Welcome to the Dataflow Developer Guide! This document provides an overview of Google Cloud Dataflow, a fully managed service for executing Apache Beam programs that processes large volumes of data in streaming or batch modes.

Key Concepts

  • Apache Beam: An open-source unified model for batch and streaming data processing.
  • Dataflow: A fully managed service that executes Apache Beam programs.
  • Streaming: Process data in real-time as it arrives.
  • Batch: Process data in batches at scheduled intervals.

Getting Started

To get started with Dataflow, you'll need to:

  1. Create a Google Cloud account
  2. Set up your project
  3. Install the Dataflow SDK

Use Cases

  • Event Processing: Real-time analytics and insights from event streams.
  • Machine Learning: Preprocess and transform data for machine learning models.
  • Data Integration: Combine data from various sources and formats.

Best Practices

  • Use Watermarks for Event Time: Ensure accurate event time processing in your pipelines.
  • Optimize Your Pipeline: Profile and optimize your pipeline for performance.
  • Monitor Your Jobs: Use Cloud Monitoring to track the health and performance of your Dataflow jobs.

Resources

Dataflow Architecture

Learn more about the architecture of Dataflow to understand how it processes data.