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Programming Pig
Programming Pig

This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop. With Pig, you can batch-process data without having to create a full-fledged application—making it easy for you to experiment with new datasets.

Programming Pig introduces...

Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

Learning Apache Kafka, Second Edition
Learning Apache Kafka, Second Edition

Start from scratch and learn how to administer Apache Kafka effectively for messaging

About This Book

  • Quickly set up Apache Kafka clusters and start writing message producers and consumers
  • Write custom producers and consumers with message partition techniques
  • Integrate...
Learning Cassandra for Administrators
Learning Cassandra for Administrators

Understand the immense capabilities of Cassandra in managing large amounts of data and learn how to ensure that data is always available. This practical, hands-on guide takes you through every stage from installation to performance tuning.

Overview

  • Install and set up a multi datacenter Cassandra
  • ...
Kubernetes Microservices with Docker
Kubernetes Microservices with Docker

Start using Kubernetes in complex big data and enterprise applications, including Docker containers. Starting with installing Kubernetes on a single node, the book introduces Kubernetes with a simple Hello example and discusses using environment variables in Kubernetes. 
 

Next, Kubernetes Microservices with...
Practical Machine Learning
Practical Machine Learning

About This Book

  • Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark
  • Comprehensive practical solutions taking you into the future of machine learning
  • Go a step further and integrate your machine learning projects with...
MongoDB Cookbook
MongoDB Cookbook

Over 80 practical recipes to design, deploy, and administer MongoDB

About This Book

  • Gain a thorough understanding of some of the key features of MongoDB
  • Learn the techniques necessary to solve frequent MongoDB problems
  • Packed full of step-by-step recipes to help you with...
Hands-on DevOps: Explore the concept of continuous delivery and integrate it with data science concepts
Hands-on DevOps: Explore the concept of continuous delivery and integrate it with data science concepts

Transform yourself into a specialist in DevOps adoption for Big Data on cloud

Key Features

  • Learn the concepts of Bigdata and Devops and Implement them
  • Get Acquainted with DevOps Frameworks Methodologies and Tools
  • A practical approach to build and work efficiently with your...
PolyBase Revealed: Data Virtualization with SQL Server, Hadoop, Apache Spark, and Beyond
PolyBase Revealed: Data Virtualization with SQL Server, Hadoop, Apache Spark, and Beyond

Harness the power of PolyBase data virtualization software to make data from a variety of sources easily accessible through SQL queries while using the T-SQL skills you already know and have mastered.

PolyBase Revealed shows you how to use the PolyBase feature of SQL Server 2019 to...

Spring Data
Spring Data
The data access landscape over the past seven or so years has changed dramatically. Relational databases, the heart of storing and processing data in the enterprise for over 30 years, are no longer the only game in town. The past seven years have seen the birth —and in some cases the death—of many...
Data Just Right: Introduction to Large-Scale Data & Analytics (Addison-Wesley Data & Analytics Series)
Data Just Right: Introduction to Large-Scale Data & Analytics (Addison-Wesley Data & Analytics Series)

Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions

 

Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets;...

Fast Data Processing with Spark (Community Experience Distilled)
Fast Data Processing with Spark (Community Experience Distilled)

High-speed distributed computing made easy with Spark

Overview

  • Implement Spark's interactive shell to prototype distributed applications
  • Deploy Spark jobs to various clusters such as Mesos, EC2, Chef, YARN, EMR, and so on
  • Use Shark's SQL query-like syntax with...
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