Search Results: hadoop-2-quick-start-guide-learn-the-essentials-of-big-data-computing-in-the-apache-hadoop-2-ecosystem-addison-wesley-data-analytics

Hadoop 2 Quick-Start Guide

Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem

Author: Douglas Eadline

Publisher: Addison-Wesley Professional

ISBN: 0134049993

Category: Computers

Page: 250

View: 2408

Get Started Fast with Apache Hadoop® 2, YARN, and Today’s Hadoop Ecosystem With Hadoop 2.x and YARN, Hadoop moves beyond MapReduce to become practical for virtually any type of data processing. Hadoop 2.x and the Data Lake concept represent a radical shift away from conventional approaches to data usage and storage. Hadoop 2.x installations offer unmatched scalability and breakthrough extensibility that supports new and existing Big Data analytics processing methods and models. Hadoop® 2 Quick-Start Guide is the first easy, accessible guide to Apache Hadoop 2.x, YARN, and the modern Hadoop ecosystem. Building on his unsurpassed experience teaching Hadoop and Big Data, author Douglas Eadline covers all the basics you need to know to install and use Hadoop 2 on personal computers or servers, and to navigate the powerful technologies that complement it. Eadline concisely introduces and explains every key Hadoop 2 concept, tool, and service, illustrating each with a simple “beginning-to-end” example and identifying trustworthy, up-to-date resources for learning more. This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Douglas Eadline will bring you up to speed quickly, whether you’re a user, admin, devops specialist, programmer, architect, analyst, or data scientist. Coverage Includes Understanding what Hadoop 2 and YARN do, and how they improve on Hadoop 1 with MapReduce Understanding Hadoop-based Data Lakes versus RDBMS Data Warehouses Installing Hadoop 2 and core services on Linux machines, virtualized sandboxes, or clusters Exploring the Hadoop Distributed File System (HDFS) Understanding the essentials of MapReduce and YARN application programming Simplifying programming and data movement with Apache Pig, Hive, Sqoop, Flume, Oozie, and HBase Observing application progress, controlling jobs, and managing workflows Managing Hadoop efficiently with Apache Ambari–including recipes for HDFS to NFSv3 gateway, HDFS snapshots, and YARN configuration Learning basic Hadoop 2 troubleshooting, and installing Apache Hue and Apache Spark

Practical Data Science with Hadoop and Spark

Designing and Building Effective Analytics at Scale

Author: Ofer Mendelevitch,Casey Stella,Douglas Eadline

Publisher: Addison-Wesley Professional

ISBN: 0134029720

Category: Computers

Page: 256

View: 3494

The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language

Apache Hadoop YARN

Moving Beyond MapReduce and Batch Processing with Apache Hadoop 2

Author: Arun C. Murthy,Vinod Kumar Vavilapalli,Doug Eadline,Jeffrey Markham

Publisher: Pearson Education

ISBN: 0321934504

Category: Computers

Page: 304

View: 4437

"Apache Hadoop is helping drive the Big Data revolution. Now, its data processing has been completely overhauled: Apache Hadoop YARN provides resource management at data center scale and easier ways to create distributed applications that process petabytes of data. And now in Apache HadoopTM YARN, two Hadoop technical leaders show you how to develop new applications and adapt existing code to fully leverage these revolutionary advances." -- From the Amazon

Microsoft Big Data Solutions

Author: Adam Jorgensen,James Rowland-Jones,John Welch,Dan Clark,Christopher Price,Brian Mitchell

Publisher: John Wiley & Sons

ISBN: 1118729552

Category: Computers

Page: 408

View: 8064

Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all, it helps you integrate these new solutions with technologies you already know, such as SQL Server and Hadoop. Walks you through how to integrate Big Data solutions in your company using Microsoft's HDInsight Server, HortonWorks Data Platform for Windows, and open source tools Explores both on-premises and cloud-based solutions Shows how to store, manage, analyze, and share Big Data through the enterprise Covers topics such as Microsoft's approach to Big Data, installing and configuring HortonWorks Data Platform for Windows, integrating Big Data with SQL Server, visualizing data with Microsoft and HortonWorks BI tools, and more Helps you build and execute a Big Data plan Includes contributions from the Microsoft and HortonWorks Big Data product teams If you need a detailed roadmap for designing and implementing a fully deployed Big Data solution, you'll want Microsoft Big Data Solutions.

