Learn Hadoop in 24 Hours

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Publisher : Guru99
ISBN 13 :
Total Pages : 103 pages
Book Rating : 4./5 ( download)

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Book Synopsis Learn Hadoop in 24 Hours by : Alex Nordeen

Download or read book Learn Hadoop in 24 Hours written by Alex Nordeen and published by Guru99. This book was released on 2020-09-15 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : Sams Publishing
ISBN 13 : 9780672338526
Total Pages : 0 pages
Book Rating : 4.3/5 (385 download)

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Book Synopsis Sams Teach Yourself Hadoop in 24 Hours by : Jeffrey Aven

Download or read book Sams Teach Yourself Hadoop in 24 Hours written by Jeffrey Aven and published by Sams Publishing. This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Author :
Publisher : Sams Publishing
ISBN 13 : 0134456726
Total Pages : 851 pages
Book Rating : 4.1/5 (344 download)

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Book Synopsis Hadoop in 24 Hours, Sams Teach Yourself by : Jeffrey Aven

Download or read book Hadoop in 24 Hours, Sams Teach Yourself written by Jeffrey Aven and published by Sams Publishing. This book was released on 2017-04-07 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Author :
Publisher : Sams Publishing
ISBN 13 : 0134445821
Total Pages : 1353 pages
Book Rating : 4.1/5 (344 download)

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Book Synopsis Apache Spark in 24 Hours, Sams Teach Yourself by : Jeffrey Aven

Download or read book Apache Spark in 24 Hours, Sams Teach Yourself written by Jeffrey Aven and published by Sams Publishing. This book was released on 2016-08-31 with total page 1353 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 in Action

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Publisher : Simon and Schuster
ISBN 13 : 1638352100
Total Pages : 471 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Hadoop in Action by : Chuck Lam

Download or read book Hadoop in Action written by Chuck Lam and published by Simon and Schuster. This book was released on 2010-11-30 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Hadoop: The Definitive Guide

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449338771
Total Pages : 687 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Hadoop: The Definitive Guide by : Tom White

Download or read book Hadoop: The Definitive Guide written by Tom White and published by "O'Reilly Media, Inc.". This book was released on 2012-05-10 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Sams Teach Yourself ADO .NET in 24 Hours

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Publisher : Sams Publishing
ISBN 13 : 9780672323836
Total Pages : 414 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Sams Teach Yourself ADO .NET in 24 Hours by : Jason Lefebvre

Download or read book Sams Teach Yourself ADO .NET in 24 Hours written by Jason Lefebvre and published by Sams Publishing. This book was released on 2002 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 24 easy lessons, learn the new object model to retrieve and work with data from multiple sources.

Learning Spark

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Publisher : O'Reilly Media
ISBN 13 : 1492050016
Total Pages : 400 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Learning Spark by : Jules S. Damji

Download or read book Learning Spark written by Jules S. Damji and published by O'Reilly Media. This book was released on 2020-07-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Sams Teach Yourself Node.js in 24 Hours

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Publisher : Sams Publishing
ISBN 13 : 0132966263
Total Pages : 1029 pages
Book Rating : 4.1/5 (329 download)

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Book Synopsis Sams Teach Yourself Node.js in 24 Hours by : George Ornbo

Download or read book Sams Teach Yourself Node.js in 24 Hours written by George Ornbo and published by Sams Publishing. This book was released on 2012-09-05 with total page 1029 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Frank Kane's Taming Big Data with Apache Spark and Python

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1787288307
Total Pages : 289 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Frank Kane's Taming Big Data with Apache Spark and Python by : Frank Kane

Download or read book Frank Kane's Taming Big Data with Apache Spark and Python written by Frank Kane and published by Packt Publishing Ltd. This book was released on 2017-06-30 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn Find out how you can identify Big Data problems as Spark problems Install and run Apache Spark on your computer or on a cluster Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets Implement machine learning on Spark using the MLlib library Process continuous streams of data in real time using the Spark streaming module Perform complex network analysis using Spark's GraphX library Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace.

