Skip to main content

The Apache Ignite book

After a year, we have decided to write down another book related to the Apache Ignite distributed database. Within a year, Apache Ignite team redesigned the memory architecture and released a few new versions which cover new features such as Native persistence, baseline topology. Apache Ignite also optimized the performance of the SQL, added new features like Alter tables to DDL and also introduced SQLLINE command line tool for SQL based interaction. From this given release Apache Ignite team revisited the definition and purpose of the project. By their words, the definition "in-memory data fabrics/grids" limits its capabilities, rather than the distributed database, caching, and processing platform. So, in this book, we are going to cover the following topics:

  1. Apache Ignite architecture in details to build right solutions to given business problems.
  2. Use cases of using in-memory databases
  3. How Apache Ignite SQL works and how you can optimize the SQL engine to get better performance
  4. Developing applications with Spring Data/Hibernate OGM/MyBatis backed by Apache Ignite.
  5. How to use Apache Ignite compute grid as a low-latency software.
  6. Developing distributed microservice in fault-tolerant fashion.
  7. Processing continuously never-ending streaming data.
  8. Accelerate Big data ecosystem without changing any existing code.
  9. How to use Apache Ignite as a Cache as a Service to improve the performance of your applications. 


The target audience of this book will be IT architect, team leaders, a programmer with minimum programming knowledge.

No excessive knowledge is required, though it would be good to be familiar with JAVA and Spring framework. The book is also useful for any reader, who already familiar with Oracle Coherence, Hazelcast, Infinispan or Memcached. The release date of the book is not fixed yet, but we expect it in winter 2018.

Comments

Popular posts from this blog

Send e-mail with attachment through OSB

Oracle Service Bus (OSB) contains a good collection of adapter to integrate with any legacy application, including ftp, email, MQ, tuxedo. However e-mail still recognize as a stable protocol to integrate with any application asynchronously. Send e-mail with attachment is a common task of any business process. Inbound e-mail adapter which, integrated with OSB support attachment but outbound adapter doesn't. This post is all about sending attachment though JavaCallout action. There are two ways to handle attachment in OSB: 1) Use JavaCallout action to pass the binary data for further manipulation. It means write down a small java library which will get the attachment and send the e-mail. 2) Use integrated outbound e-mail adapter to send attachment, here you have to add a custom variable named attachment and assign the binary data to the body of the attachment variable. First option is very common and easy to implement through javax.mail api, however a much more developer manage t

Tip: SQL client for Apache Ignite cache

A new SQL client configuration described in  The Apache Ignite book . If it got you interested, check out the rest of the book for more helpful information. Apache Ignite provides SQL queries execution on the caches, SQL syntax is an ANSI-99 compliant. Therefore, you can execute SQL queries against any caches from any SQL client which supports JDBC thin client. This section is for those, who feels comfortable with SQL rather than execute a bunch of code to retrieve data from the cache. Apache Ignite out of the box shipped with JDBC driver that allows you to connect to Ignite caches and retrieve distributed data from the cache using standard SQL queries. Rest of the section of this chapter will describe how to connect SQL IDE (Integrated Development Environment) to Ignite cache and executes some SQL queries to play with the data. SQL IDE or SQL editor can simplify the development process and allow you to get productive much quicker. Most database vendors have their own front-en

Load balancing and fail over with scheduler

Every programmer at least develop one Scheduler or Job in their life time of programming. Nowadays writing or developing scheduler to get you job done is very simple, but when you are thinking about high availability or load balancing your scheduler or job it getting some tricky. Even more when you have a few instance of your scheduler but only one can be run at a time also need some tricks to done. A long time ago i used some data base table lock to achieved such a functionality as leader election. Around 2010 when Zookeeper comes into play, i always preferred to use Zookeeper to bring high availability and scalability. For using Zookeeper you have to need Zookeeper cluster with minimum 3 nodes and maintain the cluster. Our new customer denied to use such a open source product in their environment and i was definitely need to find something alternative. Definitely Quartz was the next choose. Quartz makes developing scheduler easy and simple. Quartz clustering feature brings the HA and