I believe docs changes can go in anytime (because we can just publish new
versions of docs).
Critical bug fixes can still go in too.
On Thu, Aug 21, 2014 at 11:43 PM, Evan Chan wrote:
> I'm hoping to get in some doc enhancements and small bug fixes for Spark
> SQL.
>
> Also possibly a small ne
I'm hoping to get in some doc enhancements and small bug fixes for Spark SQL.
Also possibly a small new API to list the tables in sqlContext.
Oh, and to get the doc page I had talked about before, a list of
community Spark projects.
thanks,
Evan
-
Presto is so far good at joining different sources/databases.
I tried a simple join query in Spark SQL, it fails as the followings errors
val a = cql("select test.a from test JOIN test1 on test.a = test1.a")
a: org.apache.spark.sql.SchemaRDD =
SchemaRDD[0] at RDD at SchemaRDD.scala:104
== Query
Hi,
I have been playing around with Spark for the past few days, and evaluating
the possibility of migrating into Spark (Spark SQL) from Hive/Hadoop.
I am working on the WSO2 Business Activity Monitor (WSO2 BAM,
https://docs.wso2.com/display/BAM241/WSO2+Business+Activity+Monitor+Documentation
) w
bump.
I'm seeing the same issue with branch-1.1. Caching the RDD before running
saveAsTextFile gets things running but the job stalls 2/3 of the way by
using too much memory.
--
View this message in context:
http://apache-spark-developers-list.1001551.n3.nabble.com/saveAsTextFile-to-s3-on-spar
Hi,
Cross-posting this from users list.
I'm running on branch-1.1 and trying to do a simple transformation to a
relatively small dataset of 64GB and saveAsTextFile essentially hangs and
tasks are stuck in running mode with the following code:
// Stalls with tasks running for over an hour with n
Sandy,
I put spark.yarn.executor.memoryOverhead 1024 on spark-defaults.conf but I
don't see environment variable on spark properties on the webui->environment
Does it need to go in spark-env.sh ?
Thanks.
Deb
On Wed, Aug 20, 2014 at 12:39 AM, Sandy Ryza
wrote:
> Hi Debasish,
>
> The fix is to
Dear community,
Wow, I remember when we first open sourced the job server, at the
first Spark Summit in December. Since then, more and more of you have
started using it and contributing to it. It is awesome to see!
If you are not familiar with the spark job server, it is a REST API
for managin
We should add this link to the readme on GitHub btw.
2014년 8월 21일 목요일, Henry Saputra님이 작성한 메시지:
> The Apache Spark wiki on how to contribute should be great place to
> start:
> https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark
>
> - Henry
>
> On Thu, Aug 21, 2014 at 3:25 AM,
Hi All,
I am getting PARSING_ERROR while running my job on the code checked out up
to commit# db56f2df1b8027171da1b8d2571d1f2ef1e103b6. I am running this job
on EC2.
Any idea if there is something wrong with my config?
Here is my config:
--
.set("spark.executor.extraJavaOptions", "-XX:+UseC
The Apache Spark wiki on how to contribute should be great place to
start: https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark
- Henry
On Thu, Aug 21, 2014 at 3:25 AM, Maisnam Ns wrote:
> Hi,
>
> Can someone help me with some links on how to contribute for Spark
>
> Regards
>
Can someone from Databricks test and commit this PR? This is not a complete
solution, but would provide some relief.
https://github.com/apache/spark/pull/1391
Thanks,
Nishkam
On Wed, Aug 20, 2014 at 12:39 AM, Sandy Ryza
wrote:
> Hi Debasish,
>
> The fix is to raise spark.yarn.executor.memoryOv
Mridul,
Thanks for the suggestion.
I just updated the build today and changed the yarn/alpha/pom.xml to
1.1.1-SNAPSHOT
then the command worked.
I will create a JIRA and PR for it.
Chester
On Thu, Aug 21, 2014 at 8:03 AM, Chester @work
wrote:
> Do we have Jenkins tests these
I doubt it will work as expected.
Note that hiveContext.hql("select ...").regAsTable("a") will create a SchemaRDD
before register the SchemaRDD with the (Hive) catalog;
While sqlContext.jsonFile("xxx").regAsTable("b") will create a SchemaRDD before
register the SchemaRDD with the SparkSQL catalo
Do we have Jenkins tests these ? Should be pretty easy to setup just to test
basic build
Sent from my iPhone
> On Aug 21, 2014, at 6:45 AM, Mridul Muralidharan wrote:
>
> Weird that Patrick did not face this while creating the RC.
> Essentially the yarn alpha pom.xml has not been updated prope
Weird that Patrick did not face this while creating the RC.
Essentially the yarn alpha pom.xml has not been updated properly in
the 1.1 branch.
Just change version to '1.1.1-SNAPSHOT' for yarn/alpha/pom.xml (to
make it same as any other pom).
Regards,
Mridul
On Thu, Aug 21, 2014 at 5:09 AM, Ch
as far as i know, HQL queries try to find the schema info of all the tables
in this query from hive metastore, so it is not possible to join tables from
sqlContext using hiveContext.hql
but this should work:
hiveContext.hql("select ...").regAsTable("a")
sqlContext.jsonFile("xxx").regAsTable("b")
Hi everyone
I started looking at Kinesis integration and it looks promising. However,
I feel like it can be improved. Here are my thoughts:
1. It assumes that AWS credentials are provided
by DefaultAWSCredentialsProviderChain and there is no way to change the
behavior. I would have liked to have
Hi,
Can someone help me with some links on how to contribute for Spark
Regards
mns
Maven is just telling you that there is no version 1.1.0 of
yarn-parent, and indeed, it has not been released. To build the branch
you would need to "mvn install" to compile and make available local
copies of artifacts along the way. (You may have these for
1.1.0-SNAPSHOT locally already). Use Mave
The docs for this release are also available here:
http://people.apache.org/~pwendell/spark-1.1.0-snapshot2-docs/
On Thu, Aug 21, 2014 at 1:12 AM, Patrick Wendell wrote:
> Hi All,
>
> I've packaged and published a snapshot release of Spark 1.1 for testing.
> This is very close to RC1 and we ar
Hi All,
I've packaged and published a snapshot release of Spark 1.1 for testing.
This is very close to RC1 and we are distributing it for testing. Please
test this and report any issues on this thread.
The tag of this release is v1.1.0-snapshot1 (commit e1535ad3):
*https://git-wip-us.apache.org/r
The stream receiver seems to leverage actor receivers
http://spark.apache.org/docs/0.8.1/streaming-custom-receivers.html
But spark system doesnt lend itself to a messaging kind of a structure..
more of a DAG kind
Just curious are you looking for the actor subsystem to act on messages or
just l
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