Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. This is a Packt Instant How-to guide, which provides concise and clear recipes for getting started with Hadoop.This book is for big data enthusiasts and would-be Hadoop programmers. It is also meant for Java programmers who either have not worked with Hadoop at all, or who know Hadoop and MapReduce but are not sure how to deepen their understanding.
If you are a Big Data enthusiast and wish to use Hadoop v2 to solve your problems, then this book is for you. This book is for Java programmers with little to moderate knowledge of Hadoop MapReduce. This is also a one-stop reference for developers and system admins who want to quickly get up to speed with using Hadoop v2. It would be helpful to have a basic knowledge of software development using Java and a basic working knowledge of Linux.
Manage, analyze, and visualize data with Microsoft Excel 2013 to transform raw data into ready to use information About This Book Create formulas to help you analyze and explain findings Develop interactive spreadsheets that will impress your audience and give them the ability to slice and dice data A step-by-step guide to learn various ways to model data for businesses with the help of Excel 2013 Who This Book Is For If you want to start using Excel 2013 for data analysis and business modeling and enhance your skills in the data analysis life cycle then this book is for you, whether you're new to Excel or experienced. What You Will Learn Discover what Excel formulas are all about and how to use them in your spreadsheet development Identify bad data and learn cleaning strategies Create interactive spreadsheets that engage and appeal to your audience Leverage Excel's powerful built-in tools to get the median, maximum, and minimum values of your data Build impressive tables and combine datasets using Excel's built-in functionality Learn the powerful scripting language VBA, allowing you to implement your own custom solutions with ease In Detail Excel 2013 is one of the easiest to use data analysis tools you will ever come across. Its simplicity and powerful features has made it the go to tool for all your data needs. Complex operations with Excel, such as creating charts and graphs, visualization, and analyzing data make it a great tool for managers, data scientists, financial data analysts, and those who work closely with data. Learning data analysis and will help you bring your data skills to the next level. This book starts by walking you through creating your own data and bringing data into Excel from various sources. You'll learn the basics of SQL syntax and how to connect it to a Microsoft SQL Server Database using Excel's data connection tools. You will discover how to spot bad data and strategies to clean that data to make it useful to you. Next, you'll learn to create custom columns, identify key metrics, and make decisions based on business rules. You'll create macros using VBA and use Excel 2013's shiny new macros. Finally, at the end of the book, you'll be provided with useful shortcuts and tips, enabling you to do efficient data analysis and business modeling with Excel 2013. Style and approach This is a step-by-step guide to performing data analysis and business modelling with Excel 2013, complete with examples and tips.
Make life at the office easier for server administrators by helping them build resilient Ubuntu server systems About This Book Tackle the issues you come across in keeping your Ubuntu server up and running Build server machines and troubleshoot cloud computing related issues using Open Stack Discover tips and best practices to be followed for minimum maintenance of Ubuntu Server 3 Who This Book Is For This book is for a vast audience of Linux system administrators who primarily work on Debian-based systems and spend long hours trying fix issues with the enterprise server. Ubuntu is already one of the most popular OSes and this book targets the most common issues that most administrators have to deal with. With the right tools and definite solutions, you will be able to keep your Ubuntu servers in the pink of health. What You Will Learn Deploy packages and their dependencies with repositories Set up your own DNS and network for Ubuntu Server Authenticate and validate users and their access to various systems and services Maintain, monitor, and optimize your server resources and avoid tremendous load Get to know about processes, assigning and changing priorities, and running processes in background Optimize your shell with tools and provide users with an improved shell experience Set up separate environments for various services and run them safely in isolation Understand, build, and deploy OpenStack on your Ubuntu Server In Detail Ubuntu is becoming one of the favorite Linux flavors for many enterprises and is being adopted to a large extent. It supports a wide variety of common network systems and the use of standard Internet services including file serving, e-mail, Web, DNS, and database management. A large scale use and implementation of Ubuntu on servers has given rise to a vast army of Linux administrators who battle it out day in and day out to make sure the systems are in the right frame of operation and pre-empt any untoward incidents that may result in catastrophes for the businesses using it. Despite all these efforts, glitches and bugs occur that affect Ubuntu server's network, memory, application, and hardware and also generate cloud computing related issues using OpenStack. This book will help you end to end. Right from setting up your new Ubuntu Server to learning the best practices to host OpenStack without any hassles. You will be able to control the priority of jobs, restrict or allow access users to certain services, deploy packages, tackle issues related to server effectively, and reduce downtime. Also, you will learn to set up OpenStack, and manage and monitor its services while tuning the machine with best practices. You will also get to know about Virtualization to make services serve users better. Chapter by chapter, you will learn to add new features and functionalities and make your Ubuntu server a full-fledged, production-ready system. Style and approach This book contains topic-by-topic discussion in an easy-to-understand language with loads of examples to help you take care of Ubuntu Server. Plenty of screenshots will guide you through a step-by-step approach.
