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Make a suggestion Refine your searchData analytics with Hadoop / Benjamin Bengfort
Title : Data analytics with Hadoop : an introduction for data scientists Material Type: printed text Authors: Benjamin Bengfort, Author Publisher: Beijing : O'Reilly Publication Date: 2016 Pagination: xvi, 268 p. Size: 24 cm ISBN (or other code): 978-1-491-91370-3 General note: Includes bibliographical references and index Languages : English (eng) Original Language : English (eng) Descriptors: Apache Hadoop
Big data
Data mining
Electronic data processing - Distributed processing
File organization (Computer science)Class number: 006.312 Abstract: "Data analytics with Hadoop "- Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib Contents note: The age of the data product; An operating system for big data; A framework for Python and Hadoop streaming; In-memory computing with Spark; Distributed analysis and patterns; Data mining and warehousing; Data ingestion; Analytics with higher-level APIs; Machine learning; Summary : doing distributed data science; Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=17989 Hold
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Barcode Call number Media type Location Section Status 1702-002338 006.312 Ben-Dat 2016 General Collection Library "Max van der Stoel" English Available 1702-002339 006.312 Ben-Dat 2016 General Collection SEEU Library Skopje English Available
Title : Distributed systems : concepts and design Material Type: printed text Authors: George Coulouris, Author ; Jean Dollimore, Author ; Tim Kindberg, Author Edition statement: 4th edition Publisher: Harlow, England : Addison Wesley Publication Date: 2005 Series: International computer science series Pagination: xiv-927 p. Size: 24 cm ISBN (or other code): 978-0-321-26354-4 General note: Includes bibliographical references (p. 859-908)
Includes index (p.909-927)Languages : English (eng) Original Language : English (eng) Descriptors: Distributed operating systems (Computers)
Electronic data processing - Distributed processingClass number: 004.36 Abstract: The fourth edition of this best-selling text continues to provide a comprehensive source of material on the principles and practice of distributed computer systems and the exciting new developments based on them, using a wealth of modern case studies to illustrate their design and development. Highlights of the fourth edition include: A Three entirely new chapters on peer-to-peer systems, web services, and mobile and ubiquitous systems. A More than 25 detailed case studies of well-known systems, eight of them new, including studies of the Grid, Cooltown, Bluetooth andthe (in)security of the WiFi WEP protocol. A Updated coverage of XML and its security extensions, the Advanced Encryption Standard and security design for ubiquitous systems.Distributed Systems provides students of computer science and engineering with the skills they will need to design and maintain software for distributed applications.It will also be invaluable to software engineers and systems designers wishing to understand new and future developments in the field. George Coulouris is a Senior Visiting Fellow in the Computer Laboratory at the University of Cambridge. Jean Dollimore was, until her retirement, Senior Lecturer in computer science at Queen Mary College, Universityof London. Tim Kindberg is a Senior Researcher at Hewlett-Packard Laboratories in Bristol. Check out www.cdk4.net or www.pearsoned.co.uk/coulouris for a rich set of resources for students and instructors, including: A The book bibliography with links to relevant online references. A PowerPoint teaching slides. A Presentation guidelines for instructors. A Solutions to all exercises (for instructors only). A Material from previous editions that will not fit in this one. A Source code for all program listings. A Links to many courses using the book. A carefully maintained errata list! and more! Contents note: Characterization of distributed systems; System models; Networking and internet working; Interprocess communication; Distributed objects and remote invocation; Operating system support; Security; Distributed file systems; Name services; Peer-to-peer systems; Time and global states; Coordination and agreement; Transactions and concurrency control; Distributed transactions; Replication; Mobile and Ubiquitous computing; Distributed multimedia systems; Distributed shared memory; Web services; Corba case study; Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=14050 Hold
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Barcode Call number Media type Location Section Status 1702-000805 004.36 Cou-Dis 2005 General Collection Library "Max van der Stoel" English Available 1702-000806 004.36 Cou-Dis 2005 General Collection Library "Max van der Stoel" English Available
Title : Distributed systems : principles and paradigms Material Type: printed text Authors: Andrew S. Tanenbaum, Author ; Maarten van Steen, Author Publisher: Upper Saddle River, N.J. : Prentice Hall Publication Date: 2002 Pagination: xxii, 803 p. Size: 24 cm ISBN (or other code): 978-0-13-088893-8 General note: Includes bibliographical references (p. 737-782) and index Languages : English (eng) Descriptors: Distributed operating systems (Computers)
Electronic data processing - Distributed processingClass number: 004.36 Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=11526 Hold
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Barcode Call number Media type Location Section Status 5702-004729 004.36 Tan-Dis 2002 General Collection Library "Max van der Stoel" English Available
Title : Explorations in parallel distributed processing : a handbook of models, programs, and exercises Material Type: printed text Authors: James L McClelland, Author ; David E Rumelhart, Author Publisher: Cambridge, Mass. : MIT Press Publication Date: 1989 Series: Computational models of cognition and perception Pagination: ix, 355 p. Size: 26 cm. ISBN (or other code): 978-0-262-63132-7 General note: Includes bibliographical references (p. 331-334) Languages : English (eng) Descriptors: Electronic data processing - Distributed processing
Parallel processing (Electronic computers)Class number: 004.35 Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=6622 Copies
Barcode Call number Media type Location Section Status 5702-010541 004.35 McC-Exp 1989 General Collection Library "Max van der Stoel" English Not for loan
Title : Hadoop in practice Material Type: printed text Authors: Alex Holmes, Author Publisher: Shelter Island, N.Y. : Manning Publication Date: 2012 Pagination: xxiii, 511 p. Layout: ill. Size: 24 cm ISBN (or other code): 978-93-511-9742-3 General note: Includes index (p. 475-487) Languages : English (eng) Original Language : English (eng) Descriptors: Apache Hadoop
Electronic data processing - Distributed processing
File organization (Computer science)Class number: 005.74 Abstract: "Hadoop in Practice"-collects 85 Hadoop examples and presents them in a problem/solution format. Each technique addresses a specific task you'll face, like querying big data using Pig or writing a log file loader. You'll explore each problem step by step, learning both how to build and deploy that specific solution along with the thinking that went into its design. As you work through the tasks, you'll find yourself growing more comfortable with Hadoop and at home in the world of big data. Contents note: Preface; Acknowledgments; About this book; About the cover illustration; Background and fundamentals; Data logistics; Big data patterns; Beyond MapReduce; Summary; Appendix; Index; Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=17953 Hold
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Barcode Call number Media type Location Section Status 1702-002266 005.74 Hol-Had 2012 General Collection SEEU Library Skopje English Available
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