Pattern matching - spark scala RDD

Question

I am new to Spark and Scala coming from R background.After a few transformations of RDD, I get a RDD of type

Description: RDD[(String, Int)]

Now I want to apply a Regular expression on the String RDD and extract substrings from the String and add just substring in a new coloumn.

Input Data :

BMW 1er Model,278
MINI Cooper Model,248

Output I am looking for :

   Input                  |  Brand   | Series      
BMW 1er Model,278,          BMW ,        1er        
MINI Cooper Model ,248      MINI ,      Cooper

where Brand and Series are newly calculated substrings from String RDD

What I have done so far.

I could achieve this for a String using regular expression, but I cani apply fro all lines.

 val brandRegEx = """^.*[Bb][Mm][Ww]+|.[Mm][Ii][Nn][Ii]+.*$""".r //to look for BMW or MINI

Then I can use

brandRegEx.findFirstIn("hello this mini is bmW testing")

But how can I use it for all the lines of RDD and to apply different regular expression to achieve the output as above.

I read about this code snippet, but not sure how to put it altogether.

val brandRegEx = """^.*[Bb][Mm][Ww]+|.[Mm][Ii][Nn][Ii]+.*$""".r

def getBrand(Col4: String) : String = Col4 match {
    case brandRegEx(str)  =>  
    case _ => ""
    return 'substring
}

Any help would be appreciated !

Thanks

Answer 1

To apply your regex to each item in the RDD, you should use the RDD map function, which transforms each row in the RDD using some function (in this case, a Partial Function in order to extract to two parts of the tuple which makes up each row):

import org.apache.spark.{SparkContext, SparkConf}

object Example extends App {

  val sc = new SparkContext(new SparkConf().setMaster("local").setAppName("Example"))

  val data = Seq(
    ("BMW 1er Model",278),
    ("MINI Cooper Model",248))

  val dataRDD = sc.parallelize(data)

  val processedRDD = dataRDD.map{
    case (inString, inInt) =>
      val brandRegEx = """^.*[Bb][Mm][Ww]+|.[Mm][Ii][Nn][Ii]+.*$""".r
      val brand = brandRegEx.findFirstIn(inString)
      //val seriesRegEx = ...
      //val series = seriesRegEx.findFirstIn(inString)
      val series = "foo"
      (inString, inInt, brand, series)
  }

  processedRDD.collect().foreach(println)
  sc.stop()
}

Note that I think you have some problems in your regular expression, and you also need a regular expression for finding the series. This code outputs:

(BMW 1er Model,278,BMW,foo)
(MINI Cooper Model,248,NOT FOUND,foo)

But if you correct your regexes for your needs, this is how you can apply them to each row.

Answer 2

hi I was just looking for aother question and got this question. The above problem can be done using normal transformations.

val a=sc.parallelize(collection)
a.map{case (x,y)=>(x.split (" ")(0)+" "+x.split(" ")(1))}.collect