In order to get a major speedup from applying *single-pass* map/filter/reduce
operations on an array in GPU memory, wouldn't you need to stream the
columnar data directly into GPU memory somehow? You might find in your
experiments that GPU memory allocation is a bottleneck. See e.g. John
Canny's
> On 9 Sep 2015, at 20:18, lonikar wrote:
>
> I have seen a perf improvement of 5-10 times on expression evaluation even
> on "ordinary" laptop GPUs. Thus, it will be a good demo along with some
> concrete proposals for vectorization. As you said, I will have to hook up to
>
The following fails for me in Spark 1.5:
https://gist.github.com/nitay/d08cb294ccf00b80c49a
Specifically, it returns 1 instead of 100 (in both versions).
When I print out the contents (i.e. collect()) I see all 100 items, yet the
count returns 1.
This works in 1.3 and 1.4.
Any ideas what's going
I found these files:
spark-1.5.0/sql/catalyst/*src/main/scala*/org/apache/spark/sql/types/*SQLUserDefinedType.java*
spark-1.5.0/core/src/main/java/org/apache/spark/api/java/function/package.scala
and several java files in spark-1.5.0/core/src/main/scala/.
Is this intentional or inadvertant?
I feel like I knew the answer to this but have forgotten. Reynold do
you know about this file? looks like you added it.
On Thu, Sep 10, 2015 at 1:10 PM, lonikar wrote:
> I found these files:
>
Look at this code:
https://github.com/apache/spark/blob/branch-1.5/sql/core/src/main/scala/org/apache/spark/sql/execution/SQLExecution.scala#L42
and
https://github.com/apache/spark/blob/branch-1.5/sql/core/src/main/scala/org/apache/spark/sql/execution/SQLExecution.scala#L87
This exception is
Can you open a JIRA?
On Wed, Sep 9, 2015 at 11:11 PM, StanZhai wrote:
> After upgrade spark from 1.4.1 to 1.5.0, I encountered the following
> exception when use alter table statement in HiveContext:
>
> The sql is: ALTER TABLE a RENAME TO b
>
> The exception is:
>
> FAILED:
Does this still happen on 1.5.0 release?
On Mon, Aug 31, 2015 at 9:31 AM, Olivier Girardot wrote:
> tested now against Spark 1.5.0 rc2, and same exceptions happen when
> num-executors > 2 :
>
> 15/08/25 10:31:10 WARN scheduler.TaskSetManager: Lost task 0.1 in stage
> 5.0
@Olivier, did you use scala's parallel collections by any chance? If not,
what form of concurrency were you using?
2015-09-10 13:01 GMT-07:00 Andrew Or :
> Thanks for reporting this, I have filed
> https://issues.apache.org/jira/browse/SPARK-10548.
>
> 2015-09-10 9:09
Thank you for the swift reply!
The version of my hive metastore server is 0.13.1, I've build spark use sbt
like this:
build/sbt -Pyarn -Phadoop-2.4 -Phive -Phive-thriftserver assembly
Is spark 1.5 bind the hive client version of 1.2 by default?
--
View this message in context:
Yes, Spark 1.5 use Hive 1.2's metastore client by default. You can change
it by putting the following settings in your spark conf.
spark.sql.hive.metastore.version = 0.13.1
spark.sql.hive.metastore.jars = maven or the path of your hive 0.13 jars
and hadoop jars
For spark.sql.hive.metastore.jars,
This is probably true as the scala plugin actually compiles both
.scala and .java files. Still it seems like the wrong place just as a
matter of style. Can we try moving it and verify it's still OK?
On Fri, Sep 11, 2015 at 12:43 AM, Reynold Xin wrote:
> There isn't really
Thanks for reporting this, I have filed
https://issues.apache.org/jira/browse/SPARK-10548.
2015-09-10 9:09 GMT-07:00 Olivier Toupin :
> Look at this code:
>
>
>
After upgrade spark from 1.4.1 to 1.5.0, I encountered the following
exception when use alter table statement in HiveContext:
The sql is: ALTER TABLE a RENAME TO b
The exception is:
FAILED: Execution Error, return code 1 from
org.apache.hadoop.hive.ql.exec.DDLTask. Unable to alter table.
Thanks for pointing this out.
https://issues.apache.org/jira/browse/SPARK-10539
We will fix this for Spark 1.5.1.
On Thu, Sep 10, 2015 at 6:16 AM, Nitay Joffe wrote:
> The following fails for me in Spark 1.5:
> https://gist.github.com/nitay/d08cb294ccf00b80c49a
>
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