Update `api-server` to load a large point-cloud dataset for the pip viewport culling demo.
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- Dominant language
- TypeScript
- Stars
- 211
- Forks
- 29
- Avg merge
- 17h 30m
- Merged PRs (30d)
- 1
Description
api-server needs to provide one or more endpoints that enable a user, via the HTTP api, to specify a datafile, load it with GPU I/O into a column, and then serialize the column over arrow to a caller. I'd prefer to use a generic API that lets any @rapidsai/cudf API call to be used.
- Find a good dataset for the particles demo.
- Create an
api-serverendpoint that loads the file using one or more@rapidsai/cudfcommands, all visible on the HTTP api. - Create an
api-serverendpoint that lets the user reflect on data that has been loaded onto the GPU process. - Create an
api-serverendpoint that streams the loaded data specified by the user to a client via arrow.
Contributor guide
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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 locating the api-server entry point and reviewing the existing HTTP API surface. Check the @rapidsai/cudf loading, reflection, and Arrow streaming endpoints described in the issue, and confirm that a caller can select a datafile, inspect GPU-loaded data, and receive the loaded column.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- nodejs, typescript
- Domain
- api, backend, data
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100