Apache Spark create rdd from an array java | convert an array in to RDD

• RDD is the spark's core abstraction.
• Full form of RDD is resilient distributed dataset.
• Each RDD will split into multiple partitions which may be computed in different machines of cluster
• We can create Apache spark RDD in two ways
  
  1. Parallelizing a collection
  2. Loading an external dataset.
   
• So Creating RDD from an array comes in under Parallelizing a collection.
• Let us see Apache spark an example program to convert an array into RDD.

Program #1: Write a Apache spark java example program to create simple RDD using parallelize method of JavaSparkContext. convert an array in to RDD

1.  package com.instanceofjava.sparkInterview;
2.  
3. import java.util.Arrays;
4.  
5. import org.apache.spark.SparkConf;
6. import org.apache.spark.api.java.JavaRDD;
7. import org.apache.spark.api.java.JavaSparkContext;
8.  
9. /**
10.  *  Apache spark examples:RDD in spark example program  
11. *  converting an array to RDD
12.  * @author www.instanceofjava.com
13.  */
14. public class SparkTest {
15.     
16.     public static void main(String[] args) {
17.         
18.         SparkConf conf = new
19. SparkConf().setMaster("local[2]").setAppName("InstanceofjavaAPP");
20.         JavaSparkContext sc = new JavaSparkContext(conf);
21.         
22.         String[] arrayStr={"convert array to rdd","convert array into rdd"};
23.         
24.         JavaRDD<String> strRdd=sc.parallelize(Arrays.asList(arrayStr));
25.         System.out.println("apache spark rdd created: "+strRdd);
26.         
27.         /**
28.          * Return the first element in this RDD.
29.          */
30.         System.out.println(strRdd.first());
31.         
32.     }
33.  
34. }
35. }

Output:

1. apache spark rdd created: ParallelCollectionRDD[0] at parallelize at SparkTest.java:24
2. convert array to rdd