Unfortunately it's very difficult to get uncaching right with GraphX due to the complicated internal dependency structure that it creates. It's necessary to know exactly what operations you're doing on the graph in order to unpersist correctly (i.e., in a way that avoids recomputation).
I have a pull request (https://github.com/apache/spark/pull/497) that may make this a bit easier, but your best option is to use the Pregel API for iterative algorithms if possible. If that's not possible, leaving things cached has actually not been very costly in my experience, at least as long as VD and ED are primitive types to reduce the load on the garbage collector. Ankur -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Caching-in-graphX-tp5482p5514.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