Big Data

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Publisher : Simon and Schuster
ISBN 13 : 1638351104
Total Pages : 481 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Big Data by : James Warren

Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself

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Author :
Publisher : Sams Publishing
ISBN 13 : 013403533X
Total Pages : 1044 pages
Book Rating : 4.1/5 (34 download)

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Book Synopsis Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself by : Manpreet Singh

Download or read book Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself written by Manpreet Singh and published by Sams Publishing. This book was released on 2015-11-12 with total page 1044 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sams Teach Yourself Big Data Analytics with Microsoft HDInsight in 24 Hours In just 24 lessons of one hour or less, Sams Teach Yourself Big Data Analytics with Microsoft HDInsight in 24 Hours helps you leverage Hadoop’s power on a flexible, scalable cloud platform using Microsoft’s newest business intelligence, visualization, and productivity tools. This book’s straightforward, step-by-step approach shows you how to provision, configure, monitor, and troubleshoot HDInsight and use Hadoop cloud services to solve real analytics problems. You’ll gain more of Hadoop’s benefits, with less complexity–even if you’re completely new to Big Data analytics. Every lesson builds on what you’ve already learned, giving you a rock-solid foundation for real-world success. Practical, hands-on examples show you how to apply what you learn Quizzes and exercises help you test your knowledge and stretch your skills Notes and tips point out shortcuts and solutions Learn how to... · Master core Big Data and NoSQL concepts, value propositions, and use cases · Work with key Hadoop features, such as HDFS2 and YARN · Quickly install, configure, and monitor Hadoop (HDInsight) clusters in the cloud · Automate provisioning, customize clusters, install additional Hadoop projects, and administer clusters · Integrate, analyze, and report with Microsoft BI and Power BI · Automate workflows for data transformation, integration, and other tasks · Use Apache HBase on HDInsight · Use Sqoop or SSIS to move data to or from HDInsight · Perform R-based statistical computing on HDInsight datasets · Accelerate analytics with Apache Spark · Run real-time analytics on high-velocity data streams · Write MapReduce, Hive, and Pig programs Register your book at informit.com/register for convenient access to downloads, updates, and corrections as they become available.

Learn Hive in 24 Hours

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Author :
Publisher : Guru99
ISBN 13 :
Total Pages : 64 pages
Book Rating : 4./5 ( download)

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Book Synopsis Learn Hive in 24 Hours by : Alex Nordeen

Download or read book Learn Hive in 24 Hours written by Alex Nordeen and published by Guru99. This book was released on 2020-09-15 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apache Hive is the new member in database family that works within the Hadoop ecosystem. It provides all great features like data summarization, ad-hoc query, and analysis of large datasets. If you are not a good programmer, then this edition will teach you how to use hive queries without writing complex codes. Most users face the problem of not getting a dedicated course on Hive. The goal of this e-book is to cater everything about Hive and only Hive with minimum jargons. The notes, lessons and hands-on examples in this small e-book are simplified and tactfully presented to solve all your Hive queries. Instead of writing long code for MapReduce or Java, the e-book shows tips on writing the same program with a minimum code snippet. Beginners as well as peers will thoroughly enjoy this book. They will discover and learn more hive patterns for data processing and data integrations. Unlike other e-book, where they skip basic detail thinking users having prior subject knowledge. This edition has given complete attention to each and every small aspect of the hive like “how to set up and configure Hive in your environment”. This e-book is also helpful for those who just want to explore Hive and don’t want to spend big bucks for short courses. You will quickly learn, apply and share your Hive knowledge with this e-book. Table Of Content Chapter 1: Introduction 1. What is Hive? 2. Hive Architecture 3. Different modes of Hive 4. What is Hive Server2 (HS2)? 5. Hive vs Map Reduce Chapter 2: Installation and Configuration 1. Installation of Hive 2. Hive shell commands 3. Install and configure MYSQL database Chapter 3: Data operations 1. Data types in Hive 2. Creation and dropping of Database in Hive 3. Create, Drop and altering of tables in Hive 4. Table types and its Usage 5. Partitions 6. Buckets Chapter 4: Queries and Implementation 1. Order by query 2. Group by query 3. Sort by 4. Cluster By 5. Distribute By 6. Join queries 7. Different type of joins 8. Sub queries 9. Embedding custom scripts 10. UDFs (User Define Functions) Chapter 5: Query Language, Built-in Operators and Functions 1. Hive Query Language (HQL) 2. Built-in operators 3. Built-in functions Chapter 6: Data Extraction 1. Working with Structured Data using Hive 2. Working with Semi structured data using Hive (XML, JSON) 3. Hive in Real time projects – When and Where to Use

