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Classroom Contents
Fast Data Architectures for Streaming Applications
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- 1 Intro
- 2 Riley Report
- 3 Context
- 4 Hadoop Classic
- 5 Hadoop Architecture
- 6 Time vs Money
- 7 Streaming Data Architecture
- 8 Streaming Engines
- 9 Latency Requirements
- 10 RealTime
- 11 Latency
- 12 Windowing
- 13 Machine Learning
- 14 Batch Jobs
- 15 Volume
- 16 HighScale Problems
- 17 Partitioning Data
- 18 Integration
- 19 Sequels
- 20 Spark vs Kafka
- 21 Dynamic ML
- 22 Event Processing
- 23 Individual Event Processing
- 24 Google Stream Processing
- 25 Apache Beam
- 26 Stream Processing
- 27 Flink
- 28 akkaStreams
- 29 KafkaStreams
- 30 Spark
- 31 Lambda
- 32 Microservices and Fast Data
- 33 Microservices
- 34 Single Responsibility
- 35 Micro Services
- 36 Reactive Programming
- 37 Twitter
- 38 Big Data vs Microservices
- 39 Light Ben
- 40 Merging streams
- 41 Runner
- 42 Storm
- 43 Knife
- 44 Beam
- 45 Legacy Data
- 46 Batch vs Stream
- 47 Sharing Models
