Yes, it was done on purpose to match the behavior of Hive (
https://issues.apache.org/jira/browse/SPARK-10865).
And I believe Hive returns `Long`s because they adopted the definition used
in MySQL (https://issues.apache.org/jira/browse/HIVE-615).
On Fri, May 19, 2017 at 10:51 AM, Anton Okolnychyi
If someone else is looking how to try jdk9, you can just pass your own
JAVA_HOME environment variables:
spark.yarn.appMasterEnv.JAVA_HOME=/usr/lib/jvm/java-1.8.0
spark.executorEnv.JAVA_HOME=/usr/lib/jvm/java-1.8.0
On Fri, Oct 27, 2017 at 5:14 AM, Steve Loughran
wrote:
>
> On 27 Oct 2017, at 0
Probably not Oracle but Cloudera 🙂
Jan, I think your DataNodes might be overloaded, I'd suggest reducing
`spark.executor.cores` if you run executors alongside DataNodes, so the
DataNode process would get some resources.
The other thing you can do is to increase `dfs.client.socket-timeout` in
hado
The error message seems self-explanatory, try to figure out what's the disk
quota you have for your user.
On Wed, Nov 22, 2017 at 8:23 AM, Chetan Khatri
wrote:
> Anybody reply on this ?
>
> On Tue, Nov 21, 2017 at 3:36 PM, Chetan Khatri <
> chetan.opensou...@gmail.com> wrote:
>
>>
>> Hello Spark
not possible, but you can add your own object in your project to the
spark's package that would give you access to private methods
package org.apache.spark.sql
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.execution.LogicalRDD
import
