Hazelcast For Beginners (Paris JUG-1)

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Emrah Kocaman

Slides of Paris JUG event

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http://www.zenika.com/formation-hazelcast-essentials.html
30Th November - Free Training

What is Hazelcast?
Hazelcast Demo
Hazelcast Data Distribution
Hazelcast Features
Q/A Session
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Agenda

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“Hazelcast is In-Memory Data Grid (IMDG)
Solution”
01001
10101
01010
In Memory
Data Computing
In Memory
Data Messaging
++In Memory
Data Storage

an open-source project
8
leading open-source in-memory data
grid.
Apache 2 License
dead simple distributed programming
lightweight w/o any dependency
built with in Istanbul

Hazelcast Inc.
9
Hazelcast Enterprise
Support Contracts
Training / Consulting
Offices in Istanbul & Ankara
(Engineering) , Palo Alto(HQ+Sales)
and London(Sales)

10
“Hazelcast is a java library to create distributed
applications”

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What are the main features of Distributed Applications?

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• Scalability
What are the main features of Hazelcast?

14
• Scalability
• Speed
What are the main features of Hazelcast?

15
Reference : https://gist.github.com/hellerbarde/2843375

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Reference : http://www.statisticbrain.com/average-historic-price-of-ram/

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• Scalability
• Speed
• Simplicity
What are the main features of Distributed Applications?

<backup-count>1</backup-count>
max backup count is 6
Backups increase memory usage since they
are also kept in memory.
21
Data Backup

DATA PARTITIONING
With 4 cluster nodes every server holds
1/4 real data and 1/4 of backups

© 2015 Hazelcast Inc. Confidential & Proprietary 23
Rebalance Data on New Node
44

© 2015 Hazelcast Inc. Confidential & Proprietary 24
Distributed Maps
Fixed number of partitions (default 271)
Each key falls into a partition
partitionId = hash(keyData)%PARTITION_COUNT
Partition ownerships are reassigned upon membership change
A B C

© 2015 Hazelcast Inc. Confidential & Proprietary 25
New Node Added
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 26
Migration
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 27
Migration
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 28
Migration
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 29
Migration
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 30
Migration
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 31
Migration
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 32
Migration Complete
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 33
Data Safety when Node Dies
54

© 2015 Hazelcast Inc. Confidential & Proprietary 34
Node Crashes
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 35
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 36
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 37
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 38
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 39
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 40
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 41
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 42
Backups Are Restored
DA B C

© 2015 Hazelcast Inc. Confidential & Proprietary 43
Recovery Is Complete
DA C

Client/Server Architecture
Embedded Architecture
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Deployment Options

45
Great for early stages of rapid
application development and iteration
Necessary for scale up or scale out
deployments – decouples
upgrading of clients and cluster for
long term TCO
Embedded Hazelcast
Hazelcast Node
1
Applications
Java API
Client-Server Mode
Hazelcast
Node 3
Java API
Applications
Java API
Applications
Java API
Applications
Hazelcast
Node 2
Hazelcast
Node 1
Hazelcast Node
2
Applications
Java API
Hazelcast Node
3
Applications
Java API
Deployment Options

Multicast (default)
TCP/IP
AWS
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Networking Options

48
Data Store Features
Java Collection API: Map, List, Set, Queue
JCache
High Density Memory Store
Hibernate 2nd Level Cache
Web Session Replication: Tomcat, Jetty
Predicate API: Indexes, SQL Query
Persistence: Map/Queue Store & Loader. Write Behind/Through
Eviction
Near Cache
Transactions: Local & XA
WAN Replication
Memcached Interface

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Distributed Computing Features
Java Concurrency API
(Lock, Semaphore, AtomicLong, AtomicReference, Executor Service, Blocking Queue)
Entry and Item Listeners
Entry Processor
Aggregators
Map/Reduce
Data Affinity
Continues Query
Map Interceptors
Delta Update

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Distributed Messaging Features
Queue
Topic (Pub/Sub)
Event Listeners
Ring Buffers

Spring Cache Manager
Hibernate 2nd Level Cache Provider
Web Session Replication
OSGI Support
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Hazelcast Integration
Modules

Management Center (free up to 2 nodes)
High-Density Memory
Tomcat/Jetty Session Replication
Enterprise WAN Replication
Security
Native Clients (.NET/C++)
52
Hazelcast Enterprise
Features

Thank you ! :)
emrah@hazelcast.com
53
any questions ?

54
http://www.zenika.com/formation-hazelcast-essentials.html
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In the realm of real-time applications, Large Language Models (LLMs) have long dominated language-centric tasks, while tools like OpenCV have excelled in the visual domain. However, the future (maybe) lies in the fusion of LLMs and deep learning, giving birth to the revolutionary concept of Large Action Models (LAMs). Imagine a world where AI not only comprehends language but mimics human actions on technology interfaces. For example, the Rabbit r1 device presented at CES 2024, driven by an AI operating system and LAM, brings this vision to life. It executes complex commands, leveraging GUIs with unprecedented ease. In this presentation, join me on a journey as a software engineer tinkering with WebRTC, Janus, and LLM/LAMs. Together, we’ll evaluate the current state of these AI technologies, unraveling the potential they hold for shaping the future of real-time applications.

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Hazelcast For Beginners (Paris JUG-1)

1. 1 Emrah Kocaman Software Engineer @ Hazelcast emrahkocaman emrah@hazelcast.com Martin Black Regional Sales Director @ Hazelcast martin@hazelcast.com

2. 2 http://www.zenika.com/formation-hazelcast-essentials.html 30Th November - Free Training

3. 3 Hazelcast For Beginners

4. What is Hazelcast? Hazelcast Demo Hazelcast Data Distribution Hazelcast Features Q/A Session 4 Agenda

5. 5 what is ?

