Paco Nathan

Enterprise Data Workflows with Cascading (eBook, ePUB)

Streamlined Enterprise Data Management and Analysis

• Format: ePub

Produktbeschreibung

There is an easier way to build Hadoop applications. With this hands-on book, youll learn how to use Cascading, the open source abstraction framework for Hadoop that lets you easily create and manage powerful enterprise-grade data processing applicationswithout having to learn the intricacies of MapReduce.Working with sample apps based on Java and other JVM languages, youll quickly learn Cascadings streamlined approach to data processing, data filtering, and workflow optimization. This book demonstrates how this framework can help your business extract meaningful information from large amounts of distributed data.Start working on Cascading example projects right awayModel and analyze unstructured data in any format, from any sourceBuild and test applications with familiar constructs and reusable componentsWork with the Scalding and Cascalog Domain-Specific LanguagesEasily deploy applications to Hadoop, regardless of cluster location or data sizeBuild workflows that integrate several big data frameworks and processesExplore common use cases for Cascading, including features and tools that support themExamine a case study that uses a dataset from the Open Data Initiative

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: O'Reilly Media
• Seitenzahl: 170
• Erscheinungstermin: 11. Juli 2013
• Englisch
• ISBN-13: 9781449359607
• Artikelnr.: 39142453

Autorenporträt

Paco Nathan is a Data Scientist at Concurrent, Inc., and heads up the developer outreach program there. He has a dual background from Stanford in math/stats and distributed computing, with 25+ years experience in the tech industry. As an expert in Hadoop, R, predictive analytics, machine learning, natural language processing, Paco has built and led several expert Data Science teams, with data infrastructure based on large-scale cloud deployments. He has presented twice on the AWS Start-Up Tour, and gives talks often about Hadoop, Data Science, and Cloud Computing.

Inhaltsangabe

Preface
Chapter 1: Getting Started
Chapter 2: Extending Pipe Assemblies
Chapter 3: Test-Driven Development
Chapter 4: Scalding-A Scala DSL for Cascading
Chapter 5: Cascalog-A Clojure DSL for Cascading
Chapter 6: Beyond MapReduce
Chapter 7: The Workflow Abstraction
Chapter 8: Case Study: City of Palo Alto Open Data
Troubleshooting Workflows
Index
Colophon