Github user octavian-ganea commented on the pull request:
https://github.com/apache/spark/pull/1297#issuecomment-69505333
Writing the RDD to disk from time to time is not a solution for me. Also
the second idea it's not good if I am doing random put and get ops. A common
usecase is an SGD algorithm in which a large set of params need to be updated
(in parallel) . Is there any mutable version of this IndexedRDD that I could
use with Spark, a version that would have an interface similar to HashMap from
Java and that doesn't copy the entire RDD after each insert ? Many thanks!
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