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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.
Hadoop offers distributed processing of large datasets across clusters and is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. It enables computing solutions that are scalable, cost-effective, flexible, and fault tolerant to back up very large data sets from hardware failures. Starting off with the basics of Hadoop administration, this book becomes increasingly exciting with the best strategies of backing up distributed storage databases. You will gradually learn about the backup and recovery principles, discover the common failure points in Hadoop, and facts about backing up Hive metadata. A deep dive into the interesting world of Apache HBase will show you different ways of backing up data and will compare them. Going forward, you'll learn the methods of defining recovery strategies for various causes of failures, failover recoveries, corruption, working drives, and metadata. Also covered are the concepts of Hadoop matrix and MapReduce. Finally, you'll explore troubleshooting strategies and techniques to resolve failures.
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.
Fast data ingestion, serving, and analytics in the Hadoop ecosystem have forced developers and architects to choose solutions using the least common denominator—either fast analytics at the cost of slow data ingestion or fast data ingestion at the cost of slow analytics. There is an answer to this problem. With the Apache Kudu column-oriented data store, you can easily perform fast analytics on fast data. This practical guide shows you how. Begun as an internal project at Cloudera, Kudu is an open source solution compatible with many data processing frameworks in the Hadoop environment. In this book, current and former solutions professionals from Cloudera provide use cases, examples, best practices, and sample code to help you get up to speed with Kudu. Explore Kudu’s high-level design, including how it spreads data across servers Fully administer a Kudu cluster, enable security, and add or remove nodes Learn Kudu’s client-side APIs, including how to integrate Apache Impala, Spark, and other frameworks for data manipulation Examine Kudu’s schema design, including basic concepts and primitives necessary to make your project successful Explore case studies for using Kudu for real-time IoT analytics, predictive modeling, and in combination with another storage engine
A handy reference guide for data analysts and data scientists to help to obtain value from big data analytics using Spark on Hadoop clusters About This Book This book is based on the latest 2.0 version of Apache Spark and 2.7 version of Hadoop integrated with most commonly used tools. Learn all Spark stack components including latest topics such as DataFrames, DataSets, GraphFrames, Structured Streaming, DataFrame based ML Pipelines and SparkR. Integrations with frameworks such as HDFS, YARN and tools such as Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall. Who This Book Is For Though this book is primarily aimed at data analysts and data scientists, it will also help architects, programmers, and practitioners. Knowledge of either Spark or Hadoop would be beneficial. It is assumed that you have basic programming background in Scala, Python, SQL, or R programming with basic Linux experience. Working experience within big data environments is not mandatory. What You Will Learn Find out and implement the tools and techniques of big data analytics using Spark on Hadoop clusters with wide variety of tools used with Spark and Hadoop Understand all the Hadoop and Spark ecosystem components Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Conventional and Structured Streaming, MLLib, ML Pipelines and Graphx See batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming Get to grips with data science and machine learning using MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall. In Detail Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data. Style and approach This step-by-step pragmatic guide will make life easy no matter what your level of experience. You will deep dive into Apache Spark on Hadoop clusters through ample exciting real-life examples. Practical tutorial explains data science in simple terms to help programmers and data analysts get started with Data Science

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