Big Data Engineering Books Pdf

Big Data Engineering Books Pdf is a large volume of data that cannot be processed by traditional database management tools. In recent years, the amount of data has been increasing rapidly due to the rise of Internet and mobile devices. The ability to collect, store and analyze big data has led to many new applications that can help us with business intelligence or scientific research.

Big Data Engineering Books Pdf

Introduction

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Hadoop: The Definitive Guide PDF Download for free: Book Description: Get ready to unlock the power of your data.

Hadoop: The Definitive Guide

This book is about Apache Hadoop, the software framework for writing distributed applications that are designed to run on large clusters of commodity hardware. This book will help you use Hadoop to solve many common problems faced by today’s data analysts and information workers.

Hadoop in Practice, 2nd Edition PDF Download for free: Book Description: Summary Use more than 100 Hadoop case studies from Yahoo!, Google, and eBay to solve problems with Hadoop.

Get your copy of the best-selling Big Data book on Big Data engineering.

Hadoop in Practice is a deep dive into the practical implementation of big data systems using Apache Hadoop. Written by members of the Apache HBase team at Yahoo! Labs and Hortonworks, this book provides a broad overview of many common use cases for HBase and other tools in an easy-to-read format that covers everything from basic setup and configuration through monitoring and troubleshooting.

HBase in Action PDF Download for free: Book Description: High-performance random access to your big data is now possible with the use of HBase.

HBase is a distributed database that offers high-performance random access to your big data. You can use HBase with Apache Hadoop, but it also works independently of Hadoop. It provides fast scans, column-oriented storage, and high availability.

HBase is a NoSQL database because it’s schema-less, which means you don’t need to define the structure for the data you store before storing it. However, you can still perform queries based on row keys or column family names if necessary.

Learning Spark PDF Download for free: Book Description: Summary Get ready to unlock the power of your data.

If you want to learn how to build big-data applications using Spark, this is the book for you. The book begins with Spark’s core concepts and APIs, continues through its integration with other tools in the big data ecosystem, and covers how to use it for computations that process large volumes of data in parallel. You will also learn about Spark Machine Learning (ML) libraries and frameworks for deep learning such as TensorFlow.

This book starts by introducing the basics of programming with Python including variables and loops before moving on to complex data structures like lists or tuples along with advanced concepts such as recursion through examples which are easy enough so that anyone can follow along but still interesting enough so as not to get bored! The second half focuses more on algorithms used regularly by programmers today – sorting algorithms which help organize information stored on computers faster than usual(bubble sort), searching methods which allow us access certain pieces of information quickly without having read every single piece beforehand(binary search algorithm), etc…

Machine Learning With Spark PDF Download for free: Book Description: Summary Gain wisdom from key machine learning concepts and spark solutions through real-world examples.

Machine Learning with Spark is a well-written book that covers several important machine learning concepts and provides useful examples. It starts with the basics of machine learning and then moves on to advanced topics such as graph mining, time series data analysis using MLlib, recommendation systems using Apache Mahout, image recognition using Deeplearning4j and much more.

This book comes with an introduction section where you will learn about the fundamentals of Machine Learning (ML), artificial intelligence (AI) and Spark. Then it covers different types of datasets available for ML purposes such as text data sets like tweets or news articles; image datasets like MNIST digit recognition; video dataset like Youtube frames etc.; social network datasets such as Facebook friends graph etc.; graph data sets like Twitter hashtaggraph etc.; Time Series Data Sets like stock price series or weather forecast timestamped value pairs or sensor readings from IoT devices etc. You will also see how these datasets can be manipulated into various forms before being used by ML algorithms in order to extract useful information or make predictions from them.

These books will help you learn programming with big data.

Hadoop: The Definitive Guide by Tom White (O’Reilly Media)

HBase in Action by Deepak Vohra & Mike Cafarella (Manning Publications)

Learning Spark by Patrick Wendell & Andy Konwinski (O’Reilly Media)

Machine Learning with Spark by Matthew Zeiler & Rob Fletcher (Manning Publications)

Conclusion

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Big Data Engineering Books Pdf