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Apache Hadoop Yarn

Author: Arun Murthy
Publisher: Addison-Wesley Professional
ISBN: 0133441911
Size: 65.75 MB
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“This book is a critically needed resource for the newly released Apache Hadoop 2.0, highlighting YARN as the significant breakthrough that broadens Hadoop beyond the MapReduce paradigm.” —From the Foreword by Raymie Stata, CEO of Altiscale The Insider’s Guide to Building Distributed, Big Data Applications with Apache Hadoop™ YARN Apache Hadoop is helping drive the Big Data revolution. Now, its data processing has been completely overhauled: Apache Hadoop YARN provides resource management at data center scale and easier ways to create distributed applications that process petabytes of data. And now in Apache Hadoop™ YARN, two Hadoop technical leaders show you how to develop new applications and adapt existing code to fully leverage these revolutionary advances. YARN project founder Arun Murthy and project lead Vinod Kumar Vavilapalli demonstrate how YARN increases scalability and cluster utilization, enables new programming models and services, and opens new options beyond Java and batch processing. They walk you through the entire YARN project lifecycle, from installation through deployment. You’ll find many examples drawn from the authors’ cutting-edge experience—first as Hadoop’s earliest developers and implementers at Yahoo! and now as Hortonworks developers moving the platform forward and helping customers succeed with it. Coverage includes YARN’s goals, design, architecture, and components—how it expands the Apache Hadoop ecosystem Exploring YARN on a single node Administering YARN clusters and Capacity Scheduler Running existing MapReduce applications Developing a large-scale clustered YARN application Discovering new open source frameworks that run under YARN

Big Data And High Performance Computing

Author: L. Grandinetti
Publisher: IOS Press
ISBN: 1614995834
Size: 42.83 MB
Format: PDF, Mobi
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Big Data has been much in the news in recent years, and the advantages conferred by the collection and analysis of large datasets in fields such as marketing, medicine and finance have led to claims that almost any real world problem could be solved if sufficient data were available. This is of course a very simplistic view, and the usefulness of collecting, processing and storing large datasets must always be seen in terms of the communication, processing and storage capabilities of the computing platforms available. This book presents papers from the International Research Workshop, Advanced High Performance Computing Systems, held in Cetraro, Italy, in July 2014. The papers selected for publication here discuss fundamental aspects of the definition of Big Data, as well as considerations from practice where complex datasets are collected, processed and stored. The concepts, problems, methodologies and solutions presented are of much more general applicability than may be suggested by the particular application areas considered. As a result the book will be of interest to all those whose work involves the processing of very large data sets, exascale computing and the emerging fields of data science

Big Data Processing With Hadoop

Author: Revathi, T.
Publisher: IGI Global
ISBN: 1522537910
Size: 64.89 MB
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Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.

Practical Data Science With Hadoop And Spark

Author: Ofer Mendelevitch
Publisher: Addison-Wesley Professional
ISBN: 0134029720
Size: 60.49 MB
Format: PDF, Docs
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The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language

Big Data

Author: Daniel Fasel
Publisher: Springer-Verlag
ISBN: 3658115890
Size: 39.90 MB
Format: PDF, ePub, Docs
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Dieser Herausgeber-Band bietet eine umfassende Einführung in das Gebiet Big Data. Neben einer Markteinschätzung und grundlegenden Konzepten (semantische Modellbildung, Anfragesprachen, Konsistenzgewährung etc.) werden wichtige NoSQL-Systeme (Key/Value Store, Column Store, Document Store, Graph Database) vorgestellt und erfolgreiche Anwendungen aus unterschiedlichen Perspektiven erläutert. Eine Diskussion rechtlicher Aspekte und ein Vorschlag zum Berufsbild des Data Scientist runden das Buch ab. Damit erhält die Leserschaft Handlungsempfehlungen für die Nutzung von Big-Data-Technologien im Unternehmen.

Sql Nosql Datenbanken

Author: Andreas Meier
Publisher: Springer-Verlag
ISBN: 3662476649
Size: 25.14 MB
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Die Autoren führen in das Gebiet der relationalen (SQL) und nicht-relationalen (NoSQL) Datenbanken ein. Themenschwerpunkte in der 8. Auflage bilden Datenmanagement, Datenmodellierung, Abfrage- und Manipulationssprachen, Konsistenzgewährung, Datenschutz und -Sicherheit, Systemarchitektur, Mehrbenutzerbetrieb. Das Buch bietet außerdem einen Überblick über postrelationale und nicht-relationale Datenbanksysteme. Neben klassischen Konzepten werden wichtige Aspekte für NoSQL-Datenbanken erläutert, wie das Verfahren Map/Reduce, Verteilungsoptionen (Fragmente, Replikation) oder das CAP-Theorem (Consistency, Availability, Partition Tolerance). Eine Webseite ergänzt den Inhalt des Buches durch Tutorien für Abfrage- und Manipulationssprachen (SQL, Cypher), Übungsumgebungen für Datenbanken (MySQL, Neo4j) sowie zwei Fallstudien zu travelblitz (OpenOffice Base, Neo4j). Das Buch richtet sich sowohl an Studierende, die eine Einführung in das Gebiet der SQL- und NoSQL-Datenbanken suchen, wie auch an Praktiker, denen es hilft, Stärken und Schwächen relationaler Ansätze sowie Entwicklungen für Big-Data-Anwendungen besser einschätzen zu können.

Analytische Informationssysteme

Author: Peter Gluchowski
Publisher: Springer-Verlag
ISBN: 3662477637
Size: 68.17 MB
Format: PDF, ePub
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Informationssysteme für die analytischen Aufgaben von Fach- und Führungskräften treten verstärkt in den Vordergrund. Dieses etablierte Buch diskutiert und evaluiert Begriffe und Konzepte wie Business Intelligence und Big Data. Die aktualisierte und erweiterte fünfte Auflage liefert einen aktuellen Überblick zu Technologien, Produkten und Trends im Bereich analytischer Informationssysteme. Beiträge aus Wirtschaft und Wissenschaft geben einen umfassenden Überblick und eignen sich als fundierte Entscheidungsgrundlage beim Aufbau und Einsatz derartiger Technologien.

Digitale Bildverarbeitung

Author: Wilhelm Burger
Publisher: Springer-Verlag
ISBN: 354027653X
Size: 58.79 MB
Format: PDF
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Die Autoren geben eine fundierte Einführung in die wichtigsten Methoden der digitalen Bildverarbeitung. Dabei steht die praktische Anwendbarkeit im Vordergrund, formale und mathematische Aspekte sind auf das Wesentliche reduziert, ohne dabei auf eine präzise und konsistente Vorgehensweise zu verzichten. Der Text eignet sich für technisch orientierte Studiengänge ab dem 3.Semester und basiert auf der mehrjährigen Lehrerfahrung der Autoren zu diesem Thema. Der Einsatz in der Lehre wird durch zahlreiche praktische Übungsaufgaben unterstützt. Das Buch eignet sich auch als detaillierte Referenz für Praktiker und Anwender gängiger Verfahren der digitalen Bildverarbeitung, z.B. in der Medizin, der Materialprüfung, der Robotik oder der Medientechnik. Softwareseitig basiert das Buch auf der in Java implementierten und frei verfügbaren Bildverarbeitungsumgebung ImageJ.