Book Image

Apache Ignite Quick Start Guide

By : Sujoy Acharya
Book Image

Apache Ignite Quick Start Guide

By: Sujoy Acharya

Overview of this book

Apache Ignite is a distributed in-memory platform designed to scale and process large volume of data. It can be integrated with microservices as well as monolithic systems, and can be used as a scalable, highly available and performant deployment platform for microservices. This book will teach you to use Apache Ignite for building a high-performance, scalable, highly available system architecture with data integrity. The book takes you through the basics of Apache Ignite and in-memory technologies. You will learn about installation and clustering Ignite nodes, caching topologies, and various caching strategies, such as cache aside, read and write through, and write behind. Next, you will delve into detailed aspects of Ignite’s data grid: web session clustering and querying data. You will learn how to process large volumes of data using compute grid and Ignite’s map-reduce and executor service. You will learn about the memory architecture of Apache Ignite and monitoring memory and caches. You will use Ignite for complex event processing, event streaming, and the time-series predictions of opportunities and threats. Additionally, you will go through off-heap and on-heap caching, swapping, and native and Spring framework integration with Apache Ignite. By the end of this book, you will be confident with all the features of Apache Ignite 2.x that can be used to build a high-performance system architecture.

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Apache Ignite Quick Start Guide
Sujoy Acharya
Nov, 2018 | 260 pages
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Table of Contents (9 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Getting Familiar with Apache Ignite
Getting Familiar with Apache Ignite
Why Apache Ignite?
Exploring the features
Refactoring the architecture
Installing Apache Ignite
Running HelloWorld
Classifying Apache Ignite
Summary
References
2
Understanding the Topologies and Caching Strategies
Understanding the Topologies and Caching Strategies
CAP theorem and Apache Ignite
Clustering architecture
Caching topology
Caching strategy
Summary
3
Working with Data Grids
Working with Data Grids
Exploring the Data Grid
Configuring the DataGrid
Web session clustering
Summary
4
Exploring the Compute Grid and Query API
Exploring the Compute Grid and Query API
Query API
Compute Grid
Summary
5
Building MicroServices with Service Grid
Building MicroServices with Service Grid
Understanding the service grid
Deploying microservices on Ignite
Processing complex events
Summary
6
Sharpening Ignite Skills
Sharpening Ignite Skills
Writing data to a persistent store
Processing transactions
Exploring distributed data structures
Summary
7
Deploying To Production
Deploying To Production
Understanding the memory model
Monitoring memory and caches
Securing data
Tuning performance
Exploring the deployment options
Summary
References
8
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Compute Grid

In distributed computing, a task is split into multiple small chunks or sub-tasks; each individual task is executed in different nodes of the cluster in parallel. This pattern offers high scalability and high performance through parallel processing.

Splitter and Aggregator is a well known enterprise integration pattern (EIP) used to split a parent task into multiple child tasks, execute the child messages in parallel (possibly using message queues to distribute the sub-tasks), and then aggregate the results of each sub-task.

The Apache Ignite Compute Grid API is the gateway to distributed computing. In this section, we are going to cover the following compute grid topics:

  • Distributed Closure
  • Map Reduce and Fork-Join
  • ExecutorService
  • Job Scheduling

Distributed Closure...

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