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From Sean Owen <so...@cloudera.com>
Subject Re: Avoid broacasting huge variables
Date Sat, 20 Sep 2014 09:48:44 GMT
Joining in a side conversation - yes this is the way to go. The data is
immutable so can be shared across all executors in one JVM in a singleton.

How to load it depends on where it is but there is nothing special to Spark
here. For instance if the file is on HDFS then you use HDFS APIs in some
class in your app that implements the Singleton pattern and then you use
this class in your function to access data.
We normally copy a file to the nodes and then explicitly load it in a
function passed to mapPartitions.

On 9/20/14, octavian.ganea <octavian.ganea@inf.ethz.ch> wrote:
> Anyone ?
>
> Is there any option to load data in each node before starting any
> computation like it is the initialization of mappers in Hadoop ?
>
>
>
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--
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Martin Goodson
@martingoodson

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