Resolved MongoDB Query and Sorting Issues

• Day: 2025-01-27
• Time: 16:10 to 16:50
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Mongodb, Debugging, Data Processing, Flask, API

Description

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.

Evidence

• source_file=2025-01-27.sessions.jsonl, line_number=6, event_count=0, session_id=f9c5b89ce70a1e17b2cbbe5b860f69f4a756260b2551c6711b4d09680bde73d9
• event_ids: []