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Hazelcast 101
This document provides an overview of Hazelcast, a leading in-memory data grid solution. Hazelcast provides distributed data structures, execution services, and caching capabilities. It allows applications to scale linearly by adding additional nodes. Hazelcast can be configured via XML, API or Spring and supports features like transactions, custom serialization, and native client libraries. It integrates with Spring Framework for caching and can discover nodes via multicast or TCP/IP lists to form clusters across distributed systems.
Hazelcast 101
- 1. THE LEADING IMDGSOLUTION EXPLAINED HAZELCAST 101
- 2. About Me EMRAHKOCAMAN @emrahkocaman https://github.com/emrahkocaman emrahkocaman@gmail.com ! • Oracle Certified Professional Java Programmer • 6+ years of Professional Java development • Was working on enterprise Java technologies • Software Developer at Hazelcast (since July 2014)
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- 4. Agenda • Whatis IMDG? • What is Hazelcast? • Configuring Hazelcast • Distributed World of Hazelcast • Hazelcast - Spring Framework Integration • Management Center
- 5. What’s IMDG? IN-MEMORYDATA GRIDS Provide virtually unlimited processing power and memory as additional cluster members are added Expand in real time and dynamically to meet increasing requirements Increase capacity in a linear and predictable manner Leverage commodity or integrated systems that are easily added without complexity
- 6. What is Hazelcast? • The leading In Memory Data Grid • Highly Available Elastic Cache • 4.2 MBytes JAR • Distributed Execution Platform • Embedded or Client Server • Cloud Ready • Open Source - Apache License 2.0
- 7. Distributed Data-structures •IAtomicLong • IdGenerator • Lock • CountDownLatch • Semaphore • Queue • Map • MultiMap • Set • List • Topic • Executor • Write your own!
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- 11. Use Cases •Scale your application • Data sharing • Distributed Caching • HTTP Session Replication • Hibernate 2nd Level Cache • Parallel Execution • Map-Reduce • Spring Cache Provider
- 12. Features • JavaCollection API • MultiMap • Topic • Java Concurrency API • Lock, Semaphore, CountDownLatch, ExecutorService • Transactions • Custom Serialization • Off-Heap Support • Native Clients: C#, C++, Java, REST, memcached
- 13. CONFIGURING & FORMINGA CLUSTER
- 14. Forming A Cluster • Hazelcast Clusters run on JVM • Hazelcast discovers other instances via Multicast (Default) • Use TCP/IP lists when Multicast not possible • Segregate Clusters on same network via configuration • Hazelcast can form clusters on Amazon EC2.
- 15. Configuration • Hazelcastsearches for hazelcast.xml on class path • Will use hazelcast-default.xml for everything else. • Hazelcast can be configured via XML,API or Spring • Configure Networks, Data Structures, Indexes, EC2 • Config is locked at start-up, cannot dynamically change (feature coming soon)
- 16. Start Your FirstNodes
- 17. How Hazelcast Works 1 / 2 • Multiple Partitions Per Node • Consistent Hashing: hash(key) % partition count • Option to control partitioning • Possibility to find key owner for every key • Support for Near-Caching and executions on key owner • Automatic Fault-Tolerance • Sync / Async Backups • Configurable Backup Counts
- 18. How Hazelcast Works 2 / 3 New Node Re-balance
- 19. How Hazelcast Works 3 / 3 A node crashes Backups restored Backup for recovered data Recover from backup
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- 27. Spring Integration •Supports Spring 2.5+ • Hazelcast Namespace • Spring Cache Provider • Spring Data Integration (on the way)
- 28. Spring Integration BASICBEAN DECLARATION
- 29. Spring Integration HAZELCASTNAMESPACE
- 30. Spring Integration HAZELCASTNAMESPACE
- 31. Spring Cache DECLARATIVECONFIGURATION
- 32. Spring Cache ANNOTATIONBASED CONFIGURATION
- 33. “Management is, aboveall, a practice where art, science, and craft meet” –HENRY MINTZBERG
- 34. Q & A THANK YOU @emrahkocaman, @hazelcast emrah@hazelcast.com hazelcast@googlegroups.com http://www.hazelcast.com http://github.com/hazelcast/hazelcast