[discussion] High connect latency for wide tables
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 45/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Quiet
- Domain
- frontend, performance
Research direction
No files or tests are named. Trace the dataset-loading path and the wide-table UI entry point first, then determine how column selection or exclusion can be represented before loading; done means users can choose the columns they need and wide tables no longer load every column by default.
Written by the indexing model from the issue text.
Description
Hi team, IIRC, in the current implementation, for all the provided dataset, we load all its columns by default.
For a wide table, say, with over 1K columns, it leads to high latency and unfriendly UI (I have to scroll to the very right side to find the columns I care about).
So I'm wondering if it's possible to get users select / exclude the columns they're (un)interested in, so we don't need to read and load every single column?
- Dominant language
- Python
- Stars
- 65
- Forks
- 8
- PR merge metrics
- No merged PRs in 30d
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
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First steps
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