Pro Apache Phoenix: An SQL Driver for HBase - Brossura

Akhtar, Shakil; Magham, Ravi

Brossura

ISBN 10: 1484223691 ISBN 13: 9781484223697

Casa editrice: Apress, 2016

Riassunto

Leverage Phoenix as an ANSI SQL engine built on top of the highly distributed and scalable NoSQL framework HBase. Learn the basics and best practices that are being adopted in Phoenix to enable a high write and read throughput in a big data space. 

This book includes real-world cases such as Internet of Things devices that send continuous streams to Phoenix, and the book explains how key features such as joins, indexes, transactions, and functions help you understand the simple, flexible, and powerful API that Phoenix provides. Examples are provided using real-time data and data-driven businesses that show you how to collect, analyze, and act in seconds.  

Pro Apache Phoenix covers the nuances of setting up a distributed HBase cluster with Phoenix libraries, running performance benchmarks, configuring parameters for production scenarios, and viewing the results. The book also shows how Phoenix plays well with other key frameworks in the Hadoop ecosystem such as Apache Spark, Pig, Flume, and Sqoop.

You will learn how to:

• Handle a petabyte data store by applying familiar SQL techniques
  
• Store, analyze, and manipulate data in a NoSQL Hadoop echo system with HBase
  
• Apply best practices while working with a scalable data store on Hadoop and HBase
  
• Integrate popular frameworks (Apache Spark, Pig, Flume) to simplify big data analysis
  
• Demonstrate real-time use cases and big data modeling techniques

Who This Book Is For

Data engineers, Big Data administrators, and architects.

Su questo libro

Informazioni sull?autore

Shakil Akhtar is TOGAF 9 Certified Enterprise Architect passionate about Digital Transformation, Cloud Computing, Big Data and Internet of Things technologies. He holds many certifications including Oracle Certified Master Java Enterprise Architect (OCMJEA). He worked with Cisco, Oracle, CA Technologies and various other organizations. Where he developed and architected large-scale complex enterprise software, creating frameworks and scaling systems to petabyte datasets. He is an enthusiastic open source user and longtime fan. When not working, he can be found playing guitar and doing some jamming sessions with his friends.

Ravi Mugham, an engineer passionate about data and data-driven engineering, experienced with working and scaling solutions to petabyte datasets. In his past experience, he has worked with CA Technologies, Bazaarvoice and various other startups. Actively involved in open source projects and is a PMC member to Apache Phoenix. Currently, his interests are in Distributed Data stream processing

Dalla quarta di copertina

Leverage Phoenix as an ANSI SQL engine built on top of the highly distributed and scalable NoSQL framework HBase. Learn the basics and best practices that are being adopted in Phoenix to enable a high write and read throughput in a big data space. 

This book includes real-world cases such as Internet of Things devices that send continuous streams to Phoenix, and the book explains how key features such as joins, indexes, transactions, and functions help you understand the simple, flexible, and powerful API that Phoenix provides. Examples are provided using real-time data and data-driven businesses that show you how to collect, analyze, and act in seconds.  

Pro Apache Phoenix covers the nuances of setting up a distributed HBase cluster with Phoenix libraries, running performance benchmarks, configuring parameters for production scenarios, and viewing the results. The book also shows how Phoenix plays well with other key frameworks in the Hadoop ecosystem such as Apache Spark, Pig, Flume, and Sqoop.

You will learn how to:

• Handle a petabyte data store by applying familiar SQL techniques
  
• Store, analyze, and manipulate data in a NoSQL Hadoop echo system with HBase
  
• Apply best practices while working with a scalable data store on Hadoop and HBase
  
• Integrate popular frameworks (Apache Spark, Pig, Flume) to simplify big data analysis
  
• Demonstrate real-time use cases and big data modeling techniques
  

Dettagli dell'edizione

• Editore: Apress
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 1484223691
• ISBN 13: 9781484223697
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 160
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3,69115 Heidelberg, Germany; Heidelberg; 69115; Germania