📅 2025-01-27 — Session: Resolved MongoDB Query and Sorting Issues

🕒 16:10–16:50
🏷️ Labels: Mongodb, Debugging, Data Processing, Flask, API
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to address and resolve various issues related to MongoDB queries, including sorting, document existence checks, and schema mismatches.

Key Activities

  • Implemented a Python code snippet using pymongo to retrieve the last few elements from task_processed_collection, focusing on sorting by the processed_at field.
  • Explored methods to check document existence using updated MongoDB queries.
  • Diagnosed missing fields in collections, identifying reasons for None values and providing diagnostic steps.
  • Debugged schema mismatches in task_processed_emails, focusing on data ingestion and query logic.
  • Refined query logic for processed_at timestamps to ensure correct retrieval of recent entries.
  • Updated Flask API endpoint to sort documents by processed_at instead of received_at.
  • Reflected on job execution patterns integrating Google Sheets with MongoDB, noting insights and warnings.

Achievements

  • Successfully resolved sorting issues in MongoDB queries, ensuring accurate retrieval of recent documents.
  • Updated Flask API endpoint for improved data retrieval.
  • Gained insights into data processing workflows and identified areas for improvement.

Pending Tasks

  • Further testing of updated MongoDB queries and Flask API to ensure robustness and efficiency.
  • Continuous monitoring of data integrity and ingestion processes to prevent future schema mismatches.