Exploring KotlinX Benchmark Results with Kotlin Notebooks
Article Summary
Filipp Zhinkin and Teodor Irkhin from JetBrains show how staring at raw benchmark tables is costing you insights. Kotlin Notebooks turn those text dumps into interactive visualizations that actually tell a story.
The kotlinx-benchmark library is great for measuring Kotlin performance, but its text output becomes unreadable at scale. JetBrains engineers demonstrate how Kotlin Notebooks combine DataFrame API and Kandy charts to transform benchmark results into shareable, visual analysis.
Key Takeaways
- Load kotlinx-benchmark JSON directly into typed DataFrames for structured analysis
- Visualize performance differences across implementations and hardware with Kandy charts
- Compare results statistically using confidence intervals, not just raw numbers
- Share findings via GitHub gists, Datalore, or commit notebooks for reproducible tracking
Kotlin Notebooks transform kotlinx-benchmark's text output into interactive charts and DataFrames, making performance analysis visual, shareable, and statistically rigorous.
About This Article
As kotlinx-benchmark text output grows, it becomes hard to read. Finding performance patterns across multiple test runs and different implementations takes real effort.
JetBrains engineers used Kotlin Notebooks with the DataFrame API and Kandy charting library to convert benchmark JSON files into typed, queryable data structures. The result is visual representations that are actually useful.
Teams can run the same notebook on different machines to compare performance visually between environments or commits. This makes performance tracking reproducible. They can share results through GitHub gists or publish to Datalore.