NVIDIA-NeMo / NVIDIA-NeMo/Curator

Potential Improvements to CC download & Extract Stage

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enhancement
Dominant language
Python
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Forks
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Avg merge
4d 5h
Merged PRs (30d)
30

Description

Is your feature request related to a problem? Please describe.
The CC download and extract can have better user experience (and potentially be made faster). Here are a list of things that can be explored:

  • Add retry logic to download #1225
  • Retry logic for url generation/saving CC url's? Ran into a timeout from CC trying to get URL's. If they've already been pulled they can potentially be saved someplace to retrieve later?
  • Support saving CC downloads to cloud sources. Each snapshot can be 80-100TiB in size and is difficult to store locally #779.
  • Explore row level parallelism for extraction. Each core/CPU extracts all rows for a warc file serially. This needs to be explored further but there are often some rows that may take a much longer time to extract than others (deeply nested html files). Extracting at a row level might help get the best performance from extract which is relatively slow.
  • Limit Download concurrency for Ray-Data

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Describe alternatives you've considered
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Additional context
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Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the Common Crawl download and extraction pipeline, including the Ray-Data entry points mentioned in the issue. Review the existing download, URL-generation, cloud-storage, extraction, and concurrency behavior before narrowing this broad list to one scoped improvement. Done should mean that the selected behavior is implemented and its performance or retry/concurrency outcome is verified.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
cloud, data-engineering, distributed-systems
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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