Handling of DSG station data for big datasets
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 150
- Forks
- 23
- Avg merge
- 1d 11h
- Merged PRs (30d)
- 2
Description
This is just to keep record of enhancements regarding the handling of station data for big datasets. As use case it is proposed that cf-python can handle a DSG dataset stored in contiguous ragged array format with +100_000 stations and more than 1 billion observations (see https://github.com/zequihg50/ghcnd-dsg).
An in-memory cache of the start and end dates registered for each station is trivial to obtain in this format, assuming that for each station the time series is sorted in disk. This allows to avoid several reading from the file for stations that actually do not contain data when subspacing in time, the slowest kind of access.
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
No files, tests, or entry points are identified. Start by reviewing cf-python's existing handling of contiguous ragged-array station data and the ghcnd-dsg use case, then establish how support for more than 100,000 stations and 1 billion observations would be validated, including the proposed date-range cache behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100