Confused by SparkContext import statements - apache-spark

Question

I am trying to learn Apache Spark and cannot wrap my head wround this:
import spark.SparkContext
import SparkContext._
Why do we need the second line that almost looks like the first? And what does the '._' man after SparkContext?

Answer 1

You do not need to execute the 2nd line import SparkContext._ . Given the old approach of, say, Spark 1.6.x for a self-contained Spark App, the following from https://github.com/mk6502/spark-1.6-scala-boilerplate/blob/master/src/main/scala/HelloSpark.scala clearly and briefly demonstrates this:
import org.apache.spark.{SparkContext, SparkConf}
object HelloSpark {
def main(args: Array[String]) {
val sc = new SparkContext(new SparkConf().setAppName("hello spark").setMaster("local"))
val rdd = sc.parallelize(Array(1, 2, 3, 4, 5))
println("count: ")
println(rdd.count())
sc.stop()
}
}
In notebooks the settings and configs and entry points are automatic.
As stated in my comment, move on to Spark 2.x, 3.x and look at SparkSession via https://data-flair.training/forums/topic/sparksession-vs-sparkcontext-in-apache-spark/
In the 1.6 Spark Guide on Self-Contained Applications we see the 2nd line indeed, but no reference to underlying classes explicitly. E.g.
/* SimpleApp.scala */
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
object SimpleApp {
def main(args: Array[String]) {
val logFile = "YOUR_SPARK_HOME/README.md" // Should be some file on your system
val conf = new SparkConf().setAppName("Simple Application")
val sc = new SparkContext(conf)
val logData = sc.textFile(logFile, 2).cache()
val numAs = logData.filter(line => line.contains("a")).count()
val numBs = logData.filter(line => line.contains("b")).count()
println("Lines with a: %s, Lines with b: %s".format(numAs, numBs))
}
}