Efficient Counselor Matchmaking with PySpark and Redis WorkflowEfficient Counselor Matchmaking with PySpark and Redis Workflow
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Problem: Users needed a faster way to find the most relevant counselor based on specialization and available data.
Solution: Built a recommendation workflow using PySpark for data processing and Redis for fast lookup and recommendation serving.
Tools: Python, PySpark, Redis, Docker, Docker Compose
Result: Created a containerized recommendation system that processes counselor data and returns relevant matches efficiently.
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The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started