How spark handles object

Question

To test the Serialization exception in spark I wrote a task in 2 ways.
First way:

package examples
import org.apache.spark.SparkConf
import org.apache.         


        

Answer 1

When you run code in an RDD closure (map, filter, etc...), everything necessary to execute that code will be packaged up, serialized, and sent to the executors to be run. Any objects that are referenced (or whose fields are referenced) will be serialized in this task, and this is where you'll sometimes get a NotSerializableException.

Your use case is a little more complicated, though, and involves the scala compiler. Typically, calling a function on a scala object is the equivalent of calling a java static method. That object never really exists -- it's basically like writing the code inline. However, if you assign an object to a variable, then you're actually creating a reference to that object in memory, and the object behaves more like a class, and can have serialization issues.

scala> object A { 
  def foo() { 
    println("bar baz")
  }
}
defined module A

scala> A.foo()  // static method
bar baz

scala> val a = A  // now we're actually assigning a memory location
a: A.type = A$@7e0babb1

scala> a.foo()  // dereferences a before calling foo
bar baz