Try to reproduce what the spark-submit shell script does, setting up the class
path etc.
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> On Nov 9, 2015, at 7:07 AM, Tathagata Das wrote:
>
> You cannot submit from eclipse to a cluster that easily. You can run locally
> (master set to
While I have a preference for Scala ( not surprising as a Typesafe person), the
DataFrame API gives feature and performance parity for Python. The RDD API
gives feature parity.
So, use what makes you most successful for other reasons ;)
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> On Oct 6, 2015, at 4:14
You are mixing the 1.0.0 Spark SQL jar with Spark 1.4.0 jars in your build file
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On Jul 14, 2015, at 7:57 AM, ashwang168 ashw...@mit.edu wrote:
Hello!
I am currently using Spark 1.4.0, scala 2.10.4, and sbt 0.13.8 to try and
create a jar file from a scala file
There is no mechanism for keeping an RDD up to date with a changing source.
However you could set up a steam that watches for changes to the directory and
processes the new files or use the Hive integration in SparkSQL to run Hive
queries directly. (However, old query results will still grow
Show us the code. This shouldn't happen for the simple process you described
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On Mar 27, 2015, at 5:47 AM, jamborta jambo...@gmail.com wrote:
Hi all,
We have a workflow that pulls in data from csv files, then originally setup
up of the workflow was to parse