Wednesday

The Apache Ignite Book: table of contents

This is the table of contents of the Apache Ignite book that we are planning to publish end of this year 2018.


Table of contents:
  • Chapter 1. Introduction
  • Chapter 2. Getting started with Apache Ignite
    • Installing and setting up Apache Ignite
    • Building from source code
    • Run multiple instances of Apache Ignite in a single host
    • Running Apache Ignite from Docker
    • Using Apache Ignite SQLLINE command tool
    • Meet with Apache Ignite SQL engine: H2 database
    • Using a universal SQL client IDE to working with Apache Ignite
    • Apache Ignite thin client
    • First Java application
    • Using REST API for manipulating the Apache Ignite caches
    • Configure a multimode cluster in different hosts
    • Summary
    • What's Next
  • Chapter 3. Apache Ignite use cases
    • Caching for fast data access
    • High volume transaction processing
    • HTAP
    • Fast data processing
    • Lambda architecture
    • Resilient web acceleration
    • Microservices in distributed fashion
    • Cache as a service
    • Big Data accelerations
    • In-memory machine learning
    • In-memory geospatial
    • Cluster management
    • Summary
    • What’s next
  • Chapter 4. Architecture deep drive
    • Functional overview
    • Understanding the cluster topology: shared nothing architecture
      • Client and server node
      • Embedded with the application
      • Client and the server nodes in the same host
      • Running multiple nodes within single JVM
      • Real cluster topology
    • Data partitioning in Ignite
      • Understanding data distribution: DHT
      • Rendezvous hashing
      • Reliability and redundancy of the data
      • Partitioned mode
      • Replicated mode
      • Local mode
      • Near cache
      • Partition loss policies
      • Partition map exchange in Ignite
    • Caching strategy
      • Cache a-side
      • Read through and write through
      • Write behind
    • Apache Ignite life cycle
    • Protocols and clients
    • Distributed data models
    • CAP theorem and where does Ignite stand in?
    • Durable memory architecture
    • Native persistence
    • Data affinity in Ignite
      • Cluster group
      • Data collocation
      • Compute collocation with Data
      • Node filter
      • ZeroSPOF
    • Data rebalancing and indexing
    • Transactions
    • Discovery service provider interfaces
    • Security
    • Multi data center replication
    • Asynchronous support
    • Resilience
    • Ignite baseline topology
    • Ignite internal engines
      • Ignite SQL engines
      • Ignite full text search engine
      • Servlet container
    • Management and monitoring
    • Key API’s
    • Summary
    • What's next
  • Chapter 5: Intelligent caching
    • Smart in-memory caching
    • Database caching
      • MyBatis caching
      • Hibernate 2nd level cache
    • Memoization
    • Web session clustering
    • Updating cache
    • Prepare the cache correctly
    • Summary
    • What's next
  • Chapter 6. Database
    • Using JPA with Ignite
    • Hibenate OGM
    • SQL queries
      • Projection and indexing
      • Query API
      • Collocated distributed Joins
      • Non-collocated distributed joins
      • Performance tuning
    • Cache queries
      • Scan queries
      • Text queries
    • Data expiration
    • Eviction policies
    • Continues query
    • Distributed transactions
    • Persistence
      • Native persistence
      • Persistence in RDBMS
      • Persistence in NoSQL
    • HTAP
    • Security
    • Summary
    • What’s next
  • Chapter 7. Distributed computing
    • Compute grid
      • Distributed Closures
      • MapReduce and fork-join
      • Per-Node share state
      • Distributed task session
      • Fault tolerance & checkpointing
      • Collocation of compute and data
      • Job scheduling
    • Service Grid
      • Developing services
      • Cluster singleton
      • Service management configuration
    • Developing microservices
  • Chapter 8. Fast data processing
    • IgniteDataStreamer
      • StreamReciever
      • StreamVisitor
    • Kafka streamer
    • Camel data streamer
    • Flume streamer
    • Storm data streamer
    • ZeroMQ streamer
    • IoT in action: MQTT streamer
    • Implementing lambda architecture
    • Summary
    • What’s next
  • Chapter 9. Accelerating BigData computing
    • Hadoop accelerator
      • In-memory Map/Reduce
      • Using Apache Pig for data analysis
      • Near real-time data analysis with Hive
      • Replace HDFS by Ignite In-memory File System (IGFS)
      • Hadoop file system cache
    • Ignite for Apache Spark
      • Apache Spark – an introduction
      • IgniteContext
      • IgniteRDD
      • Ignite for Spark data frame
      • Spark application example
    • Summary
    • What’s next
  • Chapter 10. Monitoring and management
    • Web console for monitoring
    • JMX monitoring
    • Using 3rd party tools for monitoring
    • Summary


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.