Out of curiosity, is there a way to pull all the data back to the driver to save without collect()? That is, stream the data in chunks back to the driver so that maximum memory used comparable to a single node’s data, but all the data is saved on one node.
— Pedro Rodriguez PhD Student in Large-Scale Machine Learning | CU Boulder Systems Oriented Data Scientist UC Berkeley AMPLab Alumni pedrorodriguez.io | 909-353-4423 github.com/EntilZha | LinkedIn On July 14, 2016 at 6:02:12 PM, Jacek Laskowski (ja...@japila.pl) wrote: Hi, Please re-consider your wish since it is going to move all the distributed dataset to the single machine of the driver and may lead to OOME. It's more pro to save your result to HDFS or S3 or any other distributed filesystem (that is accessible by the driver and executors). If you insist... Use collect() after select() and work with Array[T]. Pozdrawiam, Jacek Laskowski ---- https://medium.com/@jaceklaskowski/ Mastering Apache Spark http://bit.ly/mastering-apache-spark Follow me at https://twitter.com/jaceklaskowski On Fri, Jul 15, 2016 at 12:15 AM, vr.n. nachiappan <nachiappan_...@yahoo.com.invalid> wrote: > Hello, > > I am using data frames to join two cassandra tables. > > Currently when i invoke save on data frames as shown below it is saving the > join results on executor nodes. > > joineddataframe.select(<col1>, <col2> > ...).format("com.databricks.spark.csv").option("header", > "true").save(<path>) > > I would like to persist the results of the join on Spark Master/Driver node. > Is it possible to save the results on Spark Master/Driver and how to do it. > > I appreciate your help. > > Nachi > --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
