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If you want to discover one of the latest tools designed to produce stunning Big Data insights, this book features everything you need to get to grips with your data. Whether you are a data architect, developer, or a business strategist, HDInsight adds value in everything from development, administration, and reporting.
Electronic data processing --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Computer networks --- Distributed processing. --- Apache Hadoop. --- Hadoop --- Distributed processing --- E-books
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Computer software --- Application software --- Electronic data processing --- Teams in the workplace --- Logiciels --- Progiciels --- Traitement réparti. --- Groupes de travail --- Development. --- Distributed processing. --- Management. --- Développement. --- Informatique. --- Git (Computer file) --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Development of application software --- Development of computer software --- Software development --- Computer networks --- Development --- Distributed processing --- Management --- Traitement réparti. --- Développement.
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Electronic data processing departments --- Electronic data processing --- 657.6 --- 657.5 --- AA / International- internationaal --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Auditing --- Distributed processing --- Audit --- Accountantscontrole. Administratiekantoren. Interne audit. Financiële ratios en analyse --- Computer networks
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This book is useful for Hadoop administrators who need to learn how to monitor and diagnose their clusters. Also, the book will prove useful for new users of the technology, as the language used is simple and easy to grasp.
Adobe Hadoop (Computer file). --- Electronic data processing -- Distributed processing. --- File organization (Computer science). --- Open source software. --- Engineering & Applied Sciences --- Computer Science --- Apache Hadoop. --- Hadoop --- Electronic data processing --- Information retrieval --- Big data --- Open source software --- Free software (Open source software) --- Open code software --- Opensource software --- Computer software --- Data sets, Large --- Large data sets --- Data sets --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Documentation --- Information science --- Information storage and retrieval systems --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Computer networks --- Distributed processing
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If you’re an R developer looking to harness the power of big data analytics with Hadoop, then this book tells you everything you need to integrate the two. You’ll end up capable of building a data analytics engine with huge potential. Write Hadoop MapReduce within R Learn data analytics with R and the Hadoop platform Handle HDFS data within R Understand Hadoop streaming with R Encode and enrich datasets into R In Detail Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing. Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS of Hadoop. You will start with the installation and configuration of R and Hadoop. Next, you will discover information on various practical data analytics examples with R and Hadoop. Finally, you will learn how to import/export from various data sources to R. Big Data Analytics with R and Hadoop will also give you an easy understanding of the R and Hadoop connectors RHIPE, RHadoop, and Hadoop streaming.
Electronic data processing --- Data mining --- Data structures (Computer science) --- R (Computer program language) --- GNU-S (Computer program language) --- Domain-specific programming languages --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Computer networks --- Distributed processing --- Apache Hadoop. --- Hadoop --- E-books --- Big data. --- Data mining. --- Data sets, Large --- Large data sets --- Data sets
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As a Packt Beginner's Guide, the book is packed with clear step-by-step instructions for performing the most useful tasks, getting you up and running quickly, and learning by doing. This book assumes no existing experience with Hadoop or cloud services. It assumes you have familiarity with a programming language such as Java or Ruby but gives you the needed background on the other topics.
File organization (Computer science) --- Electronic data processing --- Open source software --- Free software (Open source software) --- Open code software --- Opensource software --- Computer software --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Computer networks --- File management (Computer science) --- File systems (Computer science) --- Organization, File (Computer science) --- Database management --- Distributed processing --- Adobe Hadoop (Computer file) --- E-books --- Apache Hadoop (Computer file). --- Database management. --- Electronic data processing -- Distributed processing. --- File organization (Computer science). --- Hadoop (Computer program). --- Fetus --- Human embryo --- Radioisotopes in obstetrics --- Breastfeeding --- Breast feeding --- Nursing (Breastfeeding) --- Suckling --- Infants --- Lactation --- Wet nurses --- Nuclear medicine --- Obstetrics --- Radiation --- Fetus, Effect of radiation on the --- Effect of radiation on. --- Safety measures. --- Health aspects. --- Nutrition --- Physiological effect --- Radiation effects --- Diseases
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