
  _c0 _c1
  !== HIVE - 1 row(s) ==== CATALYST - 1 row(s) ==
  !2009-03-20 11:30:01 1237573801   2009-03-20 11:30:01 1237548601
(HiveComparisonTest.scala:458)


I'll start looking into them. It could be real, if possibly minor,
bugs because I presume most of the testing happens on machines in a
PDT timezone instead of UTC? that's at least the timezone of the
machine I'm testing on.

On Mon, Jun 20, 2016 at 5:24 AM, Reynold Xin  wrote:
> Please vote on releasing the following candidate as Apache Spark version
> 1.6.2. The vote is open until Wednesday, June 22, 2016 at 22:00 PDT and
> passes if a majority of at least 3+1 PMC votes are cast.
>
> [ ] +1 Release this package as Apache Spark 1.6.2
> [ ] -1 Do not release this package because ...
>
>
> The tag to be voted on is v1.6.2-rc2
> (54b1121f351f056d6b67d2bb4efe0d553c0f7482)
>
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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-1186/
>
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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 1.6.1.
>
> 
> == What justifies a -1 vote for this release? ==
> 
> This is a maintenance release in the 1.6.x series.  Bugs already present in
> 1.6.1, missing features, or bugs related to new features will not
> necessarily block this release.
>
>
>

-
To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org
For additional commands, e-mail: dev-h...@spark.apache.org

Re: [VOTE] Release Apache Spark 1.6.2 (RC2)

[Pete Robbins]

It breaks Spark running on machines with less than 3 cores/threads, which
may be rare, and it is maybe an edge case.

Personally, I like to fix known bugs and the fact there are other blocking
methods in event loops actually makes it worse not to fix ones that you
know about.

Probably not a blocker to release though but that's your call.

Cheers,

On Tue, Jun 21, 2016 at 6:40 PM Shixiong(Ryan) Zhu 
wrote:

> Hey Pete,
>
> I didn't backport it to 1.6 because it just affects tests in most cases.
> I'm sure we also have other places calling blocking methods in the event
> loops, so similar issues are still there even after applying this patch.
> Hence, I don't think it's a blocker for 1.6.2.
>
> On Tue, Jun 21, 2016 at 2:57 AM, Pete Robbins  wrote:
>
>> The PR (https://github.com/apache/spark/pull/13055) to fix
>> https://issues.apache.org/jira/browse/SPARK-15262 was applied to 1.6.2
>> however this fix caused another issue
>> https://issues.apache.org/jira/browse/SPARK-15606 the fix for which (
>> https://github.com/apache/spark/pull/13355) has not been backported to
>> the 1.6 branch so I'm now seeing the same failure in 1.6.2
>>
>> Cheers,
>>
>> On Mon, 20 Jun 2016 at 05:25 Reynold Xin  wrote:
>>
>>> Please vote on releasing the following candidate as Apache Spark version
>>> 1.6.2. The vote is open until Wednesday, June 22, 2016 at 22:00 PDT and
>>> passes if a majority of at least 3+1 PMC votes are cast.
>>>
>>> [ ] +1 Release this package as Apache Spark 1.6.2
>>> [ ] -1 Do not release this package because ...
>>>
>>>
>>> The tag to be voted on is v1.6.2-rc2
>>> (54b1121f351f056d6b67d2bb4efe0d553c0f7482)
>>>
>>> The release files, including signatures, digests, etc. can be found at:
>>> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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-1186/
>>>
>>> The documentation corresponding to this release can be found at:
>>> http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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 1.6.1.
>>>
>>> 
>>> == What justifies a -1 vote for this release? ==
>>> 
>>> This is a maintenance release in the 1.6.x series.  Bugs already present
>>> in 1.6.1, missing features, or bugs related to new features will not
>>> necessarily block this release.
>>>
>>>
>>>
>>>
>

Re: [VOTE] Release Apache Spark 1.6.2 (RC2)

[Shixiong(Ryan) Zhu]

Hey Pete,

I just pushed your PR to branch 1.6. As it's not a blocker, it may or may
not be in 1.6.2, depending on if there will be another RC.

On Tue, Jun 21, 2016 at 1:36 PM, Pete Robbins  wrote:

> It breaks Spark running on machines with less than 3 cores/threads, which
> may be rare, and it is maybe an edge case.
>
> Personally, I like to fix known bugs and the fact there are other blocking
> methods in event loops actually makes it worse not to fix ones that you
> know about.
>
> Probably not a blocker to release though but that's your call.
>
> Cheers,
>
> On Tue, Jun 21, 2016 at 6:40 PM Shixiong(Ryan) Zhu <
> shixi...@databricks.com> wrote:
>
>> Hey Pete,
>>
>> I didn't backport it to 1.6 because it just affects tests in most cases.
>> I'm sure we also have other places calling blocking methods in the event
>> loops, so similar issues are still there even after applying this patch.
>> Hence, I don't think it's a blocker for 1.6.2.
>>
>> On Tue, Jun 21, 2016 at 2:57 AM, Pete Robbins 
>> wrote:
>>
>>> The PR (https://github.com/apache/spark/pull/13055) to fix
>>> https://issues.apache.org/jira/browse/SPARK-15262 was applied to 1.6.2
>>> however this fix caused another issue
>>> https://issues.apache.org/jira/browse/SPARK-15606 the fix for which (
>>> https://github.com/apache/spark/pull/13355) has not been backported to
>>> the 1.6 branch so I'm now seeing the same failure in 1.6.2
>>>
>>> Cheers,
>>>
>>> On Mon, 20 Jun 2016 at 05:25 Reynold Xin  wrote:
>>>
 Please vote on releasing the following candidate as Apache Spark
 version 1.6.2. The vote is open until Wednesday, June 22, 2016 at 22:00 PDT
 and passes if a majority of at least 3+1 PMC votes are cast.

 [ ] +1 Release this package as Apache Spark 1.6.2
 [ ] -1 Do not release this package because ...


 The tag to be voted on is v1.6.2-rc2
 (54b1121f351f056d6b67d2bb4efe0d553c0f7482)

 The release files, including signatures, digests, etc. can be found at:
 http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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-1186/

 The documentation corresponding to this release can be found at:
 http://people.apache.org/~pwendell/spark-releases/spark-1.6.2-rc2-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 1.6.1.

 
 == What justifies a -1 vote for this release? ==
 
 This is a maintenance release in the 1.6.x series.  Bugs already
 present in 1.6.1, missing features, or bugs related to new features will
 not necessarily block this release.




>>