6. 6 “Hazelcast is In-Memory Data Grid (IMDG) Solution” 01001 10101 01010 In Memory Data Computing In Memory Data Messaging ++In Memory Data Storage

7. an open-source project 7

8. an open-source project 8 leading open-source in-memory data grid. Apache 2 License dead simple distributed programming lightweight w/o any dependency built with in Istanbul

9. Hazelcast Inc. 9 Hazelcast Enterprise Support Contracts Training / Consulting Offices in Istanbul & Ankara (Engineering) , Palo Alto(HQ+Sales) and London(Sales)

10. 10 “Hazelcast is a java library to create distributed applications”

11. 11 What are the main features of Distributed Applications?

12. 12 • Scalability What are the main features of Hazelcast?

13.

14. 14 • Scalability • Speed What are the main features of Hazelcast?

15. 15 Reference : https://gist.github.com/hellerbarde/2843375

16. 16 Memory Getting cheaper and faster

17. 17 Reference : http://www.statisticbrain.com/average-historic-price-of-ram/

18. 18 • Scalability • Speed • Simplicity What are the main features of Distributed Applications?

19. 19 Hazelcast is simple!

20. 20 IT’S DEMO TIME

21. <backup-count>1</backup-count> max backup count is 6 Backups increase memory usage since they are also kept in memory. 21 Data Backup

22. DATA PARTITIONING With 4 cluster nodes every server holds 1/4 real data and 1/4 of backups

24. © 2015 Hazelcast Inc. Confidential & Proprietary 24 Distributed Maps Fixed number of partitions (default 271) Each key falls into a partition partitionId = hash(keyData)%PARTITION_COUNT Partition ownerships are reassigned upon membership change A B C

44. Client/Server Architecture Embedded Architecture 44 Deployment Options

45. 45 Great for early stages of rapid application development and iteration Necessary for scale up or scale out deployments – decouples upgrading of clients and cluster for long term TCO Embedded Hazelcast Hazelcast Node 1 Applications Java API Client-Server Mode Hazelcast Node 3 Java API Applications Java API Applications Java API Applications Hazelcast Node 2 Hazelcast Node 1 Hazelcast Node 2 Applications Java API Hazelcast Node 3 Applications Java API Deployment Options

46. Multicast (default) TCP/IP AWS 46 Networking Options

47. Hazelcast Features 47

48. 48 Data Store Features Java Collection API: Map, List, Set, Queue JCache High Density Memory Store Hibernate 2nd Level Cache Web Session Replication: Tomcat, Jetty Predicate API: Indexes, SQL Query Persistence: Map/Queue Store & Loader. Write Behind/Through Eviction Near Cache Transactions: Local & XA WAN Replication Memcached Interface

49. 49 Distributed Computing Features Java Concurrency API (Lock, Semaphore, AtomicLong, AtomicReference, Executor Service, Blocking Queue) Entry and Item Listeners Entry Processor Aggregators Map/Reduce Data Affinity Continues Query Map Interceptors Delta Update

50. 50 Distributed Messaging Features Queue Topic (Pub/Sub) Event Listeners Ring Buffers

51. Spring Cache Manager Hibernate 2nd Level Cache Provider Web Session Replication OSGI Support 51 Hazelcast Integration Modules

52. Management Center (free up to 2 nodes) High-Density Memory Tomcat/Jetty Session Replication Enterprise WAN Replication Security Native Clients (.NET/C++) 52 Hazelcast Enterprise Features

53. Thank you ! :) emrah@hazelcast.com 53 any questions ?

54. 54 http://www.zenika.com/formation-hazelcast-essentials.html 30Th November - Free Training

Editor's Notes

I’ve joined the team one and a half year ago. teb-bnp paribas joint venture android enterprise
Anyone used it before? Anyone heard it before?
Hazelcast is an operational in-memory computing platform that lets companies manage data and distribute processing using in-memory storage and parallel execution for breakthrough application speed and scale.
it is under apache 2 license so you can fork hazelcast and develop your own features or product, it is just 1 jar..
-So, How do we survive as a company? We develop enterprise features such as high density memory. So you can put huge amount of data to native memory which is not under control JVM. Another example can be SSL support.. (security feature) - Management Center after 2 Nodes Also we open sourced our clients.
Going beyond “normal amounts of data” and “normal amounts of users” This is possible with two ways: Scale up vs. Scale out Scale up: Better hardware Scale out: Cluster/Distribute
Bruce Banner :) Choose between fighting one horse-sized duck and 100 duck-sized horses Scale up: Cons->PRICE, Greater risk of hardware failure causing bigger outages, generally severe vendor lock-in and limited upgradeability in the future. Scale out: Pros-> Much cheaper than scaling vertically, Easier to run fault-tolerance, Easy to upgrade.
L1 - There is a sandwich in front of you. L2 - Walk to the kitchen and make a sandwich RAM - Drive to the store, purchase sandwich fixings, drive home and make sandwich HD - Drive to the store. Purchase seeds. Grow seeds..... .... ... Harvest lettuce, wheat, etc. Make sandwich.
In Hazelcast, every data is stored in a partition. And partitions are stored in nodes… There are 271 partitions as default, and every node has information about which partition is stored in which node.

Hazelcast For Beginners (Paris JUG-1)

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Editor's Notes