Implement knowledge mining and information extraction solutions →hardMultiple ChoiceObjective-mapped

AI-102 Practice Question: Implement knowledge mining and information extraction solutions

Exhibit

Refer to the exhibit.
{
    "@odata.context": "https://mysearch.search.windows.net/$metadata#indexers/$entity",
    "name": "blob-indexer",
    "dataSourceName": "blob-datasource",
    "targetIndexName": "myindex",
    "skillsetName": "my-skillset",
    "schedule": {
        "interval": "PT1H",
        "startTime": "2025-01-01T00:00:00Z"
    },
    "parameters": {
        "batchSize": 10,
        "maxFailedItems": 5,
        "maxFailedItemsPerBatch": 2
    },
    "fieldMappings": [],
    "outputFieldMappings": [],
    "status": "running"
}

You have the above indexer configuration. The indexer processes a batch of 10 documents. In that batch, 3 documents fail. What happens?

⚠ Common exam trap

A common mix-up: candidates assume individual document failures are silently skipped (Option A) or that any failure stops the entire indexer (Option B), but the actual behavior depends on the configurable 'maxFailedItems' and 'maxFailedItemsPerBatch' thresholds, which cause the batch to fail but allow the indexer to continue if cumulative failures are within limits.

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

✓

The indexer fails the entire batch but continues with the next batch.

Azure AI Search indexers use a batch-level failure policy: if the number of failed documents in a batch exceeds the configured 'maxFailedItems' threshold (default 0), the entire batch is marked as failed and skipped, but the indexer continues processing subsequent batches. This behavior is controlled by the indexer's 'maxFailedItems' and 'maxFailedItemsPerBatch' properties, which default to 0, meaning any failure in a batch causes the batch to be skipped while the indexer moves on.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
The indexer skips the failed documents and continues with the same batch.
Why it's wrong here
The per-batch limit stops the entire batch, not skip individual documents.
✗
The indexer stops completely because 3 documents failed.
Why it's wrong here
The per-batch limit is 2, so the batch fails but the indexer can continue.
✗
The indexer retries the failed documents.
Why it's wrong here
No automatic retry of failed documents within the same batch.
✓
The indexer fails the entire batch but continues with the next batch.
Why this is correct
maxFailedItemsPerBatch=2 causes the batch to abort; overall limit of 5 allows subsequent batches.

Go deeper

AI-102 Practice Question: Implement knowledge mining and information extraction solutions

Exhibit

Why each option matters

Option-by-option breakdown

Related to this question