Question 950 of 988

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

Quick Answer

The answer is that the indexer fails the entire batch but continues processing the next batch. This occurs because the maxFailedItemsPerBatch parameter is set to 2, and with 3 failed documents in a batch of 10, the threshold is exceeded, causing the entire batch to be marked as failed. However, the indexer does not stop overall execution unless the global maxFailedItems limit of 5 is also surpassed, which it is not in this scenario. On the Microsoft Azure AI Engineer Associate AI-102 exam, this concept tests your understanding of how Azure Cognitive Search indexers handle partial failures during batch processing, a common scenario when dealing with malformed or incompatible source data. A frequent trap is assuming that a single batch failure halts the entire indexing job, but the key distinction is between per-batch and overall failure limits. Remember the mnemonic: “Two per batch, five overall—three fails the batch, but the indexer still rolls.”

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

This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

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?

Question 1hardmultiple choice

Full question →

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"
}

A
The indexer skips the failed documents and continues with the same batch.
Why wrong: The per-batch limit stops the entire batch, not skip individual documents.
B
The indexer stops completely because 3 documents failed.
Why wrong: The per-batch limit is 2, so the batch fails but the indexer can continue.
C
The indexer retries the failed documents.
Why wrong: No automatic retry of failed documents within the same batch.
D
The indexer fails the entire batch but continues with the next batch.
maxFailedItemsPerBatch=2 causes the batch to abort; overall limit of 5 allows subsequent batches.

Full breakdown with real-world context →

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.

The indexer allows up to 2 failed items per batch (maxFailedItemsPerBatch=2). Since 3 > 2, the entire batch fails. The indexer continues with the next batch if maxFailedItems (overall) is not exceeded. In this case, overall maxFailedItems is 5, so the indexer continues overall.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

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.
Related concept
Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Detailed technical explanation

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

KKey Concepts to Remember

Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.

TExam Day Tips

Underline the problem statement mentally.
Watch for words such as best, first, most likely and least administrative effort.
Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

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FAQ

Questions learners often ask

What does this AI-102 question test?

Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: The indexer fails the entire batch but continues with the next batch. — The indexer allows up to 2 failed items per batch (maxFailedItemsPerBatch=2). Since 3 > 2, the entire batch fails. The indexer continues with the next batch if maxFailedItems (overall) is not exceeded. In this case, overall maxFailedItems is 5, so the indexer continues overall.

What should I do if I get this AI-102 question wrong?

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

About these practice questions

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Last reviewed: Jun 20, 2026

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