Online Media Data Stream Processing with Kafka
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This talk was held at the third meeting of the Swiss Big Data User Group on September 17 at ETH Zürich.
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Online Media Data Stream Processing with Kafka
- 1. CC 2.0 by William Brawley | http://flic.kr/p/7PdUP3
- 2. 18. Septem ber 2012 • What is Streaming Data? 2 • Why Kafka? • Kafka Architecture • Use Case: Prospective Search Overview
- 3. 18. Septem ber 2012 • Spin-off of MeMo News AG, the 3 leading provider for Social Media Monitoring & Analytics in Switzerland • Big Data expert, focused on Hadoop, HBase and Solr • Objective: Transforming data into insights About Sentric
- 4. CC 2.0 by audreyjm529| http://flic.kr/p/mNMtL
- 5. 18. Septem ber 2012 • Website Activity Data 5 • User activity • Server activity • Social Media Data • News Data • … • How to Analyze in Real-Time? What is Streaming Data? Data Streams
- 6. 18. Septem ber 2012 6 now t Offline (Hadoop/MR) Online (Ka5a) What is Streaming Data? Offline vs. Online
- 7. CC 2.0 by Tom Hilton | http://flic.kr/p/54KSXy
- 8. 18. Septem ber 2012 • Message Queues (RabbitMQ, ActiveMQ) 8 • do not scale / have no persistence • Flume / Scribe • Log-Aggregation only, high throughput and scalable, push model • Focus on offline consumption • Kafka • High throughput and scalable, pull model • Different consumption profiles Why Kafka? Streaming Systems
- 9. 18. Septem ber 2012 9 Source: h<p://research.microso@.com/en-‐us/um/people/srikanth/netdb11/netdb11papers/netdb11-‐final12.pdf Why Kafka? Consumer Performance
- 10. CC 2.0 by Presidente | http://flic.kr/p/2ptSZ
- 11. 18. Septem ber 2012 • Messaging System 11 • Publish-Subscribe • Persistent • High-Throughput Kafka Architecture Key Concepts
- 12. 18. Septem ber 2012 12 ZooKeeper Producer Consumer Producer Broker Consumer Producer Push Pull Consumer Producer Kafka Architecture Messaging
- 13. 18. Septem ber 2012 Topics 13 logs … page-views Msg Msg Msg Consumer Consumer Consumer Kafka Architecture Publish-Subscribe
- 14. 18. Septem ber 2012 • Persists messages to disc 14 • Topic is base abstraction • Binary write ahead log • No message ID • Message offset ID (byte position) • Messages retained a specific time • Default is 7 days Kafka Architecture Persistent
- 15. 18. Septem ber 2012 • API Simplicity 15 • Append message • Fetch message from given byte position • Batching • Stateless Broker • O(1) disc access (no seeks) • Use of operating system features Kafka Architecture High-Throughput
- 16. CC 2.0 by nolifebeforecoffee | http://flic.kr/p/c1UTf
- 17. 18. Septem ber 2012 n News Agents 17 Kafka REST RT Alerts Web-UI HBase MySQL Solr Icons by http://dryicons.com Prospective Search Solution Architecture
- 18. 18. Septem ber 2012 18 Processing Pull (Batch) Prospective Search RT Alerts Kafka Consumer Icons by http://dryicons.com Prospective Search Prospective Search with Kafka
- 19. 18. Septem ber 2012 • http://incubator.apache.org/kafka/ 19 • http://sites.computer.org/debull/ A12june/A12JUN-CD.pdf Resources to get started
- 20. 18. Septem ber 2012 20 Questions? Christian Gügi, christian.guegi@sentric.ch Swiss Big Data User Group Thank you!