Indexing code at scale with Glean

We’re sharing details about Glean, Meta’s open source system for collecting, deriving, and working with facts about source code. In this blog post we’ll talk about why a system like Glean is import…

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Meta
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Simon Marlow
•14 min read•advanced•
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Overview

The article discusses Glean, Meta's open-source code indexing system designed to efficiently collect and manage information about source code. It highlights Glean's architecture, its query language Angle, and various applications that enhance developer tools, particularly in large codebases.

What You'll Learn

1

How to use Glean for efficient code indexing in large projects

2

Why incremental indexing is crucial for maintaining up-to-date code information

3

How to implement the Angle query language for custom code queries

Prerequisites & Requirements

  • Understanding of code indexing concepts
  • Familiarity with developer tools and IDEs(optional)

Key Questions Answered

What is Glean and how does it enhance code indexing?
Glean is an open-source code indexing system developed by Meta that collects and manages information about source code efficiently. It supports a flexible query language called Angle, enabling developers to access detailed code information quickly, which is particularly beneficial for large codebases.
How does Glean's incremental indexing work?
Glean's incremental indexing processes only the changes made to the codebase rather than re-indexing the entire repository. This approach reduces the indexing time complexity to O(changes), allowing developers to access up-to-date information without the delays associated with full repository indexing.
What are the advantages of using Glean for code navigation?
Using Glean for code navigation provides instant access to code references across large monorepos, full repository visibility, and the ability to navigate across different programming languages. This enhances the developer experience by allowing quick access to definitions and references without waiting for IDE initialization.
How does Glean support documentation generation?
Glean collects detailed API data and documentation strings from the source code, allowing for automatic generation of documentation on demand. This ensures that documentation is consistent and up-to-date, facilitating better understanding and usage of APIs across different programming languages.

Technologies & Tools

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Backend
Glean
Used for collecting and indexing code information.
Query Language
Angle
A declarative logic-based query language for querying indexed data.
Database
Rocksdb
Used for storing indexed data efficiently.

Key Actionable Insights

1
Implement Glean in your development workflow to enhance code indexing and navigation.
By integrating Glean, teams can improve their ability to navigate large codebases quickly, reducing the time spent searching for code definitions and references.
2
Utilize the Angle query language to create custom queries tailored to your project's needs.
This flexibility allows developers to extract specific information from the codebase, making it easier to analyze and understand complex code structures.
3
Adopt incremental indexing to keep your code information up-to-date without the overhead of full re-indexing.
This approach is particularly beneficial in dynamic environments where code changes frequently, ensuring that developers always have access to the latest information.

Common Pitfalls

1
Failing to implement a centralized indexing system can lead to redundant indexing efforts across developer machines.
Without a centralized approach, each developer may end up indexing the same code multiple times, wasting resources and time. A shared indexing system like Glean avoids this redundancy.

Related Concepts

Code Indexing
Query Languages
API Documentation
Incremental Indexing