Hi,
In hbase-spark module of hbase, we previously had this code:
def hbaseFieldToScalaType(
f: Field,
src: Array[Byte],
offset: Int,
length: Int): Any = {
...
case BinaryType =>
val newArray = new Array[Byte](length)
System.arraycopy(src, offse
Hi,
I'm concerned with the OOME in local mode with the version built today:
scala> val intsMM = 1 to math.pow(10, 3).toInt
intsMM: scala.collection.immutable.Range.Inclusive = Range(1, 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, 28, 29, 30, 31,
I think that this is a simpler case of
https://issues.apache.org/jira/browse/SPARK-17405. I'm going to comment on
that ticket with your simpler reproduction.
On Tue, Sep 6, 2016 at 1:32 PM Jacek Laskowski wrote:
> Hi,
>
> I'm concerned with the OOME in local mode with the version built today:
>
Hi,
I am trying to multiply Matrix of size 67584*67584 in a loop. In the first
iteration, multiplication goes through, but in the second iteration, it
fails with Java heap out of memory issue. I'm using pyspark and below is the
configuration.
Setup:
70 nodes (1driver+69 workers) with
SPARK_DRIVER_
Hi,
I am getting the following error , when I am trying to run jdbc docker
integration tests on my laptop. Any ideas , what I might be be doing wrong ?
build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -Phive-thriftserver
-Phive -DskipTests clean install
build/mvn -Pdocker-integration-t
Hi Josh,
Yes, that seems to be the issue. As I commented out in the JIRA, just
yesterday (after I had sent the email), such simple queries like the
following killed spark-shell:
Seq(1).toDF.groupBy('value).count.show
Hoping to see it get resolved soon. If there's anything I could help
you with t
Hi All,
Many users have requirements to use third party R packages in
executors/workers, but SparkR can not satisfy this requirements elegantly.
For example, you should to mess with the IT/administrators of the cluster
to deploy these R packages on each executors/workers node which is very
inflex
