Implement knowledge mining and information extraction solutions →hardMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Your Azure AI Search indexer is failing to index a large number of PDFs from Azure Blob Storage. The error log shows 'Document extraction timeout' for many documents. You need to resolve this issue without losing data. What should you do?
⚠ Common exam trap
A common mix-up: candidates confuse 'indexer execution timeout' with 'document extraction timeout' and assume the solution must involve changing parsing modes or splitting files, rather than adjusting the indexer's maximum runtime.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the indexer execution timeout in the indexer definition
The 'Document extraction timeout' error indicates that the indexer is taking longer than the default 24-hour timeout to process certain PDFs. Increasing the indexer execution timeout in the indexer definition allows the indexer to continue processing these large documents without losing data, as it extends the maximum time the indexer can run for a single execution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the indexer execution timeout in the indexer definition
Why this is correct
The timeout can be increased to allow large documents to be processed.
- ✗
Change the parsing mode of the indexer to 'text'
Why it's wrong here
PDFs are already parsed as text; changing parsing mode doesn't address timeout.
- ✗
Split large PDFs into smaller files before uploading
Why it's wrong here
This requires manual effort and re-uploading; not a direct solution within the existing pipeline.
- ✗
Enable incremental enrichment on the skillset
Why it's wrong here
Incremental enrichment affects caching, not extraction timeout.
Visual reference
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.