Our trainers are industry veterans who work alongside the original creators of Apache Flink. We know how to help you. Our trainers work with Flink users every day, and have helped hundreds get started. Our curriculum is comprehensive, and updated for each new release of the platform.
This course is a hands-on introduction to Apache Flink for Java and Scala developers who want to learn to build streaming applications.
After taking this course you will have learned enough about Flink's core concepts, its DataStream API, and its distributed runtime to be able to develop solutions for a wide variety of use cases, including data pipelines and ETL jobs, streaming analytics, and event-driven applications.
The programming exercises are oriented around common use cases, and will give you a chance to see how the pieces of the API work together to solve real problems.
Introduction to Stream Processing and Apache Flink
Runtime Architecture
Foundations of the DataStream API
Data Pipelines and Stateful Stream Processing
Event Time and Watermarks
Process Functions, Side Outputs, and Timers
Windows and Streaming Analytics
State Backends
Fault Tolerance
Connector Ecosystem
Application Evolution: Rescaling, Upgrades, State Migration
Intro to Flink SQL and the Table API
Use Cases and Application Patterns
Testing
No prior knowledge of Apache Flink is required.
For the hands-on exercises you will need a computer with at least 8 GB RAM (MacOS, Linux, or Windows), with these tools installed:
Git
Java 8 or 11 JDK (a JRE is not sufficient)
An IDE for Java (or Scala) development
Docker
As a remote, instructor-led training, this is delivered as three sessions, each about 3 hours long, with the hands-on exercises assigned as homework to be done outside of class.
This course is a hands-on introduction to key topics relating to putting Flink applications into production, including configuring and tuning your job, deployment, operations, and maintenance. Also included is a solid introduction to the organization of the Flink runtime to help you tune and troubleshoot your applications. The exercises provide a hands-on introduction to these same topics.
The intended audience includes both developers and operations staff.
Intro to Flink and its Runtime Architecture
State Backends
Metrics, Monitoring, and Alerting
Troubleshooting Watermarks
Troubleshooting Backpressure
Optimizing Latency and Throughput
Fault Tolerance, Tuning and Troubleshooting Checkpointing
Managing Flink: the CLI, WebUI, and REST API
Deploying Flink
Scaling State (RocksDB, state TTL)
Debugging job failures
Troubleshooting watermarks
Tuning for latency
Tuning for throughput
Troubleshooting checkpoints
Hands-on with the CLI and Web UI
In order to make the most of this training, you should already have a general understanding of event time and watermarking, and some familiarity with the DataStream API. The troubleshooting exercises require recognizing what the provided applications are doing wrong, and adjusting the configuration and/or the code so that they perform better.
For the hands-on exercises you will need a computer with at least 8 GB RAM (MacOS, Linux, or Windows), with these tools installed:
Git
Java 8 or 11 JDK (a JRE is not sufficient)
An IDE for Java development
Docker
As a remote, instructor-led training, this is delivered in two 3-hour sessions, with hands-on exercises assigned as homework to be done outside of class.
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