If you just want the ratio of positive to all values per key (if I'm
reading right) this works
val reduced= input.groupByKey().map(grp=>
grp._2.filter(v=>v>0).size.toFloat/grp._2.size)
reduced.foreach(println)
I don't think you need reduceByKey or combineByKey as you're not doing
anything where the values depend on each other -- you're just counting...
On Thu, Oct 9, 2014 at 11:47 AM, 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
>
