Tuesday

Book: High performance in-memory computing with Apache Ignite has been published

The book "High performance in-memory computing with apache Ignite" has been released and available at http://leanpub.com/ignite




The goal of the book is to provide a guide for those who really need to implement the In-memory platform in their projects. At the same time, the idea behind the book is not writing a manual.

This book wraps all the topics like in-memory data grid, highly available service grid, streaming and in-memory computing use cases from high-performance computing to get the performance gain. The book will be particularly useful for those, who have the following use cases:

  • You have database bottleneck in your application and want to solve the problem.
  • You have a high volume of ACID transactions in your system.
  • You want to develop and deploy microservices in distributed fashion.
  • You have existing Hadoop ecosystem (OLAP) and want to improve the performance of the Map/Reduce jobs without making any changes in your existing Map/Reduce jobs.
  • You want to share Spark RDD directly in-memory (without storing the state to disk), which can dramatically increase the performance of the Spark jobs.
  • You are planning to migrate to microservices and the web session clustering is the problem for you.
  • You are planning to process continuous never-ending streams and complex events of data in scalable and fault-tolerant fashion.
  • You want to use distributed computations in parallel fashion to gain high performance, low latency, and linear scalability.
  • You heard about Off-heap memory but don't know how to use it in your application.

For every topic, a complete application is delivered, which will help the audience to quick start with the topic. The book is a project-based guide, where each chapter focuses on the complete implementation of a real-world scenario, the commonly occurring challenges in each scenario has also discussed, along with tips and tricks and best practices on how to overcome them. Every chapter is independent and a complete project.

Who is this book for

Target audience of this book will be IT architect, team leaders, a programmer with minimum programming knowledge, who want to get the maximum performance from their applications.

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.

Happy Reading.

Friday

The full table of contents of the book High Performance in-memory computing with Apache Ignite

The book High Performance in-memory computing with Apache Ignite has been completed and available at LeanPub.


Table of contents:

  • Introduction
    • What is Apache Ignite
    • Who uses Apache Ignite
    • Why Ignite instead of others
    • Our Hope
  • Chapter one: Installation and the first Ignite application
    • Pre-requirities
    • Installation
    • Run multiple instances of Ignite in a single host
    • Configure a multi-node cluster in different host
    • Rest client to manipulate with Ignite
    • Java client
    • SQL client
    • Conclusion
    • What's Next
  • Chapter two: Architecture overview
    • Functional overview
    • ClusterTopology
      • Client and Server
      • Embedded with the application
      • Server in separate JVM (real cluster topology)
      • Client and Server in separate JVM on single host
    • Caching Topology
      • Partitioned caching topology
      • Replicated caching topology
      • Local mode
    • Caching strategy
      • Cache-aside
      • Read-through and Write-through
      • Write behind
    • Data model
    • CAP theorem and where does Ignite stand in?
    • Clustering
      • Cluster group
      • Data collocation
      • Compute collocation with Data
      • ZeroSPOF
    • How SQL queries works in Ignite
    • Multi-data center replication
    • Asynchronous support
    • Resilience
    • Security
    • KeyAPI
    • Conclusion
    • What's next
  • Chapter three: In-memory caching
    • Apache Ignite as a 2nd level cache
      • MyBatis 2nd level cache
      • Hibernate 2nd level cache
    • Java method caching
    • Web session clustering with Apache Ignite
    • Apache Ignite as a big memory, off-heap memory
    • Conclusion
    • What’s next
  • Chapter four: Persistence
    • Persistence Ignite’s cache
      • Persistence in RDBMS (PostgreSQL)
      • Persistence in MongoDB
    • Cache queries
      • Scan queries
      • Text queries
    • SQL queries
      • Projection and indexing with annotations
      • Query API
      • Collocated distributed Joins
      • Non-collocated distributed joins
      • Performance tuning SQL queries
    • Apache Ignite with JPA
    • Expiration & Eviction of cache entries in Ignite
      • Expiration
      • Eviction
    • Transaction
      • Ignite transactions
      • Transaction commit protocols
      • Optimistic Transactions
      • Pessimistic Transactions
      • Performance impact on transaction
    • Conclusion
    • What’s next
  • Chapter five: 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
    • Conclusion
    • What’s next
  • Chapter six: Streaming and complex event processing
    • Introducing data streamer
      • StreamReceiver
      • StreamVisitor
    • IgniteDataStreamer
      • Direct Ingestion
      • Mediated Ingestion
    • Camel data streamer
    • Flume streamer
    • Storm data streamer
    • Conclusion
    • What’s next
  • Chapter seven: 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 in Ignite