+1
----
Ricardo Almeida
On 20 May 2016 at 18:33, Mark Hamstra <m...@clearstorydata.com> wrote:
> This is isn't yet a release candidate since, as Reynold mention in his
> opening post, preview releases are "not meant to be functional, i.e. they
> can and highly likely will contain critical bugs or documentation errors."
> Once we're at the point where we expect there not to be such bugs and
> errors, then the release candidates will start.
>
> On Fri, May 20, 2016 at 4:40 AM, Ross Lawley <ross.law...@gmail.com>
> wrote:
>
>> +1 Having an rc1 would help me get stable feedback on using my library
>> with Spark, compared to relying on 2.0.0-SNAPSHOT.
>>
>>
>> On Fri, 20 May 2016 at 05:57 Xiao Li <gatorsm...@gmail.com> wrote:
>>
>>> Changed my vote to +1. Thanks!
>>>
>>> 2016-05-19 13:28 GMT-07:00 Xiao Li <gatorsm...@gmail.com>:
>>>
>>>> Will do. Thanks!
>>>>
>>>> 2016-05-19 13:26 GMT-07:00 Reynold Xin <r...@databricks.com>:
>>>>
>>>>> Xiao thanks for posting. Please file a bug in JIRA. Again as I said in
>>>>> the email this is not meant to be a functional release and will contain
>>>>> bugs.
>>>>>
>>>>> On Thu, May 19, 2016 at 1:20 PM, Xiao Li <gatorsm...@gmail.com> wrote:
>>>>>
>>>>>> -1
>>>>>>
>>>>>> Unable to use Hive meta-store in pyspark shell. Tried both
>>>>>> HiveContext and SparkSession. Both failed. It always uses in-memory
>>>>>> catalog. Anybody else hit the same issue?
>>>>>>
>>>>>>
>>>>>> Method 1: SparkSession
>>>>>>
>>>>>> >>> from pyspark.sql import SparkSession
>>>>>>
>>>>>> >>> spark = SparkSession.builder.enableHiveSupport().getOrCreate()
>>>>>>
>>>>>> >>>
>>>>>>
>>>>>> >>> spark.sql("CREATE TABLE IF NOT EXISTS src (key INT, value
>>>>>> STRING)")
>>>>>>
>>>>>> DataFrame[]
>>>>>>
>>>>>> >>> spark.sql("LOAD DATA LOCAL INPATH
>>>>>> 'examples/src/main/resources/kv1.txt' INTO TABLE src")
>>>>>>
>>>>>> Traceback (most recent call last):
>>>>>>
>>>>>> File "<stdin>", line 1, in <module>
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/session.py",
>>>>>> line 494, in sql
>>>>>>
>>>>>> return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py",
>>>>>> line 933, in __call__
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py",
>>>>>> line 57, in deco
>>>>>>
>>>>>> return f(*a, **kw)
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py",
>>>>>> line 312, in get_return_value
>>>>>>
>>>>>> py4j.protocol.Py4JJavaError: An error occurred while calling o21.sql.
