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Exploring Hadoop Tools on Windows 10 Platform

Exploring Hadoop Tools on Windows 10 Platform
Author: Dr. Poornima G. Naik
Publisher: Shashwat Publication
Total Pages: 226
Release: 2023-02-23
Genre: Computers
ISBN: 939076193X
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This book is precisely organized into five chapters. Each chapter has been carefully developed with the help of several implemented commands. Dedicated efforts have been put in to ensure that every concept of Hadoop tools discussed in this book is explained with help of relevant commands and screenshots of the outputs have been included. Chapter-1 includes details of Installing Hadoop on Windows 10, with prerequisites required. A step by step detail process of downloading is explained along with Configuring Hadoop Cluster, HDFS Site Configuration, Hadoop Web UI, HDFS Commands etc . Chapter-2 describes Installation Pig on Windows 10. Apache Pig is a platform build on the top of Hadoop. It explores Hands on Sessions with Apache Pig focusing on Loading Data into Pig Relation and Operators in Pig. Chapter-3 talks about Installing Sqoop on Windows 10. It also demonstrates Installing MySQL Workbench, Exporting and importing Data Using Sqoop. Chapter-4 explores Installation of HBase on Windows 10 along with Testing HBase Installation and different HBase Commands. Chapter-5 the last chapter of the book entitled ‘Installing Hive On Windows 10’, includes Installing Apache Derby, Cygwin Tool, downloading Apache Hive binaries, Initializing Hive Metastore etc.

Web 2.0 Fundamentals: With AJAX, Development Tools, and Mobile Platforms

Web 2.0 Fundamentals: With AJAX, Development Tools, and Mobile Platforms
Author: Oswald Campesato
Publisher: Jones & Bartlett Learning
Total Pages: 794
Release: 2011
Genre: Business & Economics
ISBN: 0763779733
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Designed for a broad spectrum of people with technically diverse backgrounds, this book covers the most recent developments in Web 2.0 programming topics and applications. The accompanying CD-ROM and companion Web site provide code samples.

Big Data Made Easy

Big Data Made Easy
Author: Michael Frampton
Publisher: Apress
Total Pages: 381
Release: 2014-12-31
Genre: Computers
ISBN: 1484200942
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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.

Proceedings of Data Analytics and Management

Proceedings of Data Analytics and Management
Author: Abhishek Swaroop
Publisher: Springer Nature
Total Pages: 550
Release: 2024-01-29
Genre: Technology & Engineering
ISBN: 9819965535
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This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.

Introduction to Machine Learning in the Cloud with Python

Introduction to Machine Learning in the Cloud with Python
Author: Pramod Gupta
Publisher: Springer Nature
Total Pages: 284
Release: 2021-04-28
Genre: Technology & Engineering
ISBN: 3030712702
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This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.

Big Data and Hadoop

Big Data and Hadoop
Author: VK Jain
Publisher: KHANNA PUBLISHING
Total Pages: 655
Release: 2017-01-01
Genre: Education
ISBN: 938260913X
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This book introduces you to the Big Data processing techniques addressing but not limited to various BI (business intelligence) requirements, such as reporting, batch analytics, online analytical processing (OLAP), data mining and Warehousing, and predictive analytics. The book has been written on IBMs Platform of Hadoop framework. IBM Infosphere BigInsight has the highest amount of tutorial matter available free of cost on Internet which makes it easy to acquire proficiency in this technique. This therefore becomes highly vunerable coaching materials in easy to learn steps. The book optimally provides the courseware as per MCA and M. Tech Level Syllabi of most of the Universities. All components of big Data Platform like Jaql, Hive Pig, Sqoop, Flume , Hadoop Streaming, Oozie: HBase, HDFS, FlumeNG, Whirr, Cloudera, Fuse , Zookeeper and Mahout: Machine learning for Hadoop has been discussed in sufficient Detail with hands on Exercises on each.

Azure and Xamarin Forms

Azure and Xamarin Forms
Author: Russell Fustino
Publisher: Apress
Total Pages: 271
Release: 2018-06-15
Genre: Computers
ISBN: 1484235614
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Discover how to create cross platform apps for Android, iOS and UWP using Azure services and C# with Xamarin Forms. This book illustrates how to utilize Azure cloud storage for serving up Azure SQL DB data through Azure App Services. The book starts by setting up Xamarin and introducing Xamarin Forms and then covers the Azure Portal from a developer’s perspective and goes on to demonstrate how to build an Azure Service using Quickstart. You'll also see how to add Azure support to Xamarin Forms application. You'll review in detail how to build a Xamarin Form with Azure Client and modify an existing app to become a Xamarin Forms Client for Azure with offline synchronization. You then move on to third-party controls that speed up development. By the end of the book, you will be able to use Azure and Xamarin together and master how to use Azure Mobile Quickstarts, Azure SQL plumbing, database synchronization and Xamarin Forms. What You'll Learn Create a Xamarin Forms App and understand the Structure of a Xamarin Forms App. Navigate pages and use platform specific coding. Use images, ListView and the Azure Mobile App Quickstart to build a Service and Xamarin Forms app Modify an existing app to use Azure Client Libraries, understand offline storage with SQLite and incorporate offline synchronization Who This Book Is For Software developers new to Xamarin and/or Azure and for the developers who are familiar with both the technologies to use in mobile apps.

Big Data Analytics

Big Data Analytics
Author: Ümit Demirbaga
Publisher: Springer Nature
Total Pages: 299
Release:
Genre:
ISBN: 3031556399
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Big Data Analytics with Hadoop 3

Big Data Analytics with Hadoop 3
Author: Sridhar Alla
Publisher: Packt Publishing Ltd
Total Pages: 471
Release: 2018-05-31
Genre: Computers
ISBN: 1788624955
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Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.

Hadoop: The Definitive Guide

Hadoop: The Definitive Guide
Author: Tom White
Publisher: "O'Reilly Media, Inc."
Total Pages: 687
Release: 2012-05-10
Genre: Computers
ISBN: 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