What is RDD in Apache Spark ? How to create an empty RDD ?

Nixon Data What is RDD in Apache Spark ? How to create an empty RDD ?

RDD (Resilient Distributed Dataset) is the fundamental data structure for distributed data processing in Apache Spark. An RDD is an immutable distributed collection of data that can be processed in parallel. RDDs are fault-tolerant and can be created from data stored in external storage systems, such as HDFS (Hadoop Distributed File System), or by transforming existing RDDs using operations called transformations.

There are several ways to create an empty RDD in Spark. Here are a few examples:

  1. Using the parallelize method: You can create an empty RDD by calling the parallelize method on an empty list. For example:

sc = SparkContext()
empty_rdd = sc.parallelize([])

2. Using the emptyRDD method: You can also create an empty RDD using the emptyRDD method of the SparkContext. For example:

sc = SparkContext()
empty_rdd = sc.emptyRDD()

  1. Using the range method: You can create an empty RDD by calling the range method with an end value of 0. For example:
sc = SparkContext()
empty_rdd = sc.range(0)