Distributed Computing with Hazelcast
summary
Overview of Hazelcast internals with a live two‑JVM demo showing a distributed java.util.Map working across nodes, lock semantics (lock prevents remote put), and Management Center displaying backups and cluster stats with ~10,000 entries. Data is sharded into 271 partitions and replicas use a backup count up to 6; partitions migrate on join/leave and ownership runs operations on the owning node (entry processor). Native C# and C++ clients are open sourced and optional map store persistence exists for durability.
AI-written summary · about
chapters (17)
- 0:00Introduction to talk
- 1:17What is Hazelcast
- 3:08Hazelcast features
- 6:26Simple distributed map demo
- 7:32Demo setup and tools
- 8:59Running Hazelcast console
- 10:06Distributed data operations
- 12:21Monitoring with Management Center
- 14:41Data management in clusters
- 18:44Backup and partition handling
- 20:15Distributed data structures
- 22:26Distributed processing
- 23:16Caching and integrations
- 24:42Enterprise features
- 25:06Who uses Hazelcast
- 25:49Hazelcast Enhancement Proposals
- 26:35Q&A session
related talks
59mDistributed applications using Hazelcast
41mWhat can go wrong with the distributed system - the Hazelcast exp...
55mHazelcast - Hitchhiker’s Guide. Grzegorz Piwowarek. Java Fest 2020 Online
45mjava.util.concurrent for Distributed Coordination
41mDistributed Java DBs Under the Hood: Main Components and Interactions Between Them
38mHazelcast That Could: Getting Lightning-Fast Responses at Hundreds of RPS
46mWhat can go wrong in a distributed system - experience from...
47mjava.util.concurrent for Distributed Coordination