>>>>>>
>>>>>> : java.lang.UnsupportedOperationException: loadTable is not
>>>>>> implemented
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.catalyst.catalog.InMemoryCatalog.loadTable(InMemoryCatalog.scala:297)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.catalyst.catalog.SessionCatalog.loadTable(SessionCatalog.scala:280)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.LoadData.run(tables.scala:263)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:57)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:55)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:69)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:85)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:85)
>>>>>>
>>>>>> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:187)
>>>>>>
>>>>>> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:168)
>>>>>>
>>>>>> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63)
>>>>>>
>>>>>> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:541)
>>>>>>
>>>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>>>
>>>>>> at
>>>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>>>>
>>>>>> at
>>>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>>>>
>>>>>> at java.lang.reflect.Method.invoke(Method.java:606)
>>>>>>
>>>>>> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
>>>>>>
>>>>>> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
>>>>>>
>>>>>> at py4j.Gateway.invoke(Gateway.java:280)
>>>>>>
>>>>>> at
>>>>>> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
>>>>>>
>>>>>> at py4j.commands.CallCommand.execute(CallCommand.java:79)
>>>>>>
>>>>>> at py4j.GatewayConnection.run(GatewayConnection.java:211)
>>>>>>
>>>>>> at java.lang.Thread.run(Thread.java:745)
>>>>>>
>>>>>>
>>>>>> Method 2: Using HiveContext:
>>>>>>
>>>>>> >>> from pyspark.sql import HiveContext
>>>>>>
>>>>>> >>> sqlContext = HiveContext(sc)
>>>>>>
>>>>>> >>> sqlContext.sql("CREATE TABLE IF NOT EXISTS src (key INT, value
>>>>>> STRING)")
>>>>>>
>>>>>> DataFrame[]
>>>>>>
>>>>>> >>> sqlContext.sql("LOAD DATA LOCAL INPATH
>>>>>> 'examples/src/main/resources/kv1.txt' INTO TABLE src")
>>>>>>
>>>>>> Traceback (most recent call last):
>>>>>>
>>>>>> File "<stdin>", line 1, in <module>
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/context.py",
>>>>>> line 346, in sql
>>>>>>
>>>>>> return self.sparkSession.sql(sqlQuery)
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/session.py",
>>>>>> line 494, in sql
>>>>>>
>>>>>> return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py",
>>>>>> line 933, in __call__
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py",
>>>>>> line 57, in deco
>>>>>>
>>>>>> return f(*a, **kw)
>>>>>>
>>>>>> File
>>>>>> "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py",
>>>>>> line 312, in get_return_value
>>>>>>
>>>>>> py4j.protocol.Py4JJavaError: An error occurred while calling o21.sql.
>>>>>>
>>>>>> : java.lang.UnsupportedOperationException: loadTable is not
>>>>>> implemented
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.catalyst.catalog.InMemoryCatalog.loadTable(InMemoryCatalog.scala:297)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.catalyst.catalog.SessionCatalog.loadTable(SessionCatalog.scala:280)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.LoadData.run(tables.scala:263)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:57)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:55)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:69)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:85)
>>>>>>
>>>>>> at
>>>>>> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:85)
>>>>>>
>>>>>> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:187)
>>>>>>
>>>>>> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:168)
>>>>>>
>>>>>> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63)
>>>>>>
>>>>>> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:541)
>>>>>>
>>>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>>>
>>>>>> at
>>>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>>>>
>>>>>> at
>>>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>>>>
>>>>>> at java.lang.reflect.Method.invoke(Method.java:606)
>>>>>>
>>>>>> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
>>>>>>
>>>>>> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
>>>>>>
>>>>>> at py4j.Gateway.invoke(Gateway.java:280)
>>>>>>
>>>>>> at
>>>>>> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
>>>>>>
>>>>>> at py4j.commands.CallCommand.execute(CallCommand.java:79)
>>>>>>
>>>>>> at py4j.GatewayConnection.run(GatewayConnection.java:211)
>>>>>>
>>>>>> at java.lang.Thread.run(Thread.java:745)
>>>>>>
>>>>>> 2016-05-19 12:49 GMT-07:00 Herman van Hövell tot Westerflier <
>>>>>> hvanhov...@questtec.nl>:
>>>>>>
>>>>>>> +1
>>>>>>>
>>>>>>>
>>>>>>> 2016-05-19 18:20 GMT+02:00 Xiangrui Meng <m...@databricks.com>:
>>>>>>>
>>>>>>>> +1
>>>>>>>>
>>>>>>>> On Thu, May 19, 2016 at 9:18 AM Joseph Bradley <
>>>>>>>> jos...@databricks.com> wrote:
>>>>>>>>
>>>>>>>>> +1
>>>>>>>>>
>>>>>>>>> On Wed, May 18, 2016 at 10:49 AM, Reynold Xin <r...@databricks.com
>>>>>>>>> > wrote:
>>>>>>>>>
>>>>>>>>>> Hi Ovidiu-Cristian ,
>>>>>>>>>>
>>>>>>>>>> The best source of truth is change the filter with target version
>>>>>>>>>> to 2.1.0. Not a lot of tickets have been targeted yet, but I'd
>>>>>>>>>> imagine as
>>>>>>>>>> we get closer to 2.0 release, more will be retargeted at 2.1.0.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Wed, May 18, 2016 at 10:43 AM, Ovidiu-Cristian MARCU <
>>>>>>>>>> ovidiu-cristian.ma...@inria.fr> wrote:
>>>>>>>>>>
>>>>>>>>>>> Yes, I can filter..
