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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


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