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1
Introduction
2
Welcome
3
About For Very Good
4
Recap
5
Quest for Data
6
Everything is a Stream
7
String Processing
8
Apache Flink
9
Flink Users
10
String Processing Use Cases
11
Streaming Analytics Use Cases
12
Stateful Serverless Applications
13
Companies using Flink
14
Alibaba
15
You Hopper
16
What makes Flink different
17
Flink API Stack
18
Your Code
19
Distributed Systems
20
State Fault Tolerance
21
Checkpointing
22
Safe Points
23
Time
24
Event Time
25
Processing Time
26
Summary
27
Flink on Kubernetes
28
Questions
29
Experience with Flink
30
What does Flink help with
31
What other events or adapters do you have
32
Are there any advantages performance or otherwise
33
Mix and match
34
Python
Description:
Explore the fundamentals of stream processing and Apache Flink in this 56-minute conference talk by Marta Paes Moreira. Dive into the evolution of stream processing from real-time applications to a unified paradigm for distributed data processing. Learn about Flink's flexible APIs, powerful execution model, and its adoption by major companies like Alibaba, Netflix, Uber, and Yelp. Discover key concepts such as state, time, and the building blocks that make Flink a resilient and versatile option for stateful stream processing. Examine Flink's competitive edge over similar frameworks, its API stack, and how it handles distributed systems, fault tolerance, and checkpointing. Gain insights into Flink's applications in streaming analytics, stateful serverless applications, and its deployment on Kubernetes. Engage with questions about Flink's advantages, performance, and integration with other technologies, including Python support.

Introduction to Stream Processing with Apache Flink

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