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

Exhibit

Refer to the exhibit.

{
  "$schema": "https://schemas.microsoft.com/azure/cosmosdb/2019-08-01",
  "datasources": [
    {
      "name": "my-cosmosdb",
      "type": "cosmosdb",
      "credentials": { "connectionString": "AccountEndpoint=https://mycosmos.documents.azure.com:443/;AccountKey=...;" },
      "container": { "name": "mycontainer", "query": "SELECT c.id, c.title, c.content FROM c WHERE c._ts > @HighWaterMark ORDER BY c._ts" }
    }
  ]
}

You have configured an Azure AI Search indexer with a Cosmos DB data source as shown in the exhibit. The indexer runs successfully, but you notice that the index is missing some documents that were recently added to Cosmos DB. What is the most likely cause?

⚠ Common exam trap

Many candidates assume the indexer must be failing entirely or that a configuration error is obvious, but the question describes a successful run with missing documents, which points to a subtle change tracking issue rather than a connectivity or schema mismatch.

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 high water mark is not being updated correctly, causing some documents to be skipped.

The most likely cause is that the high water mark (the _ts value) is not being updated correctly, causing the indexer to skip documents that were recently added. Azure AI Search uses a high water mark strategy to track changes from Cosmos DB, and if the _ts value is not properly recorded or the indexer's change tracking logic fails, new documents may be missed even though the indexer runs successfully.

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 is not configured to track changes using _ts.
Why it's wrong here
The query uses _ts, so change tracking is enabled.
✗
The container name is misspelled.
Why it's wrong here
If misspelled, the indexer would fail.
✓
The high water mark is not being updated correctly, causing some documents to be skipped.
Why this is correct
If the high water mark is not updated, documents with _ts <= high water mark are skipped.
✗
The query does not select all fields required by the index.
Why it's wrong here
Missing fields would cause indexing errors, not missing documents.

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