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.ga...@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 ? > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Avoid-broacasting-huge-variables-tp14696p14726.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > > -- -- Martin Goodson @martingoodson - --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
