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Learn Hadoop in 24 Hours

Author: Alex Nordeen

Publisher: Guru99

Published: 2020-09-15

Total Pages: 103

ISBN-13:

Hadoop has changed the way large data sets are analyzed, stored, transferred, and processed. At such low cost, it provides benefits like supports partial failure, fault tolerance, consistency, scalability, flexible schema, and so on. It also supports cloud computing. More and more number of individuals are looking forward to mastering their Hadoop skills. While initiating with Hadoop, most users are unsure about how to proceed with Hadoop. They are not aware of what are the pre-requisite or data structure they should be familiar with. Or How to make the most efficient use of Hadoop and its ecosystem. To help them with all these queries and other issues this e-book is designed. The book gives insights into many of Hadoop libraries and packages that are not known to many Big data Analysts and Architects. The e-book also tells you about Hadoop MapReduce and HDFS. The example in the e-book is well chosen and demonstrates how to control Hadoop ecosystem through various shell commands. With this book, users will gain expertise in Hadoop technology and its related components. The book leverages you with the best Hadoop content with the lowest price range. After going through this book, you will also acquire knowledge on Hadoop Security required for Hadoop Certifications like CCAH and CCDH. It is a definite guide to Hadoop. Table Of Content Chapter 1: What Is Big Data 1. Examples Of 'Big Data' 2. Categories Of 'Big Data' 3. Characteristics Of 'Big Data' 4. Advantages Of Big Data Processing Chapter 2: Introduction to Hadoop 1. Components of Hadoop 2. Features Of 'Hadoop' 3. Network Topology In Hadoop Chapter 3: Hadoop Installation Chapter 4: HDFS 1. Read Operation 2. Write Operation 3. Access HDFS using JAVA API 4. Access HDFS Using COMMAND-LINE INTERFACE Chapter 5: Mapreduce 1. How MapReduce works 2. How MapReduce Organizes Work? Chapter 6: First Program 1. Understanding MapReducer Code 2. Explanation of SalesMapper Class 3. Explanation of SalesCountryReducer Class 4. Explanation of SalesCountryDriver Class Chapter 7: Counters & Joins In MapReduce 1. Two types of counters 2. MapReduce Join Chapter 8: MapReduce Hadoop Program To Join Data Chapter 9: Flume and Sqoop 1. What is SQOOP in Hadoop? 2. What is FLUME in Hadoop? 3. Some Important features of FLUME Chapter 10: Pig 1. Introduction to PIG 2. Create your First PIG Program 3. PART 1) Pig Installation 4. PART 2) Pig Demo Chapter 11: OOZIE 1. What is OOZIE? 2. How does OOZIE work? 3. Example Workflow Diagram 4. Oozie workflow application 5. Why use Oozie? 6. FEATURES OF OOZIE

Sams Teach Yourself Hadoop in 24 Hours

Author: Jeffrey Aven

Publisher: Sams Publishing

Published: 2017

Total Pages: 0

ISBN-13: 9780672338526

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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, students can learn all the skills and techniques they'll need to deploy each key component of a Hadoop platform in a 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 students master all of Hadoop's essentials, and extend it to meet real-world 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 students 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 avoid pitfalls. By the time they're finished, they'll be comfortable using Apache Hadoop to solve a wide spectrum of Big Data problems.

Hadoop in 24 Hours, Sams Teach Yourself

Author: Jeffrey Aven

Publisher: Sams Publishing

Published: 2017-04-07

Total Pages: 496

ISBN-13: 0134456726

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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.

Apache Spark in 24 Hours, Sams Teach Yourself

Author: Jeffrey Aven

Publisher: Sams Publishing

Published: 2016-08-31

Total Pages: 1352

ISBN-13: 0134445821

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Apache Spark is a fast, scalable, and flexible open source distributed processing engine for big data systems and is one of the most active open source big data projects to date. In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark’s amazing speed, scalability, simplicity, and versatility. This book’s straightforward, step-by-step approach shows you how to deploy, program, optimize, manage, integrate, and extend Spark–now, and for years to come. You’ll discover how to create powerful solutions encompassing cloud computing, real-time stream processing, machine learning, and more. Every lesson builds on what you’ve already learned, giving you a rock-solid foundation for real-world success. Whether you are a data analyst, data engineer, data scientist, or data steward, learning Spark will help you to advance your career or embark on a new career in the booming area of Big Data. Learn how to • Discover what Apache Spark does and how it fits into the Big Data landscape • Deploy and run Spark locally or in the cloud • Interact with Spark from the shell • Make the most of the Spark Cluster Architecture • Develop Spark applications with Scala and functional Python • Program with the Spark API, including transformations and actions • Apply practical data engineering/analysis approaches designed for Spark • Use Resilient Distributed Datasets (RDDs) for caching, persistence, and output • Optimize Spark solution performance • Use Spark with SQL (via Spark SQL) and with NoSQL (via Cassandra) • Leverage cutting-edge functional programming techniques • Extend Spark with streaming, R, and Sparkling Water • Start building Spark-based machine learning and graph-processing applications • Explore advanced messaging technologies, including Kafka • Preview and prepare for Spark’s next generation of innovations 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 Spark to solve a wide spectrum of Big Data problems.

Hadoop: The Definitive Guide

Author: Tom White

Publisher: "O'Reilly Media, Inc."

