You have a typo in your code at "var acc:", and the map from opPart1 to opPart2 looks like a no-op, but those aren't the problem I think. It sounds like you intend the first element of each pair to be a count of nonzero values, but you initialize the first element of the pair to v, not 1, in v => (v,1). Try v => (1,1)
On Thu, Oct 9, 2014 at 4:47 PM, HARIPRIYA AYYALASOMAYAJULA <aharipriy...@gmail.com> wrote: > > I am a beginner to Spark and finding it difficult to implement a very simple > reduce operation. I read that is ideal to use combineByKey for complex > reduce operations. > > My input: > > val input = sc.parallelize(List(("LAX",6), ("LAX",8), ("LAX",7), ("SFO",0), > ("SFO",1), ("SFO",9),("PHX",65),("PHX",88),("KX",7),("KX",6),("KX",1), > ("KX",9), > ("HOU",56),("HOU",5),("HOU",59),("HOU",0),("MA",563),("MA",545),("MA",5),("MA",0),("MA",0))) > > > val opPart1 = input.combineByKey( > (v) => (v, 1), > (var acc: (Int, Int), v) => ( if(v > 0) acc._1 + 1 else acc._1, acc._2 + > 1), > (acc1: (Int, Int), acc2: (Int, Int)) => (acc1._1 + acc2._1, acc1._2 + > acc2._2) > ) > > val opPart2 = opPart1.map{ case (key, value) => (key, > (value._1,value._2)) } > > opPart2.collectAsMap().map(println(_)) > > If the value is greater than 0, the first accumulator should be incremented > by 1, else it remains the same. The second accumulator is a simple counter > for each value. I am getting an incorrect output (garbage values )for the > first accumulator. Please help. > > The equivalent reduce operation in Hadoop MapReduce is : > > public static class PercentageCalcReducer extends > Reducer<Text,IntWritable,Text,FloatWritable> > > { > > private FloatWritable pdelay = new FloatWritable(); > > > public void reduce(Text key, Iterable<IntWritable> values,Context > context)throws IOException,InterruptedException > > { > > int acc2=0; > > float frac_delay, percentage_delay; > > int acc1=0; > > for(IntWritable val : values) > > { > > if(val.get() > 0) > > { > > acc1++; > > } > > acc2++; > > } > > > > frac_delay = (float)acc1/acc2; > > percentage_delay = frac_delay * 100 ; > > pdelay.set(percentage_delay); > > context.write(key,pdelay); > > } > > } > > > Please help. Thank you for your time. > > -- > > Regards, > > Haripriya Ayyalasomayajula > contact : 650-796-7112 --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org