>>>>>>>>>>> Did that and for example:
>>>>>>>>>>>
>>>>>>>>>>> https://issues.apache.org/jira/browse/SPARK-15370?jql=project%20%3D%20SPARK%20AND%20resolution%20%3D%20Unresolved%20AND%20affectedVersion%20%3D%202.0.0
>>>>>>>>>>> <https://issues.apache.org/jira/browse/SPARK-15370?jql=project%20=%20SPARK%20AND%20resolution%20=%20Unresolved%20AND%20affectedVersion%20=%202.0.0>
>>>>>>>>>>>
>>>>>>>>>>> To rephrase: for 2.0 do you have specific issues that are not a
>>>>>>>>>>> priority and will released maybe with 2.1 for example?
>>>>>>>>>>>
>>>>>>>>>>> Keep up the good work!
>>>>>>>>>>>
>>>>>>>>>>> On 18 May 2016, at 18:19, Reynold Xin <r...@databricks.com>
>>>>>>>>>>> wrote:
>>>>>>>>>>>
>>>>>>>>>>> You can find that by changing the filter to target version =
>>>>>>>>>>> 2.0.0. Cheers.
>>>>>>>>>>>
>>>>>>>>>>> On Wed, May 18, 2016 at 9:00 AM, Ovidiu-Cristian MARCU <
>>>>>>>>>>> ovidiu-cristian.ma...@inria.fr> wrote:
>>>>>>>>>>>
>>>>>>>>>>>> +1 Great, I see the list of resolved issues, do you have a list
>>>>>>>>>>>> of known issue you plan to stay with this release?
>>>>>>>>>>>>
>>>>>>>>>>>> with
>>>>>>>>>>>> build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.7.1 -Phive
>>>>>>>>>>>> -Phive-thriftserver -DskipTests clean package
>>>>>>>>>>>>
>>>>>>>>>>>> mvn -version
>>>>>>>>>>>> Apache Maven 3.3.9 (bb52d8502b132ec0a5a3f4c09453c07478323dc5;
>>>>>>>>>>>> 2015-11-10T17:41:47+01:00)
>>>>>>>>>>>> Maven home: /Users/omarcu/tools/apache-maven-3.3.9
>>>>>>>>>>>> Java version: 1.7.0_80, vendor: Oracle Corporation
>>>>>>>>>>>> Java home:
>>>>>>>>>>>> /Library/Java/JavaVirtualMachines/jdk1.7.0_80.jdk/Contents/Home/jre
>>>>>>>>>>>> Default locale: en_US, platform encoding: UTF-8
>>>>>>>>>>>> OS name: "mac os x", version: "10.11.5", arch: "x86_64",
>>>>>>>>>>>> family: “mac"
>>>>>>>>>>>>
>>>>>>>>>>>> [INFO] Reactor Summary:
>>>>>>>>>>>> [INFO]
>>>>>>>>>>>> [INFO] Spark Project Parent POM ...........................
>>>>>>>>>>>> SUCCESS [ 2.635 s]
>>>>>>>>>>>> [INFO] Spark Project Tags .................................
>>>>>>>>>>>> SUCCESS [ 1.896 s]
>>>>>>>>>>>> [INFO] Spark Project Sketch ...............................
>>>>>>>>>>>> SUCCESS [ 2.560 s]
>>>>>>>>>>>> [INFO] Spark Project Networking ...........................
>>>>>>>>>>>> SUCCESS [ 6.533 s]
>>>>>>>>>>>> [INFO] Spark Project Shuffle Streaming Service ............
>>>>>>>>>>>> SUCCESS [ 4.176 s]
>>>>>>>>>>>> [INFO] Spark Project Unsafe ...............................
>>>>>>>>>>>> SUCCESS [ 4.809 s]
>>>>>>>>>>>> [INFO] Spark Project Launcher .............................
>>>>>>>>>>>> SUCCESS [ 6.242 s]
>>>>>>>>>>>> [INFO] Spark Project Core .................................