Big Data Processing With Hadoop

Author: Revathi, T.,Muneeswaran, K.,Blessa Binolin Pepsi, M.

Publisher: IGI Global

ISBN: 1522537910

Category: Computers

Page: 244

View: 5103

Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.

Hadoop in 24 Hours, Sams Teach Yourself

Author: Jeffrey Aven

Publisher: Sams Publishing

ISBN: 0134456726

Category: Computers

Page: 496

View: 4977

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 Hadoop cluster and using it with real programs and datasets. Each short, easy lesson builds on all that's come before, helping you master all of Hadoop's essentials, and extend it to meet your unique challenges. Apache Hadoop in 24 Hours, Sams Teach Yourself covers all this, and much more: Understanding Hadoop and the Hadoop Distributed File System (HDFS) Importing data into Hadoop, and process it there Mastering basic MapReduce Java programming, and using advanced MapReduce API concepts Making the most of Apache Pig and Apache Hive Implementing and administering YARN Taking advantage of the full Hadoop ecosystem Managing Hadoop clusters with Apache Ambari Working with the Hadoop User Environment (HUE) Scaling, securing, and troubleshooting Hadoop environments Integrating Hadoop into the enterprise Deploying Hadoop in the cloud Getting started with Apache Spark Step-by-step instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Hadoop to solve a wide spectrum of Big Data problems.

Hadoop Application Architectures

Author: Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira

Publisher: "O'Reilly Media, Inc."

ISBN: 1491900075

Category: Computers

Page: 400

View: 5785

Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing

The Routledge Handbook of Language and Intercultural Communication

Author: Jane Jackson

Publisher: Routledge

ISBN: 1136649522

Category: Language Arts & Disciplines

Page: 632

View: 9808

The Routledge Handbook of Language and Intercultural Communication constitutes a comprehensive introduction to the multidisciplinary field of intercultural communication, drawing on the expertise of leading scholars from diverse backgrounds. The Handbook is structured in five sections and covers historical perspectives, core issues and topics, and new debates in the field, with a particular focus on the language dimension. Among the key themes addressed are: the foundation of intercultural communication; core themes and issues; putting intercultural communication theory into practice; new debates and future directions. The Handbook includes an introduction and overview by the editor, which provides readers with an indication of the focus of each section and chapter. The Routledge Handbook of Language and Intercultural Communication is the ideal resource for advanced undergraduates and postgraduate students of applied linguistics, TESOL/TEFL and communication studies.

Professional Hadoop Solutions

Author: Boris Lublinsky,Kevin T. Smith,Alexey Yakubovich

Publisher: John Wiley & Sons

ISBN: 1118824180

Category: Computers

Page: 504

View: 6240

The go-to guidebook for deploying Big Data solutions with Hadoop Today's enterprise architects need to understand how the Hadoop frameworks and APIs fit together, and how they can be integrated to deliver real-world solutions. This book is a practical, detailed guide to building and implementing those solutions, with code-level instruction in the popular Wrox tradition. It covers storing data with HDFS and Hbase, processing data with MapReduce, and automating data processing with Oozie. Hadoop security, running Hadoop with Amazon Web Services, best practices, and automating Hadoop processes in real time are also covered in depth. With in-depth code examples in Java and XML and the latest on recent additions to the Hadoop ecosystem, this complete resource also covers the use of APIs, exposing their inner workings and allowing architects and developers to better leverage and customize them. The ultimate guide for developers, designers, and architects who need to build and deploy Hadoop applications Covers storing and processing data with various technologies, automating data processing, Hadoop security, and delivering real-time solutions Includes detailed, real-world examples and code-level guidelines Explains when, why, and how to use these tools effectively Written by a team of Hadoop experts in the programmer-to-programmer Wrox style Professional Hadoop Solutions is the reference enterprise architects and developers need to maximize the power of Hadoop.

