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You're reading from Scala and Spark for Big Data Analytics Explore the concepts of functional programming, data streaming, and machine learning

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781785280849

Length 796 pages

Edition 1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Big Data

Authors (2):

Sridhar Alla

Md. Rezaul Karim

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Table of Contents (19) Chapters

Preface

1. Introduction to Scala

2. Object-Oriented Scala FREE CHAPTER

3. Functional Programming Concepts

4. Collection APIs

5. Tackle Big Data – Spark Comes to the Party

6. Start Working with Spark – REPL and RDDs

7. Special RDD Operations

8. Introduce a Little Structure - Spark SQL

9. Stream Me Up, Scotty - Spark Streaming

10. Everything is Connected - GraphX

11. Learning Machine Learning - Spark MLlib and Spark ML

12. My Name is Bayes, Naive Bayes

13. Time to Put Some Order - Cluster Your Data with Spark MLlib

14. Text Analytics Using Spark ML

15. Spark Tuning

16. Time to Go to ClusterLand - Deploying Spark on a Cluster

17. Testing and Debugging Spark

18. PySpark and SparkR

Functional Programming Concepts

"Object-oriented programming makes code understandable by encapsulating moving parts. Functional programming makes code understandable by minimizing moving parts."

- Michael Feathers

Using Scala and Spark is a very good combination for learning big data analytics. However, along with the OOP paradigm, we also need to know-how why functional concepts are important for writing Spark applications that eventually analyze your data. As mentioned in the previous chapters, Scala supports two programming paradigms: the Object-Oriented Programming paradigm and the Functional programming concepts. In Chapter 2, Object-Oriented Scala, we explored the OOP paradigm in which we have seen how to represent real-world objects in blueprints (classes) and then instantiate them into objects having real memory representation.

In this chapter, we will focus...

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Authors (2)

Karim

Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.

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Sridhar Alla

Sridhar?Alla?is the co-founder and CTO of Blue Whale Consulting and is expert at helping companies (big and small) define their vision for systems and capabilities that will allow them to establish a strategic execution plan to deal with the ever-growing data collected to support analytics and product teams. He has very experienced at dealing with all aspects of data collection, security, governance, and processing as part of end-to-end big data analytics and machine learning initiatives (including predictive modeling, deep learning, and ML automation). Sridhar?is a published book author and an avid presenter at numerous conferences, including Strata, Hadoop World, and Spark Summit.? He also has several patents filed with the US PTO on large-scale computing and distributed systems.? He has over 18 years' experience writing code in Scala, Java, C, C++, Python, R, and Go, and has extensive hands-on knowledge of Spark, Flink, TensorFlow, Keras, Hadoop, Cassandra, HBase, MongoDB, Riak, Redis, Zeppelin, Mesos, Docker, Kafka, ElasticSearch, Solr, H2O, machine learning, text analytics, distributed computing, and high-performance computing. Sridhar lives with his wife and daughter in New Jersey and in his spare time loves blogging and coaching organizations on next-generation advancements in technology and their alignment with business goals.

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