Track performance over time
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- Dominant language
- C++
- Stars
- 3.1k
- Forks
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- PR merge metrics
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Description
Come up with a reasonably representative set of test loads and monitor how quickly or slowly different versions of tippecanoe can tile them.
The tricky part will be tracking how performance degrades when data is too large to fit in memory. This should separately track:
- large numbers of features
- smaller number of features, but more geometrically complex
- large numbers of attributes
- smaller numbers of attributes, but with less duplication between them
cc @aaronlidman
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 by defining representative test loads for feature count, geometric complexity, attribute count, and attribute duplication, then determine how to compare tiling speed across tippecanoe versions. Pay particular attention to cases where data exceeds memory. Done means performance results are tracked separately for each requested workload category.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- performance, testing-qa
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100