Hadoop

Hadoop

This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.

Author: Tom White

Publisher:

ISBN: 1491901683

Category: Databases

Page:

View: 400

"Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, you l learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters."--
Categories: Databases

Hadoop The Definitive Guide

Hadoop  The Definitive Guide

This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.

Author: Tom White

Publisher: "O'Reilly Media, Inc."

ISBN: 9781491901700

Category: Computers

Page: 756

View: 664

Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. You’ll learn about recent changes to Hadoop, and explore new case studies on Hadoop’s role in healthcare systems and genomics data processing. Learn fundamental components such as MapReduce, HDFS, and YARN Explore MapReduce in depth, including steps for developing applications with it Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN Learn two data formats: Avro for data serialization and Parquet for nested data Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer) Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop Learn the HBase distributed database and the ZooKeeper distributed configuration service
Categories: Computers

Advanced Intelligent Systems for Sustainable Development AI2SD 2018

Advanced Intelligent Systems for Sustainable Development  AI2SD   2018

SSRN Scholarly Paper. Rochester, Social Science Research Network, NY 26
May 2018. https://papers.ssrn.com/abstract=3185342 6. White, T.: Hadoop—The
Definitive Guide 4e-. 4th ed. O'Reilly, Beijing (2015) 7. Alapati, S.R.: Expert
Hadoop ...

Author: Mostafa Ezziyyani

Publisher: Springer

ISBN: 9783030119287

Category: Technology & Engineering

Page: 1005

View: 163

This book includes the outcomes of the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD-2018), held in Tangier, Morocco on July 12–14, 2018. Presenting the latest research in the field of computing sciences and information technology, it discusses new challenges and provides valuable insights into the field, the goal being to stimulate debate, and to promote closer interaction and interdisciplinary collaboration between researchers and practitioners. Though chiefly intended for researchers and practitioners in advanced information technology management and networking, the book will also be of interest to those engaged in emerging fields such as data science and analytics, big data, internet of things, smart networked systems, artificial intelligence, expert systems and cloud computing.
Categories: Technology & Engineering

Big Scientific Data Management

Big Scientific Data Management

White, T.: Hadoop-The Definitive Guide 4e, 4th edn, pp. 1–4. O'Reilly Media,
Newton (2015) 5. Zang, D.S., Huo, J., Liang, D., et al.: High energy physics data
analysis system based on mapreduce. Comput. Eng. 40(2), 1–5 (2014) 6. Glaser,
F.

Author: Jianhui Li

Publisher: Springer

ISBN: 9783030280611

Category: Computers

Page: 332

View: 896

This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018. The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies.
Categories: Computers

Social Computing

Social Computing

White, T.: Hadoop: The Definitive Guide, 4E. O'Reilly Media ... Liu, X., Peng, C.,
Yu, Z.: Research on the small files problem of Hadoop. ... HadoopArchivesGuide.
http://hadoop.apache.org/docs/stable/hadoop-archives/Hadoop Archives.html 6.

Author: Wanxiang Che

Publisher: Springer

ISBN: 9789811020537

Category: Computers

Page: 716

View: 539

This two volume set (CCIS 623 and 634) constitutes the refereed proceedings of the Second International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, held in Harbin, China, in August 2016. The 91 revised full papers presented were carefully reviewed and selected from 338 submissions. The papers are organized in topical sections on Research Track (Part I) and Education Track, Industry Track, and Demo Track (Part II) and cover a wide range of topics related to social computing, social media, social network analysis, social modeling, social recommendation, machine learning, data mining.
Categories: Computers

Big Data Analytics with R

Big Data Analytics with R

Data processing in Hadoop has recently become one of the major and most
influential topics in the Big Data community. There are a large number of online ...
Hadoop: The Definitive Guide, 4th Edition. USA: O'Reilly In addition to these, the
 ...

Author: Simon Walkowiak

Publisher: Packt Publishing Ltd

ISBN: 9781786463722

Category: Computers

Page: 506

View: 312

Utilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market Who This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R. What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities Deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner Apply the R language to real-world Big Data problems on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platform In Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O. Style and approach This book will serve as a practical guide to tackling Big Data problems using R programming language and its statistical environment. Each section of the book will present you with concise and easy-to-follow steps on how to process, transform and analyse large data sets.
Categories: Computers

Architecting Modern Data Platforms

Architecting Modern Data Platforms

A Guide to Enterprise Hadoop at Scale Jan Kunigk, Ian Buss, Paul Wilkinson,
Lars George ... In particular, see: • Hadoop: The Definitive Guide, 4th Edition, by
Tom White (O'Reilly) • ZooKeeper, by Benjamin Reed and Flavio Junqueira ...

Author: Jan Kunigk

Publisher: O'Reilly Media

ISBN: 9781491969243

Category: Computers

Page: 636

View: 522

There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’ll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability
Categories: Computers