>>>>>>>>>>>> SUCCESS [01:20 min]
>>>>>>>>>>>> [INFO] Spark Project GraphX ...............................
>>>>>>>>>>>> SUCCESS [ 9.148 s]
>>>>>>>>>>>> [INFO] Spark Project Streaming ............................
>>>>>>>>>>>> SUCCESS [ 22.760 s]
>>>>>>>>>>>> [INFO] Spark Project Catalyst .............................
>>>>>>>>>>>> SUCCESS [ 50.783 s]
>>>>>>>>>>>> [INFO] Spark Project SQL ..................................
>>>>>>>>>>>> SUCCESS [01:05 min]
>>>>>>>>>>>> [INFO] Spark Project ML Local Library .....................
>>>>>>>>>>>> SUCCESS [ 4.281 s]
>>>>>>>>>>>> [INFO] Spark Project ML Library ...........................
>>>>>>>>>>>> SUCCESS [ 54.537 s]
>>>>>>>>>>>> [INFO] Spark Project Tools ................................
>>>>>>>>>>>> SUCCESS [ 0.747 s]
>>>>>>>>>>>> [INFO] Spark Project Hive .................................
>>>>>>>>>>>> SUCCESS [ 33.032 s]
>>>>>>>>>>>> [INFO] Spark Project HiveContext Compatibility ............
>>>>>>>>>>>> SUCCESS [ 3.198 s]
>>>>>>>>>>>> [INFO] Spark Project REPL .................................
>>>>>>>>>>>> SUCCESS [ 3.573 s]
>>>>>>>>>>>> [INFO] Spark Project YARN Shuffle Service .................
>>>>>>>>>>>> SUCCESS [ 4.617 s]
>>>>>>>>>>>> [INFO] Spark Project YARN .................................
>>>>>>>>>>>> SUCCESS [ 7.321 s]
>>>>>>>>>>>> [INFO] Spark Project Hive Thrift Server ...................
>>>>>>>>>>>> SUCCESS [ 16.496 s]
>>>>>>>>>>>> [INFO] Spark Project Assembly .............................
>>>>>>>>>>>> SUCCESS [ 2.300 s]
>>>>>>>>>>>> [INFO] Spark Project External Flume Sink ..................
>>>>>>>>>>>> SUCCESS [ 4.219 s]
>>>>>>>>>>>> [INFO] Spark Project External Flume .......................
>>>>>>>>>>>> SUCCESS [ 6.987 s]
>>>>>>>>>>>> [INFO] Spark Project External Flume Assembly ..............
>>>>>>>>>>>> SUCCESS [ 1.465 s]
>>>>>>>>>>>> [INFO] Spark Integration for Kafka 0.8 ....................
>>>>>>>>>>>> SUCCESS [ 6.891 s]
>>>>>>>>>>>> [INFO] Spark Project Examples .............................
>>>>>>>>>>>> SUCCESS [ 13.465 s]
>>>>>>>>>>>> [INFO] Spark Project External Kafka Assembly ..............
>>>>>>>>>>>> SUCCESS [ 2.815 s]
>>>>>>>>>>>> [INFO]
>>>>>>>>>>>> ------------------------------------------------------------------------
>>>>>>>>>>>> [INFO] BUILD SUCCESS
>>>>>>>>>>>> [INFO]
>>>>>>>>>>>> ------------------------------------------------------------------------
>>>>>>>>>>>> [INFO] Total time: 07:04 min
>>>>>>>>>>>> [INFO] Finished at: 2016-05-18T17:55:33+02:00
>>>>>>>>>>>> [INFO] Final Memory: 90M/824M
>>>>>>>>>>>> [INFO]
>>>>>>>>>>>> ------------------------------------------------------------------------
>>>>>>>>>>>>
>>>>>>>>>>>> On 18 May 2016, at 16:28, Sean Owen <so...@cloudera.com> wrote:
>>>>>>>>>>>>
>>>>>>>>>>>> I think it's a good idea. Although releases have been preceded
>>>>>>>>>>>> before
>>>>>>>>>>>> by release candidates for developers, it would be good to get a
>>>>>>>>>>>> formal
>>>>>>>>>>>> preview/beta release ratified for public consumption ahead of a
>>>>>>>>>>>> new
>>>>>>>>>>>> major release. Better to have a little more testing in the wild
>>>>>>>>>>>> to
>>>>>>>>>>>> identify problems before 2.0.0 is finalized.
