Python examples - Managed Service for Apache Flink

Amazon Managed Service for Apache Flink was previously known as Amazon Kinesis Data Analytics for Apache Flink.

Python examples

The following examples demonstrate how to create applications written in Python.

Note

Most of the examples are designed to run both locally, on your development machine and your IDE of choice, and on Amazon Managed Service for Apache Flink. They demonstrate the simple mechanism that you can use to pass application parameters, and how to set the dependency correctly to run the application in both environments with no changes.

Project dependencies

Most PyFlink examples require one or more dependencies in the form of JAR files, for example for Flink connectors. These dependencies must then be packaged with the application when deployed on Amazon Managed Service for Apache Flink.

The following examples already include the tooling that lets you run the application locally for development and testing, and to package the required dependencies correctly. This tooling requires using Java JDK11 and Apache Maven. Refer to the README contained in each example for the specific instructions.

Examples

This example demonstrates the basic structure of a PyFlink application using SQL embedded in Pyton code. This project also provides a skeleton for any PyFlink application that includes JAR dependencies such as connectors. The README section provides detailed guidance about how to run your Python application locally for development. The example also shows how to include a single JAR dependency, the Kinesis SQL connector in this example, in your PyFlink application.

Code example: GettingStarted

This example demonstrates four types of the windowing aggregation in SQL embedded in a Python application.

  1. Sliding Window based on processing time

  2. Sliding Window based on event time

  3. Tumbling Window based on processing time

  4. Tumbling Window based on event time

Code example: Windowing

This example shows how to write your output to Amazon S3 as JSON files, using SQL embedded in a Python application. You must enable checkpointing for the S3 sink to write and rotate files to Amazon S3.

Code example: S3Sink

This example demonstrates how to define a User Defined Funtion, implement it in Python, and use it in SQL code that runs in a Python application.

Code example: UDF

This example demonstrates how to send data to Amazon Data Firehose using SQL.

Code example: FirehoseSink