In this Chapter, instead of using Spark shell, we will build two standalone Spark applications using Scala API: one for model preparation and the second for model deployment. In the case of Spark, the Spark application is a normal Scala application with a main method that serves as an entry point for execution. For example, here is a skeleton of application for model training:
object Chapter8 extends App {
val spark = SparkSession.builder()
.master("local[*]")
.appName("Chapter8")
.getOrCreate()
val sc = spark.sparkContext
sc.setLogLevel("WARN")
script(spark, sc, spark.sqlContext)
def script(spark: SparkSession, sc: SparkContext, sqlContext: SQLContext): Unit = {
// ...code of application } }
Moreover, we will try to extract parts, which can be shared between both applications, into a library. This will...