Published: 2012-05-10

Total Pages: 687

ISBN-13: 1449338771

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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

Hadoop in Action

Author: Chuck Lam

Publisher: Simon and Schuster

Published: 2010-11-30

Total Pages: 471

ISBN-13: 1638352100

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Hadoop in Action teaches readers how to use Hadoop and write MapReduce programs. The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. Hadoop in Action will lead the reader from obtaining a copy of Hadoop to setting it up in a cluster and writing data analytic programs. The book begins by making the basic idea of Hadoop and MapReduce easier to grasp by applying the default Hadoop installation to a few easy-to-follow tasks, such as analyzing changes in word frequency across a body of documents. The book continues through the basic concepts of MapReduce applications developed using Hadoop, including a close look at framework components, use of Hadoop for a variety of data analysis tasks, and numerous examples of Hadoop in action. Hadoop in Action will explain how to use Hadoop and present design patterns and practices of programming MapReduce. MapReduce is a complex idea both conceptually and in its implementation, and Hadoop users are challenged to learn all the knobs and levers for running Hadoop. This book takes you beyond the mechanics of running Hadoop, teaching you to write meaningful programs in a MapReduce framework. This book assumes the reader will have a basic familiarity with Java, as most code examples will be written in Java. Familiarity with basic statistical concepts (e.g. histogram, correlation) will help the reader appreciate the more advanced data processing examples. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Real-World Hadoop

Author: Ted Dunning

Publisher: "O'Reilly Media, Inc."

Published: 2015-03-24

Total Pages: 104

ISBN-13: 1491928921

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If you’re a business team leader, CIO, business analyst, or developer interested in how Apache Hadoop and Apache HBase-related technologies can address problems involving large-scale data in cost-effective ways, this book is for you. Using real-world stories and situations, authors Ted Dunning and Ellen Friedman show Hadoop newcomers and seasoned users alike how NoSQL databases and Hadoop can solve a variety of business and research issues. You’ll learn about early decisions and pre-planning that can make the process easier and more productive. If you’re already using these technologies, you’ll discover ways to gain the full range of benefits possible with Hadoop. While you don’t need a deep technical background to get started, this book does provide expert guidance to help managers, architects, and practitioners succeed with their Hadoop projects. Examine a day in the life of big data: India’s ambitious Aadhaar project Review tools in the Hadoop ecosystem such as Apache’s Spark, Storm, and Drill to learn how they can help you Pick up a collection of technical and strategic tips that have helped others succeed with Hadoop Learn from several prototypical Hadoop use cases, based on how organizations have actually applied the technology Explore real-world stories that reveal how MapR customers combine use cases when putting Hadoop and NoSQL to work, including in production

Sams Teach Yourself Node.js in 24 Hours

Author: George Ornbo

Publisher: Sams Publishing

Published: 2012-09-05

Total Pages: 1029

ISBN-13: 0132966263

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In just 24 sessions of one hour or less, Sams Teach Yourself Node.js in 24 Hours will help you master the Node.js platform and use it to build server-side applications with extraordinary speed and scalability. Using this text’s straightforward, step-by-step approach, you’ll move from basic installation, configuration, and programming all the way through real-time messaging between browser and server, testing and deployment. Every lesson and case-study application builds on what you’ve already learned, giving you a rock-solid foundation for real-world success! Step-by-step instructions carefully walk you through the most common Node.js development tasks. Quizzes and Exercises at the end of each chapter help you test your knowledge. By the Way notes present valuable additional information related to the discussion. Did You Know? tips offer advice or show you easier ways to perform tasks. Watch Out! cautions alert you to possible problems and give you advice on how to avoid them. Learn how to... · Create end-to-end applications entirely in JavaScript · Master essential Node.js concepts like callbacks and quickly create your first program · Create basic sites with the HTTP module and Express web framework · Manage data persistence with Node.js and MongoDB · Debug and test Node.js applications · Deploy Node.js applications to thirdparty services, such as Heroku and Nodester · Build powerful real-time solutions, from chat servers to Twitter clients · Create JSON APIs using JavaScript on the server · Use core components of the Node.js API, including processes, child processes, events, buffers, and streams · Create and publish a Node.js module

Moving Hadoop to the Cloud

Author: Bill Havanki

Publisher: "O'Reilly Media, Inc."

Published: 2017-07-14

Total Pages: 338

ISBN-13: 1491959584

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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 systems administrators familiar with Hadoop how to install, use, and manage cloud-born clusters efficiently. You’ll learn how to architect clusters that work with cloud-provider features—not just to avoid pitfalls, but also to take full advantage of these services. You’ll also compare the Amazon, Google, and Microsoft clouds, and learn how to set up clusters in each of them. Learn how Hadoop clusters run in the cloud, the problems they can help you solve, and their potential drawbacks Examine the common concepts of cloud providers, including compute capabilities, networking and security, and storage Build a functional Hadoop cluster on cloud infrastructure, and learn what the major providers require Explore use cases for high availability, relational data with Hive, and complex analytics with Spark Get patterns and practices for running cloud clusters, from designing for price and security to dealing with maintenance

Learning Spark

Author: Jules S. Damji

Publisher: O'Reilly Media

Published: 2020-07-16

Total Pages: 400

ISBN-13: 1492050016

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Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow