Getting Started

This page summarizes the basic steps required to setup and get started with PyFlink.

There are live notebooks where you can try PyFlink out without any other step:

• Live Notebook: Table

• Live Notebook: DataStream

The list below is the contents of this quickstart page:

• Installation
  • Preparation
    • Python Version Supported
    • Create a Python virtual environment
      • Create a virtual environment using virtualenv
      • Create a virtual environment using conda
    • Install PyFlink
      • Installing using PyPI
      • Installing from Source
    • Check the installed package
  • Local
    • Set up Python environment
    • Execute PyFlink jobs in terminal
    • Execute PyFlink jobs in IDE
  • Standalone
    • Set up Python environment
    • Submit PyFlink jobs to a standalone Flink cluster
  • YARN
    • Set up Python environment
    • Submit PyFlink jobs to YARN cluster
  • Kubernetes
    • Build PyFlink Image
    • Execute PyFlink jobs in application mode with Native Kubernetes
    • Execute PyFlink jobs in session mode with Native Kubernetes
    • Execute PyFlink jobs with Flink Kubernetes Operator
• QuickStart
  • QuickStart: Table API
    • TableEnvironment Creation
    • Table Creation
    • Viewing Data on Table
    • Selecting and Accessing Data on Table
    • Applying a Function on Table
    • Emits Results of Table
  • QuickStart: DataStream API
    • StreamExecutionEnvironment Creation
    • DataStream Creation
    • Viewing Data on DataStream
    • Applying a Function on DataStream
    • Emits Results of DataStream