Kuntalthakur01/Efficient-Query-Processing-on-Distributed-Systems-
View on GitHub ↗Related repositories →Designed a scalable ETL pipeline using Docker, Neo4j, Kafka, Hadoop, and Kubernetes to process 1.5B+ rows (~50GB). Configured Minikube for Kubernetes orchestration, optimizing resource allocation & latency. Utilized Spark & MapReduce for high-throughput data filtering, enabling efficient analytics.
active 2025-03-01 → 2025-03-01 (UTC)
Activity over time
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Line chart, 1 days from 2025-03-01 to 2025-03-01. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| Kuntalthakur01 | 2 | 2 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.