News

This week The apache Ignite book becomes one of the top books of leanpub

This week The apache Ignite book becomes one of the top books of leanpub.

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

No comments :