On 09/10/2015 07:42 AM, Tathagata Das wrote: > Rewriting is necessary. You will have to convert RDD/DStream operations > to DataFrame operations. So get the RDDs in DStream, using > transform/foreachRDD, convert to DataFrames and then do DataFrame > operations.
Are there any plans for 1.6 or later to add support of tungsten to RDD/DStream directly or it is intended that users should switch to dataframe rather then operating on RDD/Dstream level. > > On Wed, Sep 9, 2015 at 9:23 PM, N B <nb.nos...@gmail.com > <mailto:nb.nos...@gmail.com>> wrote: > > Hello, > > How can we start taking advantage of the performance gains made > under Project Tungsten in Spark 1.5 for a Spark Streaming program? > > From what I understand, this is available by default for Dataframes. > But for a program written using Spark Streaming, would we see any > potential gains "out of the box" in 1.5 or will we have to rewrite > some portions of the application code to realize that benefit? > > Any insight/documentation links etc in this regard will be appreciated. > > Thanks > Nikunj > > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
