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airscholar/RedditDataEngineering

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This project provides a comprehensive data pipeline solution to extract, transform, and load (ETL) Reddit data into a Redshift data warehouse. The pipeline leverages a combination of tools and services including Apache Airflow, Celery, PostgreSQL, Amazon S3, AWS Glue, Amazon Athena.

active 2023-10-23 → 2026-07-22 (UTC)

Complete coverage27,457 / 27,457 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-02 (UTC)
Events
260
Pushes
0
Pull requests
2
Issues
2
Stars
166
Forks
88

Activity over time

Daily event counts in the loaded window

Line chart, 1004 days from 2023-10-23 to 2026-07-22. Pushes: 0 total, peak 0 in a day. Pull requests: 2 total, peak 1 in a day. Issues: 2 total, peak 1 in a day. Comments: 0 total, peak 0 in a day. Stars: 166 total, peak 9 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
annguyen-git2000
Barathkumar011010
shasank-periwal1010

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 166 stars here means stars gained during the window, not the repo's star count.