Spark SQL's query planner has always delayed building the RDD, so has never needed to eagerly calculate the range boundaries (since Spark 1.0).
On Mon, Apr 25, 2016 at 2:04 AM, Praveen Devarao <praveen...@in.ibm.com> wrote: > Thanks Reynold for the reason as to why sortBykey invokes a Job > > When you say "DataFrame/Dataset does not have this issue" is it right to > assume you are referring to Spark 2.0 or Spark 1.6 DF already has built-in > it? > > Thanking You > > --------------------------------------------------------------------------------- > Praveen Devarao > Spark Technology Centre > IBM India Software Labs > > --------------------------------------------------------------------------------- > "Courage doesn't always roar. Sometimes courage is the quiet voice at the > end of the day saying I will try again" > > > > From: Reynold Xin <r...@databricks.com> > To: Praveen Devarao/India/IBM@IBMIN > Cc: "dev@spark.apache.org" <dev@spark.apache.org>, user < > u...@spark.apache.org> > Date: 25/04/2016 11:26 am > Subject: Re: Do transformation functions on RDD invoke a Job > [sc.runJob]? > ------------------------------ > > > > Usually no - but sortByKey does because it needs the range boundary to be > built in order to have the RDD. It is a long standing problem that's > unfortunately very difficult to solve without breaking the RDD API. > > In DataFrame/Dataset we don't have this issue though. > > > On Sun, Apr 24, 2016 at 10:54 PM, Praveen Devarao <*praveen...@in.ibm.com* > <praveen...@in.ibm.com>> wrote: > Hi, > > I have a streaming program with the block as below [ref: > *https://github.com/agsachin/streamingBenchmark/blob/master/spark-benchmarks/src/main/scala/TwitterStreaming.scala* > <https://github.com/agsachin/streamingBenchmark/blob/master/spark-benchmarks/src/main/scala/TwitterStreaming.scala> > ] > > *1 val **lines *= *messages*.map(_._2) > *2 val **hashTags *= *lines*.flatMap(status => status.split(*" "* > ).filter(_.startsWith(*"#"*))) > > *3 val **topCounts60 *= *hashTags*.map((_, 1)).reduceByKey( _ + _ ) > *3a* .map { *case *(topic, count) => (count, topic) } > *3b* .transform(_.sortByKey(*false*)) > > *4a**topCounts60*.foreachRDD( rdd => { > *4b* *val *topList = rdd.take( 10 ) > }) > > This batch is triggering 2 jobs...one at line *3b**(sortByKey)* and > the other at *4b (rdd.take) *I agree that there is a Job triggered on > line 4b as take() is an action on RDD while as on line 3b sortByKey is just > a transformation function which as per docs is lazy evaluation...but I see > that this line uses a RangePartitioner and Rangepartitioner on > initialization invokes a method called *sketch() *that invokes *collect()* > triggering a Job. > > My question: Is it expected that sortByKey will invoke a Job...if > yes, why is sortByKey listed as a transformation and not action. Are there > any other functions like this that invoke a Job, though they are > transformations and not actions? > > I am on Spark 1.6 > > Thanking You > > --------------------------------------------------------------------------------- > Praveen Devarao > Spark Technology Centre > IBM India Software Labs > > --------------------------------------------------------------------------------- > "Courage doesn't always roar. Sometimes courage is the quiet voice at the > end of the day saying I will try again" > > > >
