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Learning Apache Spark 2

You're reading from  Learning Apache Spark 2

Product type Book
Published in Mar 2017
Publisher Packt
ISBN-13 9781785885136
Pages 356 pages
Edition 1st Edition
Languages

Table of Contents (18) Chapters

Learning Apache Spark 2
Credits
About the Author
About the Reviewers
www.packtpub.com
Customer Feedback
Preface
Architecture and Installation Transformations and Actions with Spark RDDs ETL with Spark Spark SQL Spark Streaming Machine Learning with Spark GraphX Operating in Clustered Mode Building a Recommendation System Customer Churn Prediction Theres More with Spark

Passing functions to Spark (Python)


Python provides a simple way to pass functions to Spark. The Spark programming guide available at spark.apache.org suggests there are three recommended ways to do this:

  • Lambda expressions is the ideal way for short functions that can be written inside a single expression
  • Local defs inside the function calling into Spark for longer code
  • Top-level functions in a module

While we have already looked at the lambda functions in some of the previous examples, let's look at local definitions of the functions. We can encapsulate our business logic which is splitting of words, and counting into two separate functions as shown below.

def splitter(lineOfText): 
     words = lineOfText.split(" ") 
     return len(words) 
def aggregate(numWordsLine1, numWordsLineNext): 
     totalWords = numWordsLine1 + numWordsLineNext 
     return totalWords 

Let's see the working code example:

Figure 2.15: Code example of Python word count (local definition...

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