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Modern Big Data Processing with Hadoop

Modern Big Data Processing with Hadoop

The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools.This book will give you a complete understanding...
PySpark Recipes

PySpark Recipes

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved!PySpark Recipes covers Hadoop and its shortcomings...
Advanced Data Analytics Using Python

Advanced Data Analytics Using Python

Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You'...
Practical Enterprise Data Lake Insights

Practical Enterprise Data Lake Insights

Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues.When designing an enterprise data lake you often hit a roadblock when you must leave the comfort of the relational world and learn the nuances of handling non-relational data...
Beginning Apache Spark 2

Beginning Apache Spark 2

Develop applications for the big data landscape with Spark and Hadoop. This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it.Along the way, you'll discover res...
Getting Started with Kudu

Getting Started with Kudu

Fast data ingestion, serving, and analytics in the Hadoop ecosystem have forced developers and architects to choose solutions using the least common denominator - either fast analytics at the cost of slow data ingestion or fast data ingestion at the cost of slow analytics. There is an answer to this problem. With the Apache Kudu column-or...
Learning Apache Drill

Learning Apache Drill

Apache Drill enables interactive analysis of massively large datasets, allowing you to execute SQL queries against data in many different data sources - including Hadoop and MongoDB clusters, HBase, or even your local file system - and get results quickly. With this practical guide, analysts and data scientists focused on business or rese...
Big Data Architect's Handbook

Big Data Architect's Handbook

The big data architects are the “masters” of data, and hold high value in today's market. Handling big data, be it of good or bad quality, is not an easy task. The prime job for any big data architect is to build an end-to-end big data solution that integrates data from different sources and analyzes it to find useful, hidden insights...
Moving Hadoop to the Cloud

Moving Hadoop to the Cloud

Until recently, Hadoop deployments existed on hardware owned and run by organizations. Now, of course, you can acquire the computing resources and network connectivity to run Hadoop clusters in the cloud. But there's a lot more to deploying Hadoop to the public cloud than simply renting machines.This hands-on guide shows developers and sy...
Sams Teach Yourself Hadoop in 24 Hours

Sams Teach Yourself Hadoop in 24 Hours

Apache Hadoop is the technology at the heart of the Big Data revolution, and Hadoop skills are in enormous demand. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to deploy each key component of a Hadoop platform in your local environment or in the cloud, building a fully functional Had...
Deep Learning

Deep Learning

Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning - especially deep neural networks - make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but als...
Data Science with Java

Data Science with Java

Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz expl...
Practical Hadoop Migration

Practical Hadoop Migration

Re-architect relational applications to NoSQL, integrate relational database management systems with the Hadoop ecosystem, and transform and migrate relational data to and from Hadoop components. This book covers the best-practice design approaches to re-architecting your relational applications and transforming your relational data for u...
Professional Hadoop

Professional Hadoop

Professional Hadoop is the complete reference and resource for experienced developers looking to employ Apache Hadoop in real-world settings. Written by an expert team of certified Hadoop developers, committers, and Summit speakers, this book details every key aspect of Hadoop technology to enable optimal processing of large data sets. De...
Practical Hive

Practical Hive

Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stor...
Scalable Big Data Architecture

Scalable Big Data Architecture

This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance.Scalable Big Data Architecture covers real-world, concrete industr...
Kubernetes Microservices with Docker

Kubernetes Microservices with Docker

This book on Kubernetes, a container cluster manager, discusses all aspects of using Kubernetes in today's complex big data and enterprise applications, with Docker containers.Starting with installing Kubernetes on a single node, Kubernetes Microservices with Docker introduces Kubernetes with a simple Hello example and discusses using env...
Cassandra: The Definitive Guide, 2nd Edition

Cassandra: The Definitive Guide, 2nd Edition

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition - updated for Cassandra 3.0 - provides the technical details and pr...
MongoDB Cookbook, 2nd Edition

MongoDB Cookbook, 2nd Edition

MongoDB is a high-performance and feature-rich NoSQL database that forms the backbone of the systems that power many different organizations - it's easy to see why it's the most popular NoSQL database on the market. Packed with many features that have become essential for many different types of software professionals and incredibly easy ...
Field Guide to Hadoop

Field Guide to Hadoop

If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. You'll quick...

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