Practical Hadoop Ecosystem

A Definitive Guide to Hadoop-Related Frameworks and Tools

Author: Deepak Vohra

Publisher: Apress

ISBN: 1484221990

Category: Computers

Page: 421

View: 4333

Learn how to use the Apache Hadoop projects, including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout, and Apache Solr. From setting up the environment to running sample applications each chapter in this book is a practical tutorial on using an Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects, MapReduce and HDFS, and none discusses the other Apache Hadoop ecosystem projects and how they all work together as a cohesive big data development platform. What You Will Learn: Set up the environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5 Run a MapReduce job Store data with Apache Hive, and Apache HBase Index data in HDFS with Apache Solr Develop a Kafka messaging system Stream Logs to HDFS with Apache Flume Transfer data from MySQL database to Hive, HDFS, and HBase with Sqoop Create a Hive table over Apache Solr Develop a Mahout User Recommender System Who This Book Is For: Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.

Expert Hadoop Administration

Managing, Tuning, and Securing Spark, YARN, and HDFS

Author: Sam R. Alapati

Publisher: Addison-Wesley Professional

ISBN: 0134703383

Category: Computers

Page: 848

View: 7327

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. The Comprehensive, Up-to-Date Apache Hadoop Administration Handbook and Reference “Sam Alapati has worked with production Hadoop clusters for six years. His unique depth of experience has enabled him to write the go-to resource for all administrators looking to spec, size, expand, and secure production Hadoop clusters of any size.” —Paul Dix, Series Editor In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experience with large-scale Hadoop administration, Alapati integrates action-oriented advice with carefully researched explanations of both problems and solutions. He covers an unmatched range of topics and offers an unparalleled collection of realistic examples. Alapati demystifies complex Hadoop environments, helping you understand exactly what happens behind the scenes when you administer your cluster. You’ll gain unprecedented insight as you walk through building clusters from scratch and configuring high availability, performance, security, encryption, and other key attributes. The high-value administration skills you learn here will be indispensable no matter what Hadoop distribution you use or what Hadoop applications you run. Understand Hadoop’s architecture from an administrator’s standpoint Create simple and fully distributed clusters Run MapReduce and Spark applications in a Hadoop cluster Manage and protect Hadoop data and high availability Work with HDFS commands, file permissions, and storage management Move data, and use YARN to allocate resources and schedule jobs Manage job workflows with Oozie and Hue Secure, monitor, log, and optimize Hadoop Benchmark and troubleshoot Hadoop

Cloud Computing for Science and Engineering

Author: Ian Foster,Dennis B. Gannon

Publisher: MIT Press

ISBN: 0262343991

Category: Computers

Page: 392

View: 5492

The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors.

Hadoop: The Definitive Guide

Author: Tom White

Publisher: "O'Reilly Media, Inc."

ISBN: 1449338771

Category: Computers

Page: 688

View: 1596

Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems

Professional Hadoop

Author: Benoy Antony,Konstantin Boudnik,Cheryl Adams,Branky Shao,Cazen Lee,Kai Sasaki

Publisher: John Wiley & Sons

ISBN: 111926720X

Category: Computers

Page: 216

View: 8291

The professional's one-stop guide to this open-source, Java-based big data framework 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. Designed expressly for the professional developer, this book skips over the basics of database development to get you acquainted with the framework's processes and capabilities right away. The discussion covers each key Hadoop component individually, culminating in a sample application that brings all of the pieces together to illustrate the cooperation and interplay that make Hadoop a major big data solution. Coverage includes everything from storage and security to computing and user experience, with expert guidance on integrating other software and more. Hadoop is quickly reaching significant market usage, and more and more developers are being called upon to develop big data solutions using the Hadoop framework. This book covers the process from beginning to end, providing a crash course for professionals needing to learn and apply Hadoop quickly. Configure storage, UE, and in-memory computing Integrate Hadoop with other programs including Kafka and Storm Master the fundamentals of Apache Big Top and Ignite Build robust data security with expert tips and advice Hadoop's popularity is largely due to its accessibility. Open-source and written in Java, the framework offers almost no barrier to entry for experienced database developers already familiar with the skills and requirements real-world programming entails. Professional Hadoop gives you the practical information and framework-specific skills you need quickly.

