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Apache Flink

8h 31m 38s
English
Paid

Course description

Apache Flink is a distributed system and computational engine for stateful big data streaming. That was a mouthful. In plain English, Flink is an library that allows you to process big data at scale, as it arrives, in almost real time. Flink gives you a variety of APIs that allow you to do plain functional programming on streaming data, and low-level APIs to give you ultimate control. Plus connectors to everything popular, including Kafka, JDBC, Cassandra, Pulsar, S3 and all sorts of data processors and storage systems. In this course, you'll learn how to be productive with Flink, and you'll grow as a data engineer.

Read more about the course

First of all, this course will give you everything you need to be productive with Flink:

  • You'll deeply understand the Flink streaming engine and how it works
  • You'll use functional programming on data streams
  • You'll process any kind of data in real time, at scale
  • You'll master complex transformations such as window functions
  • You'll be able to run stateful computations, which is the main strength of Flink
  • You'll know how to connect Flink to the most popular message buses, data streaming and data storage systems
  • You'll be able to design your own connectors
  • You'll be able to deploy Flink applications to a cluster
  • You'll be able to troubleshoot and find relevant information in the Flink UI

After this course, you'll be able to process data in any way you need using Flink.

But most importantly, you'll develop timeless skills that you'll carry with you for your entire career, regardless of which data streaming tool you'll end up using:

  • You'll deeply understand the practical benefits of streaming data in general
  • You'll be able to work with event time and processing time
  • You'll internalize the implications and tradeoffs of choosing latency vs throughput
  • You'll understand the need for data consistency and persistence

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#1: Welcome

All Course Lessons (30)

#Lesson TitleDurationAccess
1
Welcome Demo
11:59
2
Scala Recap
31:05
3
Flink: First Principles
16:42
4
DataStreams
14:15
5
DataStreams: Exercise
15:07
6
DataStreams: Explicit Transformations
14:57
7
Handling Late Data: Watermarks
05:22
8
Window Functions
28:56
9
Window Functions, Part 2
26:33
10
Window Functions: Exercise
12:48
11
Time Based Transformations
33:15
12
Triggers
16:38
13
Handling Multiple Streams
33:36
14
Partitions
14:33
15
State First Principles
03:55
16
Rich Functions
22:05
17
Keyed State
24:10
18
Keyed State, Part 2
19:21
19
Checkpoints
20:16
20
Broadcast State
18:35
21
Integrations: Kafka
25:07
22
Integrations: JDBC
12:11
23
Integrations: Cassandra
09:44
24
Custom Sources
24:11
25
Custom Sinks
16:47
26
Side Outputs
08:07
27
How Flink Runs on a Cluster
07:17
28
Managing and Submitting Applications
13:48
29
Managing Applications in the Flink UI
09:47
30
You Rock!
00:31

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