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

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

Exhibit

Refer to the exhibit.

{
  "dataSource": {
    "name": "blob-datasource",
    "type": "azureblob",
    "credentials": {
      "connectionString": "DefaultEndpointsProtocol=https;AccountName=myaccount;AccountKey=...;EndpointSuffix=core.windows.net"
    },
    "container": {
      "name": "documents"
    }
  },
  "index": {
    "name": "docs-index",
    "fields": [
      {"name":"id","type":"Edm.String","key":true,"searchable":false},
      {"name":"content","type":"Edm.String","searchable":true},
      {"name":"metadata_storage_name","type":"Edm.String","searchable":true}
    ]
  },
  "indexer": {
    "name": "docs-indexer",
    "dataSourceName": "blob-datasource",
    "targetIndexName": "docs-index",
    "parameters": {
      "batchSize": 10,
      "maxFailedItems": -1
    }
  }
}

You review the configuration for an Azure AI Search indexer. The indexer runs successfully but no documents are indexed. What is the most likely cause?

⚠ Common exam trap

Watch out — candidates often assume a successful indexer run means data was indexed, but Azure AI Search can report success even when no documents are written to the index due to missing field mappings or skillset configuration.

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 does not have a skillset or field mappings to populate the 'content' field from the blob

When an Azure AI Search indexer runs successfully but indexes zero documents, the most common cause is that the indexer lacks a skillset or field mappings to extract and map the blob content (e.g., the 'content' field) into the search index. Without explicit field mappings or a skillset that defines how to populate the index fields from the blob's default properties, the indexer may complete execution without transferring any data into the index fields.

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 connection string in the data source is invalid
Why it's wrong here
The indexer runs successfully, so connection is fine.
✗
The container name is incorrect
Why it's wrong here
Indexer runs, so container exists.
✓
The indexer does not have a skillset or field mappings to populate the 'content' field from the blob
Why this is correct
Without a skillset or field mappings, the blob's content is not extracted into the content field.
✗
The maxFailedItems parameter is set to -1, which causes the indexer to skip all documents
Why it's wrong here
-1 means no limit on failed items, but indexer still indexes successful ones.

Go deeper

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

Exhibit

Why each option matters

Option-by-option breakdown

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