You are viewing a plain text version of this content. The canonical link for it is here.
Posted to user@spark.apache.org by Jaonary Rabarisoa <ja...@gmail.com> on 2014/03/22 10:49:36 UTC
Yet another question on saving RDD into files
Dear all,
As a Spark newbie, I need some help to understand how RDD save to file
behaves. After reading the post on saving single files efficiently
http://apache-spark-user-list.1001560.n3.nabble.com/How-to-save-as-a-single-file-efficiently-td3014.html
I understand that each partition of the RDD is saved into a separate file,
isn't it ? And in order to get one single file, one should call
coalesce(1,shuffle=true), right ?
The other use case that I have is : append a RDD into existing file. Is it
possible with spark ? Precisely, I have a map transformation that results
vary over time, like a big time series :
I need to store the result for further analysis but if I store the RDD in
a different file each time I run the computation I may end with many little
files. A pseudo code of my process is as follow :
every tamestamp do
RDD[Array[Double]].map -> RDD[(timestamp,Double)].save to the same file
What should be the best solution to that ?
Best