There was a proposal to make schedulers pluggable in context of adding one
which leverages Apache Tez : IIRC it was a abandoned - but the jira might
be a good starting point.
Regards
Mridul
On Dec 3, 2015 2:59 PM, "Rad Gruchalski" wrote:
> There was a talk in this thread
Excuse me,
I'm working on SPARK-10259.(this parent issue is SPARK-7751.)
https://issues.apache.org/jira/browse/SPARK-10259
This issues's purpose is to add @Since annotation to stable and experimenal
methods in MLlib.
in SPARK-7751, this and this children issues' target version is v.1.6.0,
but
Reynold, did you (or someone else) delete version 1.7.0 in JIRA? I
think that's premature. If there's a 1.7.0 then we've lost info about
what it would contain. It's trivial at any later point to merge the
versions. And, since things change and there's not a pressing need to
decide one way or the
+1
OSX 10.10.5, java version "1.8.0_40", scala 2.10
mvn clean package -DskipTests
[INFO] Spark Project External Kafka ... SUCCESS [ 18.161
s]
[INFO] Spark Project Examples . SUCCESS [01:18
min]
[INFO] Spark Project External Kafka Assembly
I reported this in the 1.6 preview thread, but wouldn't mind if someone can
confirm that ctrl-c is not keyboard interrupting / clearing the current line
of input anymore in the pyspark shell. I saw the change that would kill the
currently running job when using ctrl+c, but now the only way to
+1 (non binding)
Tested our pipelines on a Spark 1.6.0 standalone cluster (Python only):
- Pyspark package
- Spark SQL
- Dataframes
- Spark MLlib
No major issues, good performance.
Just a minor distinct behavior from version 1.4.1 using a SQLContext:
"select case myColumn when null then 'Y'
Hi,
Wanted to pick Cody's mind on what he thinks about
DirectKafkaInputDStream/KafkaRDD internally using the new Kafka consumer
API. I know the latter is documented as beta-quality, but yet wanted to
know if he sees any blockers as to why shouldn't go there shortly. On my
side the consideration
Pardon for tacking on one more message to this thread, but I'm
reminded of one more issue when building the RC today: Scala 2.10 does
not in general try to work with Java 8, and indeed I can never fully
compile it with Java 8 on Ubuntu or OS X, due to scalac assertion
errors. 2.11 is the first
spark 1.x has been supporting scala 2.11 for 3 or 4 releases now. seems to
me you already provide a clear upgrade path: get on scala 2.11 before
upgrading to spark 2.x
from scala team when scala 2.10.6 came out:
We strongly encourage you to upgrade to the latest stable version of Scala
2.11.x, as
Does this https://github.com/apache/spark/pull/10134 is valid fix?
(still worse than 1.5)
On Thu, Dec 3, 2015 at 8:45 AM, mkhaitman wrote:
> I reported this in the 1.6 preview thread, but wouldn't mind if someone can
> confirm that ctrl-c is not keyboard interrupting /
Licenses and signature are all fine.
Docker integration tests consistently fail for me with Java 7 / Ubuntu
and "-Pyarn -Phadoop-2.6 -Phive -Phive-thriftserver"
*** RUN ABORTED ***
java.lang.NoSuchMethodError:
There was a talk in this thread about removing the fine-grained Mesos
scheduler. I think it would a loss to lose it completely, however, I understand
that it might be a burden to keep it under development for Mesos only.
Having been thinking about it for a while, it would be great if the
Try to read this before Marcelo gets to you.
https://issues.apache.org/jira/browse/SPARK-11157
On Thu, Dec 3, 2015 at 5:27 PM, Matt Cheah wrote:
> Hi everyone,
>
> A very brief question out of curiosity – is there any particular reason
> why we don’t publish the Spark
On Mon, Nov 30, 2015 at 1:53 PM, Josh Rosen
wrote:
> The JDBC drivers are currently being pulled in as test-scope dependencies
> of the `sql/core` module:
> https://github.com/apache/spark/blob/f2fbfa444f6e8d27953ec2d1c0b3abd603c963f9/sql/core/pom.xml#L91
>
> In SBT,
Hi everyone,
A very brief question out of curiosity is there any particular reason why
we don¹t publish the Spark assembly jar on the Maven repository?
Thanks,
-Matt Cheah
smime.p7s
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I try to do test on HiveSparkSubmitSuite on local box, but fails. The cause
is that spark is still using my local single node cluster hadoop when doing
the unit test. I don't think it make sense to do that. These environment
variable should be unset before the testing. And I suspect dev/run-tests
Honestly my feeling on any new API is to wait for a point release before
taking it seriously :)
Auth and encryption seem like the only compelling reason to move, but
forcing people on kafka 8.x to upgrade their brokers is questionable.
On Thu, Dec 3, 2015 at 11:30 AM, Mario Ds Briggs
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