The examples are basic and only for newbies in Scala and Spark.

There are a lot of developers who love Spark and want to have custom APIs for Spark. For example, a Spark integration with another software or simple customized APIs, which can be modulized and used frequently as a thrid-party library. For those guys, here are some custom API examples in this library. This can be imported by a jar as a third-party with Spark.

• customPipe(..) equivalent to pipe(..) in RDD

  import com.company.spark.custom._
  
  val rdd = sc.parallelize(Seq(1, 2, 3))
  rdd.customPipe("cat").collect()

• customCount() equivalent to count() in DataFrame

  import com.company.spark.custom._
  
  val data = Seq(1, 2, 3, 4, 5)
  val rdd = sc.parallelize(numList)
  val df = numRDD.toDF
  df.customCount()

• customTextFile(..) equivalent to textFile(..) in SparkContext

  import com.company.spark.custom._
  
  val path = "path-to-file"
  sc.customTextFile(path)

• customLoadJsonRDD(..) equivalent to jsonRDD(..) in SQLContext

  import com.company.spark.custom._
  
  val jsonRDD = sparkContext.parallelize(
    """{"a": 1}""" ::
    """{"a": 2}""" :: Nil)
  sqlContext.customLoadJsonRDD(jsonRDD)

• For test in your local, just run below:

  ./dev/run-tests
  

This library is built with SBT, which is automatically downloaded by the included shell script. To build a JAR file simply run sbt/sbt package from the project root. The build configuration includes support for both Scala 2.10 and 2.11.