For each partition results in having one instance of the lambda/closure per partition when e.g. publishing to output systems like message brokers, databases and file systems - that increases the level of parallelism of your output processing
-----Original Message----- From: dgoldenberg [mailto:dgoldenberg...@gmail.com] Sent: Wednesday, July 8, 2015 2:43 PM To: user@spark.apache.org Subject: foreachRDD vs. forearchPartition ? Is there a set of best practices for when to use foreachPartition vs. foreachRDD? Is it generally true that using foreachPartition avoids some of the over-network data shuffling overhead? When would I definitely want to use one method vs. the other? Thanks. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/foreachRDD-vs-forearchPa rtition-tp23714.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 --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
