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Evaluating the Performance Impact of Bazel's Parallelization and Incremental Build Features in Continuous Integration


Core Concepts
Bazel's parallelization and incremental build features can significantly speed up long-duration builds in continuous integration, but their adoption and effectiveness vary across open-source projects.
Abstract
The study investigates the usage and performance impact of Bazel's parallelization and incremental build features in continuous integration (CI) builds. Key highlights: 31.23% of Bazel projects adopt a CI service but do not use Bazel in the CI service, as Bazel is adopted for other purposes beyond just building projects. For projects that use Bazel in CI, 26.36% of them use additional tools like Shell scripts, Make, and Docker to facilitate the execution of Bazel. All studied Bazel projects in the 4 CI services (GitHub Actions, CircleCI, Travis CI, Buildkite) use Bazel's parallel build feature, but only 44.08% of them use caching to speed up build performance. Bazel's parallelization can significantly improve the build performance for long-build duration projects, with median speedups of 2.00x, 3.84x, 7.36x, and 12.80x at parallelism degrees 2, 4, 8, and 16, respectively. However, at parallelism degree 16, 100% of short, 96% of medium, and 83% of long-build duration projects are unable to fully harness the benefits of parallelism. Caching of build dependencies in CI can slow down builds, with only 52.17% of short, 8.70% of medium, and 4.17% of long-build duration projects exhibiting improved build performance compared to clean builds. Caching of build results (incremental build) can greatly help reduce the build time for medium- and long-build duration projects, with median speedups of 1.21x-1.25x and 4.22x-4.71x, respectively. The results provide guidance for developers to improve the usage of Bazel in their projects and emphasize the importance of exploring modern build systems due to their potential advantages within contemporary software practices.
Stats
The median baseline build times for short-build duration projects are 44.74s, 253.41s, and 108.88s. The median baseline build times for medium-build duration projects are 258.21s, 850.49s, and 467.78s. The median baseline build times for long-build duration projects are 935.84s, 14836.71s, and 1801.53s.
Quotes
"Bazel's parallelization can significantly improve the build performance for long-build duration projects, with median speedups of 2.00x, 3.84x, 7.36x, and 12.80x at parallelism degrees 2, 4, 8, and 16, respectively." "Caching of build results (incremental build) can greatly help reduce the build time for medium- and long-build duration projects, with median speedups of 1.21x-1.25x and 4.22x-4.71x, respectively."

Key Insights Distilled From

by Shenyu Zheng... at arxiv.org 05-03-2024

https://arxiv.org/pdf/2405.00796.pdf
Does Using Bazel Help Speed Up Continuous Integration Builds?

Deeper Inquiries

How can the adoption and usage of Bazel's parallelization and incremental build features be further improved in open-source projects?

To enhance the adoption and utilization of Bazel's parallelization and incremental build features in open-source projects, several strategies can be implemented: Education and Training: Providing comprehensive documentation, tutorials, and training sessions on how to effectively use Bazel's parallelization and incremental build features can help developers understand the benefits and best practices. Integration with CI/CD Pipelines: Integrate Bazel seamlessly into Continuous Integration/Continuous Deployment (CI/CD) pipelines to automate the build process and ensure that parallelization and incremental build features are utilized consistently. Community Support: Foster a strong community around Bazel to encourage knowledge sharing, collaboration, and the exchange of best practices for optimizing parallelization and incremental builds. Tooling and Plugins: Develop tools and plugins that enhance the visibility and control over parallelization and incremental build processes within Bazel, making it easier for developers to leverage these features effectively. Performance Monitoring: Implement monitoring and analytics tools to track the performance of parallel builds and incremental builds, allowing developers to identify bottlenecks and optimize their usage of Bazel's features.

What are the potential drawbacks or trade-offs of using Bazel compared to traditional build systems that developers should consider?

While Bazel offers significant advantages in terms of parallelization and incremental builds, developers should also be aware of the potential drawbacks and trade-offs: Learning Curve: Bazel has a steeper learning curve compared to traditional build systems like Maven, requiring developers to invest time in understanding its unique concepts and configuration. Maintenance Overhead: Bazel's advanced features may require more maintenance and configuration compared to traditional build systems, potentially increasing the complexity of the build process. Compatibility Issues: Bazel's strict dependency management and build rules may lead to compatibility issues with existing projects or third-party libraries that are not designed to work with Bazel. Resource Intensive: Bazel's parallelization features can be resource-intensive, requiring sufficient computing power and infrastructure to fully leverage its capabilities. Tool Ecosystem: Bazel's ecosystem of plugins and tools may not be as extensive as that of traditional build systems, limiting the availability of additional features and integrations.

How can the structure and granularity of the Bazel dependency graph be optimized to better leverage the parallelization and incremental build features?

To optimize the structure and granularity of the Bazel dependency graph for improved parallelization and incremental build features utilization, the following strategies can be implemented: Modularization: Break down projects into smaller, more modular components to reduce interdependencies and improve parallelization efficiency. Dependency Management: Ensure that dependencies are well-defined and minimized to reduce unnecessary rebuilds and improve incremental build performance. Target Granularity: Define fine-grained build targets to allow for more precise parallelization and incremental build optimizations, focusing on specific components rather than entire projects. Dependency Analysis Tools: Utilize tools and plugins that analyze the dependency graph of Bazel projects to identify potential bottlenecks, circular dependencies, or inefficiencies that hinder parallelization and incremental builds. Regular Maintenance: Regularly review and optimize the structure of the Bazel dependency graph to adapt to changes in project requirements, dependencies, and build processes, ensuring optimal performance.
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