High Performance in-memory computing with Apache Ignite - Tapa blanda

Zheludkov, Michael; Bhuiyan, Shamim; Isachenko, Timur

 
9781365732355: High Performance in-memory computing with Apache Ignite
Tapa blanda
ISBN 10: 1365732355 ISBN 13: 9781365732355
Editorial: Lulu.com, 2017

Sinopsis

This book covers a verity of topics, including in-memory data grid, highly available service grid, streaming (event processing for IoT and fast data) and in-memory computing use cases from high-performance computing to get performance gains. The book will be particularly useful for those, who have the following use cases:1) You have a high volume of ACID transactions in your system.2) You have database bottleneck in your application and want to solve the problem.3) You want to develop and deploy Microservices in a distributed fashion.4) You have an existing Hadoop ecosystem (OLAP) and want to improve the performance of map/reduce jobs without making any changes in your existing map/reduce jobs.5) You want to share Spark RDD directly in-memory (without storing the state into the disk)7) You are planning to process continuous never-ending streams and complex events of data.8) You want to use distributed computations in parallel fashion to gain high performance.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

This book covers a verity of topics, including in-memory data grid, highly available service grid, streaming (event processing for IoT and fast data) and in-memory computing use cases from high-performance computing to get performance gains. The book will be particularly useful for those, who have the following use cases: 1) You have a high volume of ACID transactions in your system. 2) You have database bottleneck in your application and want to solve the problem. 3) You want to develop and deploy Microservices in a distributed fashion. 4) You have an existing Hadoop ecosystem (OLAP) and want to improve the performance of map/reduce jobs without making any changes in your existing map/reduce jobs. 5) You want to share Spark RDD directly in-memory (without storing the state into the disk) 7) You are planning to process continuous never-ending streams and complex events of data. 8) You want to use distributed computations in parallel fashion to gain high performance.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Lulu.com
Año de publicación
2017
Idioma
Inglés
ISBN 10 
1365732355
ISBN 13 
9781365732355
Encuadernación
Tapa blanda
Número de páginas
360
Contacto del fabricante
no disponible
Persona responsable
HACHETTE LIVRE SA
https://www.hachette.fr/

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