Overview
Syllabus
Intro
Riley Report
Context
Hadoop Classic
Hadoop Architecture
Time vs Money
Streaming Data Architecture
Streaming Engines
Latency Requirements
RealTime
Latency
Windowing
Machine Learning
Batch Jobs
Volume
HighScale Problems
Partitioning Data
Integration
Sequels
Spark vs Kafka
Dynamic ML
Event Processing
Individual Event Processing
Google Stream Processing
Apache Beam
Stream Processing
Flink
akkaStreams
KafkaStreams
Spark
Lambda
Microservices and Fast Data
Microservices
Single Responsibility
Micro Services
Reactive Programming
Twitter
Big Data vs Microservices
Light Ben
Merging streams
Runner
Storm
Knife
Beam
Legacy Data
Batch vs Stream
Sharing Models
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GOTO Conferences