user@spark.apache.org

Hi Daniel, I will try this one out and let you know. Thank you.


On Wed, Oct 5, 2016 at 9:50 AM, Daniel Siegmann <dsiegmann@securityscorecard.io> wrote:
I think it's fine to read animal types locally because there are only 70 of them. It's just that you want to execute the Spark actions in parallel. The easiest way to do that is to have only a single action.

Instead of grabbing the result right away, I would just add a column for the animal type and union the datasets for the animal types. Something like this (not sure if the syntax is correct):

val animalCounts: DataFrame = animalTypes.map { anmtyp =>
    sqlContext.sql("select lit("+anmtyp+") as animal_type, count(distinct("+anmtyp+")) from TEST1 ")
}.reduce(_.union(_))

animalCounts.foreach( /* print the output */ )

On Wed, Oct 5, 2016 at 12:42 AM, Daniel <daniel.tizon@gmail.com> wrote:

First of all, if you want to read a txt file in Spark, you should use sc.textFile, because you are using "Source.fromFile", so you are reading it with Scala standard api, so it will be read sequentially.

Furthermore you are going to need create a schema if you want to use dataframes.


El 5/10/2016 1:53, "Ajay Chander" <itschevva@gmail.com> escribió:
Right now, I am doing it like below,

import scala.io.Source

val animalsFile = "/home/ajay/dataset/animal_types.txt"
val animalTypes = Source.fromFile(animalsFile).getLines.toArray

for ( anmtyp <- animalTypes ) {
      val distinctAnmTypCount = sqlContext.sql("select count(distinct("+anmtyp+")) from TEST1 ")
      println("Calculating Metrics for Animal Type: "+anmtyp)
      if( distinctAnmTypCount.head().getAs[Long](0) <= 10 ){
        println("Animal Type: "+anmtyp+" has <= 10 distinct values")
      } else {
        println("Animal Type: "+anmtyp+" has > 10 distinct values")
      }
    }

But the problem is it is running sequentially.

Any inputs are appreciated. Thank you.


Regards,
Ajay


On Tue, Oct 4, 2016 at 7:44 PM, Ajay Chander <itschevva@gmail.com> wrote:
Hi Everyone,

I have a use-case where I have two Dataframes like below,

1) First Dataframe(DF1) contains,

    ANIMALS    
Mammals
Birds
Fish
Reptiles
Amphibians

2) Second Dataframe(DF2) contains,

    ID, Mammals, Birds, Fish, Reptiles, Amphibians    
1,      Dogs,      Eagle,      Goldfish,      NULL,      Frog
2,      Cats,      Peacock,      Guppy,     Turtle,      Salamander
3,      Dolphins,      Eagle,      Zander,      NULL,      Frog
4,      Whales,      Parrot,      Guppy,      Snake,      Frog
5,      Horses,      Owl,      Guppy,      Snake,      Frog
6,      Dolphins,      Kingfisher,      Zander,      Turtle,      Frog
7,      Dogs,      Sparrow,      Goldfish,      NULL,      Salamander

Now I want to take each row from DF1 and find out its distinct count in DF2. Example, pick Mammals from DF1 then find out count(distinct(Mammals)) from DF2 i.e. 5

DF1 has 70 distinct rows/Animal types
DF2 has some million rows

Whats the best way to achieve this efficiently using parallelism ?

Any inputs are helpful. Thank you.

Regards,
Ajay