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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

Why FP and Scala for learning Spark?

In this section, we will discuss why we will learn Spark to solve our data analytics problem. We will then discuss why the functional programming concepts in Scala are particularly important to make data analysis easier for the data scientists. We will also discuss the Spark programming model and its ecosystem to make them clearer.

Why Spark?

Spark is a lightning fast cluster computing framework and is mainly designed for fast computations. Spark is based on the Hadoop MapReduce model and uses MapReduce in more forms and types of computation, such as interactive queries and stream processing. One of the main features of Spark is in-memory processing, which helps increase the performance...

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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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