planetscale / planetscale/vtprotobuf
Performance regression for int32 and sfixed32 lists
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- Dominant language
- Go
- Stars
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Description
While benchmarking vtprotobuf in our projects, we noticed a performance regression in case of lists of int32 and sfixed32 numbers.
Marshaling and unmarshaling both seem to be slower with vtprotobuf in case of repeated int32 fields.
Although unmarshaling is faster with vtprotobuf for repeated sfixed32, marshaling is slower.
This repository contains samples of these microbenchmarks: https://github.com/themreza/vtprotobuf-bench/tree/main
What could be causing this? Is there a way to improve the performance?
It would be helpful to have automated benchmarks for different data types comparing vtprotobuf with the built-in proto.Marshal and proto.Unmarshal.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the microbenchmarks in the linked vtprotobuf-bench repository and compare vtprotobuf with the built-in proto.Marshal and proto.Unmarshal for repeated int32 and sfixed32 fields. Inspect the generated marshaling and unmarshaling behavior, then consider the issue done when the regression is explained, performance is improved where possible, and automated benchmarks cover the data types.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- go
- Domain
- performance, tooling
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100