>>>>>>>>>>>>
>>>>>>>>>>>> +1 to the release. License, sigs, etc check out. On Ubuntu 16 +
>>>>>>>>>>>> Java
>>>>>>>>>>>> 8, compilation and tests succeed for "-Pyarn -Phive
>>>>>>>>>>>> -Phive-thriftserver -Phadoop-2.6".
>>>>>>>>>>>>
>>>>>>>>>>>> On Wed, May 18, 2016 at 6:40 AM, Reynold Xin <r...@apache.org>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>>
>>>>>>>>>>>> Hi,
>>>>>>>>>>>>
>>>>>>>>>>>> In the past the Apache Spark community have created preview
>>>>>>>>>>>> packages (not
>>>>>>>>>>>> official releases) and used those as opportunities to ask
>>>>>>>>>>>> community members
>>>>>>>>>>>> to test the upcoming versions of Apache Spark. Several people
>>>>>>>>>>>> in the Apache
>>>>>>>>>>>> community have suggested we conduct votes for these preview
>>>>>>>>>>>> packages and
>>>>>>>>>>>> turn them into formal releases by the Apache foundation's
>>>>>>>>>>>> standard. Preview
>>>>>>>>>>>> releases are not meant to be functional, i.e. they can and
>>>>>>>>>>>> highly likely
>>>>>>>>>>>> will contain critical bugs or documentation errors, but we will
>>>>>>>>>>>> be able to
>>>>>>>>>>>> post them to the project's website to get wider feedback. They
>>>>>>>>>>>> should
>>>>>>>>>>>> satisfy the legal requirements of Apache's release policy
>>>>>>>>>>>> (http://www.apache.org/dev/release.html) such as having proper
>>>>>>>>>>>> licenses.
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> Please vote on releasing the following candidate as Apache
>>>>>>>>>>>> Spark version
>>>>>>>>>>>> 2.0.0-preview. The vote is open until Friday, May 20, 2015 at
>>>>>>>>>>>> 11:00 PM 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-preview
>>>>>>>>>>>> [ ] -1 Do not release this package because ...
>>>>>>>>>>>>
>>>>>>>>>>>> To learn more about Apache Spark, please see
>>>>>>>>>>>> http://spark.apache.org/
>>>>>>>>>>>>
>>>>>>>>>>>> The tag to be voted on is 2.0.0-preview
>>>>>>>>>>>> (8f5a04b6299e3a47aca13cbb40e72344c0114860)
>>>>>>>>>>>>
>>>>>>>>>>>> The release files, including signatures, digests, etc. can be
>>>>>>>>>>>> found at:
>>>>>>>>>>>>
>>>>>>>>>>>> http://home.apache.org/~pwendell/spark-releases/spark-2.0.0-preview-bin/
>>>>>>>>>>>>
>>>>>>>>>>>> Release artifacts are signed with the following key:
>>>>>>>>>>>> https://people.apache.org/keys/committer/pwendell.asc
>>>>>>>>>>>>
>>>>>>>>>>>> The documentation corresponding to this release can be found at:
>>>>>>>>>>>>
>>>>>>>>>>>> http://home.apache.org/~pwendell/spark-releases/spark-2.0.0-preview-docs/
>>>>>>>>>>>>
>>>>>>>>>>>> The list of resolved issues are:
>>>>>>>>>>>>
>>>>>>>>>>>> https://issues.apache.org/jira/browse/SPARK-15351?jql=project%20%3D%20SPARK%20AND%20fixVersion%20%3D%202.0.0
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> If you are a Spark user, you can help us test this release by
>>>>>>>>>>>> taking an
>>>>>>>>>>>> existing Apache Spark workload and running on this candidate,
>>>>>>>>>>>> then reporting
>>>>>>>>>>>> any regressions.
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> ---------------------------------------------------------------------
>>>>>>>>>>>> To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org
>>>>>>>>>>>> For additional commands, e-mail: dev-h...@spark.apache.org
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>
