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Why might using joinedload() cause performance issues in some Flask SQLAlchemy queries?

hard📝 Conceptual Q10 of 15
Flask - Performance Optimization
Why might using joinedload() cause performance issues in some Flask SQLAlchemy queries?
ABecause it limits the number of records returned
BBecause it delays loading related objects until accessed
CBecause it can produce large result sets with repeated parent data due to SQL JOINs
DBecause it creates multiple separate queries
Step-by-Step Solution
Solution:

  1. Step 1: Understand joinedload behavior

    joinedload uses SQL JOINs which can duplicate parent rows when multiple related rows exist, increasing data size.

  2. Step 2: Analyze impact

    This can cause large result sets and slow performance if many related rows exist.

  3. Final Answer:

    Because it can produce large result sets with repeated parent data due to SQL JOINs -> Option C

  4. Quick Check:

    joinedload can cause large joined results = C [OK]
Quick Trick: joinedload may duplicate parent rows due to SQL JOINs [OK]
Common Mistakes:
MISTAKES
  • Confusing joinedload with lazy loading
  • Thinking joinedload limits records
  • Assuming joinedload runs multiple queries

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