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.
"MapReduce is a technology that enables users to process large datasets and Hadoop is an implementation of MapReduce." This book "is a concise introduction to Hadoop and programming with MapReduce. It is aimed to get you started and give you an overall feel for programming with Hadoop providing you with a well-grounded foundation to understand and solve all of your MapReduce problems as needed"--Cover.
Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved! PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand and adopt the model. What You Will Learn Understand the advanced features of PySpark2 and SparkSQL Optimize your code Program SparkSQL with Python Use Spark Streaming and Spark MLlib with Python Perform graph analysis with GraphFrames Who This Book Is For Data analysts, Python programmers, big data enthusiasts
Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to optimize your PySpark SQL code. PySpark SQL Recipes starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You’ll also discover how to solve problems in graph analysis using graphframes. On completing this book, you’ll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases. What You Will Learn Understand PySpark SQL and its advanced features Use SQL and HiveQL with PySpark SQL Work with structured streaming Optimize PySpark SQL Master graphframes and graph processing Who This Book Is ForData scientists, Python programmers, and SQL programmers.
A guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. 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.
The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.
Discover how data science can help you gain in-depth insight into your business - the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.
Visualize and analyze your Hadoop data using Hunk About This Book Explore your data in Hadoop and NoSQL data stores Create and optimize your reporting experience with advanced data visualizations and data analytics A comprehensive developer's guide that helps you create outstanding analytical solutions efficiently Who This Book Is For If you are Hadoop developers who want to build efficient real-time Operation Intelligence Solutions based on Hadoop deployments or various NoSQL data stores using Hunk, this book is for you. Some familiarity with Splunk is assumed. What You Will Learn Deploy and configure Hunk on top of Cloudera Hadoop Create and configure Virtual Indexes for datasets Make your data presentable using the wide variety of data visualization components and knowledge objects Design a data model using Hunk best practices Add more flexibility to your analytics solution via extended SDK and custom visualizations Discover data using MongoDB as a data source Integrate Hunk with AWS Elastic MapReduce to improve scalability In Detail Hunk is the big data analytics platform that lets you rapidly explore, analyse, and visualize data in Hadoop and NoSQL data stores. It provides a single, fluid user experience, designed to show you insights from your big data without the need for specialized skills, fixed schemas, or months of development. Hunk goes beyond typical data analysis methods and gives you the power to rapidly detect patterns and find anomalies across petabytes of raw data. This book focuses on exploring, analysing, and visualizing big data in Hadoop and NoSQL data stores with this powerful full-featured big data analytics platform. You will begin by learning the Hunk architecture and Hunk Virtual Index before moving on to how to easily analyze and visualize data using Splunk Search Language (SPL). Next you will meet Hunk Apps which can easy integrate with NoSQL data stores such as MongoDB or Sqqrl. You will also discover Hunk knowledge objects, build a semantic layer on top of Hadoop, and explore data using the friendly user-interface of Hunk Pivot. You will connect MongoDB and explore data in the data store. Finally, you will go through report acceleration techniques and analyze data in the AWS Cloud. Style and approach A step-by-step guide starting right from the basics and deep diving into the more advanced and technical aspects of Hunk.
