PySpark : Explain map in Python or PySpark ? How it can be used.

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‘map’ in PySpark is a transformation operation that allows you to apply a function to each element in an RDD (Resilient Distributed Dataset), which is the basic data structure in PySpark. The function takes a single element as input and returns a single output.

The result of the map operation is a new RDD where each element is the result of applying the function to the corresponding element in the original RDD.

Suppose you have an RDD of integers, and you want to multiply each element by 2. You can use the map transformation as follows:

rdd = sc.parallelize([1, 2, 3, 4, 5])
result = x: x * 2)

The output of this code will be [2, 4, 6, 8, 10]. The map operation takes a lambda function (or any other function) that takes a single integer as input and returns its double. The collect action is used to retrieve the elements of the RDD back to the driver program as a list.

Spark important urls to refer

  1. Spark Examples
  2. PySpark Blogs
  3. Bigdata Blogs
  4. Spark Interview Questions
  5. Official Page
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