Practical Hadoop Ecosystem

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Author :
Publisher : Apress
ISBN 13 : 1484221990
Total Pages : 429 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Practical Hadoop Ecosystem by : Deepak Vohra

Download or read book Practical Hadoop Ecosystem written by Deepak Vohra and published by Apress. This book was released on 2016-09-30 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Professional Hadoop Solutions

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1118824180
Total Pages : 505 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Professional Hadoop Solutions by : Boris Lublinsky

Download or read book Professional Hadoop Solutions written by Boris Lublinsky and published by John Wiley & Sons. This book was released on 2013-09-12 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Big Data Made Easy

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Author :
Publisher : Apress
ISBN 13 : 1484200942
Total Pages : 381 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Big Data Made Easy by : Michael Frampton

Download or read book Big Data Made Easy written by Michael Frampton and published by Apress. This book was released on 2014-12-31 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many corporations are finding that the size of their data sets are outgrowing the capability of their systems to store and process them. The data is becoming too big to manage and use with traditional tools. The solution: implementing a big data system. As Big Data Made Easy: A Working Guide to the Complete Hadoop Toolset shows, Apache Hadoop offers a scalable, fault-tolerant system for storing and processing data in parallel. It has a very rich toolset that allows for storage (Hadoop), configuration (YARN and ZooKeeper), collection (Nutch and Solr), processing (Storm, Pig, and Map Reduce), scheduling (Oozie), moving (Sqoop and Avro), monitoring (Chukwa, Ambari, and Hue), testing (Big Top), and analysis (Hive). The problem is that the Internet offers IT pros wading into big data many versions of the truth and some outright falsehoods born of ignorance. What is needed is a book just like this one: a wide-ranging but easily understood set of instructions to explain where to get Hadoop tools, what they can do, how to install them, how to configure them, how to integrate them, and how to use them successfully. And you need an expert who has worked in this area for a decade—someone just like author and big data expert Mike Frampton. Big Data Made Easy approaches the problem of managing massive data sets from a systems perspective, and it explains the roles for each project (like architect and tester, for example) and shows how the Hadoop toolset can be used at each system stage. It explains, in an easily understood manner and through numerous examples, how to use each tool. The book also explains the sliding scale of tools available depending upon data size and when and how to use them. Big Data Made Easy shows developers and architects, as well as testers and project managers, how to: Store big data Configure big data Process big data Schedule processes Move data among SQL and NoSQL systems Monitor data Perform big data analytics Report on big data processes and projects Test big data systems Big Data Made Easy also explains the best part, which is that this toolset is free. Anyone can download it and—with the help of this book—start to use it within a day. With the skills this book will teach you under your belt, you will add value to your company or client immediately, not to mention your career.

Expert Hadoop Administration

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Author :
Publisher : Addison-Wesley Professional
ISBN 13 : 0134703383
Total Pages : 2087 pages
Book Rating : 4.1/5 (347 download)

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Book Synopsis Expert Hadoop Administration by : Sam R. Alapati

Download or read book Expert Hadoop Administration written by Sam R. Alapati and published by Addison-Wesley Professional. This book was released on 2016-11-29 with total page 2087 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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