I don't think it is possible that way. Spark streaming is a minibatch processing system.
If processing contents of 2 batch is your objective what you can do is 1) keep a cache(or two) that represent the previous batch(s). 2) every new batch replaces the old cache by one time slot back. 3) you process each batch as rdd in parallel. ...Manas -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/how-to-spark-streaming-application-start-working-on-next-batch-before-completing-on-previous-batch-tp25559p25581.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
