rupeshtr78

package PlayGround

object ScalaCollectionsSortGroup {

  val evens = List(2,4,6)
  val odds = List(1,3,5)
  val a = "foo bar baz"
  val foo = "foo"
  val bar = "bar"
  val names = List("Al","Chistina","Kim")

rupeshtr78

package PlayGround

object ScalaCollectionsFoldReduceFlat {

  val evens = List(2,4,6)
  val odds = List(1,3,5)
  val a = "foo bar baz"
  val foo = "foo"
  val bar = "bar"
  val names = List("Al","Chistina","Kim")

rupeshtr78

import scala.collection.immutable.{HashMap, ListMap, ListSet, Queue}
import scala.collection.{LinearSeq, SortedSet, mutable}

val trav = Traversable(1, 2, 3)
val iter = Iterable("x", "y", "z")
val map = Map("x" -> 24, "y" -> 25, "z" -> 26)

val numArray = Array[Int](1, 2, 3, 4, 5)

val numList = List[Int](1, 2, 3, 4, 5)

rupeshtr78

Immutable
val numList = List[Int](1, 2, 3)
val numList2 = List[Int](10, 20, 30)
val numList3 = 1 :: 2:: 3:: Nil 		 //List(1, 2, 3)
val numlist3 = numList ++ numList2   	 //List(1, 2, 3, 10, 20, 30)
val x = 100 :: numList               		 //List(100, 1, 2, 3)
val x1 = numList :+ 100             		 //List(1, 2, 3, 100)
val x2 = 100 +: numList             		 //List(100, 1, 2, 3)
val x3 = numList :: numList2         	 //List(List(1, 2, 3), 10, 20, 30)
val y = numList +: numList2          	 //List(List(1, 2, 3), 10, 20, 30)

rupeshtr78

def sum(args:Int *): Int = {
 @tailrec
 def tailRecursionSum(argSeq: Seq[Int],result: Int): Int = {
   if (argSeq == Nil)    result
   else
     tailRecursionSum(argSeq.tail, result + argSeq.head)
 }
 tailRecursionSum(args,0)
}

rupeshtr78

val bullFlag = stockRecord.close match {
   case stockRecord.close if (previousState.bullFlag == 1 && stockRecord.close >= previousState.lowClose) => 1
   case stockRecord.close if ((stockRecord.close > highOfLowClose) && stockRecord.candle == 1) => 1
   case _ => 0
 }

rupeshtr78

//Big rule → Functions
//“Be liberal in what you accept from others” 
//“Be conservative in what you do” 

//type Function[-A, +B] = Function1[A, B] 
//the inputs of functions are contravariant and output are covariant.

//method arguments are in CONTRAVARIANT position -A (more general input argument)
//return types are in COVARIANT position +B  (more specific return type)

rupeshtr78

import java.io.{FileWriter, PrintWriter}
import scala.io.Source

val fileLines = Source.fromFile("/data/bullflag.txt").getLines()
for ((line, n) <- fileLines zipWithIndex) {
  val lineNumber = n+1
  val fileName = s"line-$lineNumber.txt"
  val filePath = s"/data/$fileName"
  val fileWriter = new PrintWriter(new FileWriter(filePath))
  fileWriter.write(line)

rupeshtr78

spark.readStream
  .format("kafka")
  .option("subscribe", "input")
  .load()
  .withWatermark(eventTime="timestampColumn", delayThreshold="10 seconds")
  .groupBy('value.cast("string") as 'key)
  .groupBy(window(col("time"), "1 day").as("time")) // tumbling window
  .groupBy(window(col("time"), "10 minutes", "5 minutes").as("time")) // sliding window
  .groupBy( 'keyCol, window("timestamp","10 mins"))
  .agg(count("*") as 'value)

rupeshtr78

package scalacollections

object ScalaCollectionsMap {

  import scala.collection.immutable.{HashMap, ListMap}

  val res: Seq[Char] = "hello world".toList.filter(_.isLetter).map(_.toUpper) //List(H, E, L, L, O, W, O, R, L, D)

  val resMap: Map[Char, Seq[Char]] = res.groupBy(x => x) //Map(E -> List(E), L -> List(L, L, L), H -> List(H), W -> List(W), R -> List(R), O -> List(O, O), D -> List(D))