Hadoop in Action

Author: Chuck Lam,Mark Davis,Ajit Gaddam

Publisher: Manning Publications

ISBN: 9781617291227

Category:

Page: 525

View: 406

The massive datasets required for most modern businesses are too large to safely store and efficiently process on a single server. Hadoop is an open source data processing framework that provides a distributed file system that can manage data stored across clusters of servers and implements the MapReduce data processing model so that users can effectively query and utilize big data. The new Hadoop 2.0 is a stable, enterprise-ready platform supported by a rich ecosystem of tools and related technologies such as Pig, Hive, YARN, Spark, Tez, and many more. Hadoop in Action, Second Edition, provides a comprehensive introduction to Hadoop and shows how to write programs in the MapReduce style. It starts with a few easy examples and then moves quickly to show how Hadoop can be used in more complex data analysis tasks. It covers how YARN, new in Hadoop 2, simplifies and supercharges resource management to make streaming and real-time applications more feasible. Included are best practices and design patterns of MapReduce programming. The book expands on the first edition by enhancing coverage of important Hadoop 2 concepts and systems, and by providing new chapters on data management and data science that reinforce a practical understanding of Hadoop. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

PySpark Cookbook

Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python

Author: Tomasz Drabas,Denny Lee

Publisher: Packt Publishing Ltd

ISBN: 1788834259

Category: Computers

Page: 330

View: 303

Combine the power of Apache Spark and Python to build effective big data applications Key Features Perform effective data processing, machine learning, and analytics using PySpark Overcome challenges in developing and deploying Spark solutions using Python Explore recipes for efficiently combining Python and Apache Spark to process data Book Description Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. The PySpark Cookbook presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem. You’ll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You’ll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you’ll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You’ll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications. What you will learn Configure a local instance of PySpark in a virtual environment Install and configure Jupyter in local and multi-node environments Create DataFrames from JSON and a dictionary using pyspark.sql Explore regression and clustering models available in the ML module Use DataFrames to transform data used for modeling Connect to PubNub and perform aggregations on streams Who this book is for The PySpark Cookbook is for you if you are a Python developer looking for hands-on recipes for using the Apache Spark 2.x ecosystem in the best possible way. A thorough understanding of Python (and some familiarity with Spark) will help you get the best out of the book.

Cloudera Administration Handbook

Author: Rohit Menon

Publisher: Packt Publishing Ltd

ISBN: 1783558970

Category: Computers

Page: 254

View: 2466

An easy-to-follow Apache Hadoop administrator’s guide filled with practical screenshots and explanations for each step and configuration. This book is great for administrators interested in setting up and managing a large Hadoop cluster. If you are an administrator, or want to be an administrator, and you are ready to build and maintain a production-level cluster running CDH5, then this book is for you.

YARN Essentials

Author: Amol Fasale,Nirmal Kumar

Publisher: Packt Publishing Ltd

ISBN: 1784397725

Category: Computers

Page: 176

View: 6820

If you have a working knowledge of Hadoop 1.x but want to start afresh with YARN, this book is ideal for you. You will be able to install and administer a YARN cluster and also discover the configuration settings to fine-tune your cluster both in terms of performance and scalability. This book will help you develop, deploy, and run multiple applications/frameworks on the same shared YARN cluster.

Programming Hive

Author: Edward Capriolo,Dean Wampler,Jason Rutherglen

Publisher: "O'Reilly Media, Inc."

ISBN: 1449319335

Category: Computers

Page: 328

View: 2722

Describes the features and functions of Apache Hive, the data infrastructure for Hadoop.

Modern Big Data Processing with Hadoop

Expert techniques for architecting end-to-end big data solutions to get valuable insights

Author: V Naresh Kumar,Prashant Shindgikar

Publisher: Packt Publishing Ltd

ISBN: 1787128814

Category: Computers

Page: 394

View: 4045

A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description 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 of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.

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