Any help on this warmly appreciated. 

    On Tuesday, 6 September 2016, 21:31, Ashok Kumar 
<ashok34...@yahoo.com.INVALID> wrote:
 

 Hello Gurus,
I am creating some figures and feed them into Kafka and then spark streaming.
It works OK but I have the following issue.
For now as a test I sent 5 prices in each batch interval. In the loop code this 
is what is hapening
      dstream.foreachRDD { rdd =>     val x= rdd.count
     i += 1     println(s"====> rdd loop i is ${i}, number of lines is  ${x} 
<======")     if (x > 0) {       println(s"================processing ${x} 
records=================")       var words1 = 
rdd.map(_._2).map(_.split(',').view(0)).map(_.toInt).collect.apply(0)        
println (words1)       var words2 = 
rdd.map(_._2).map(_.split(',').view(1)).map(_.toString).collect.apply(0)        
println (words2)       var price = 
rdd.map(_._2).map(_.split(',').view(2)).map(_.toFloat).collect.apply(0)        
println (price)        rdd.collect.foreach(println)       }     }

My tuple looks like this
// (null, "ID       TIMESTAMP                           PRICE")// (null, 
"40,20160426-080924,                  67.55738301621814598514")
And this the sample output from the run
================processing 5 
records=================320160906-21250980.224686(null,3,20160906-212509,80.22468448052631637099)(null,1,20160906-212509,60.40695324215582386153)(null,4,20160906-212509,61.95159400693415572125)(null,2,20160906-212509,93.05912099305473237788)(null,5,20160906-212509,81.08637370113427387121)
Now it does process the first values 3, 20160906-212509, 80.224686  for record 
(null,3,20160906-212509,80.22468448052631637099) but ignores the rest. of 4 
records. How can I make it go through all records here? I want the third column 
from all records!
Greetings




   

Reply via email to