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AI-200 Data Management Services And Vector Search Practice Question

You are designing a data architecture on Azure where embeddings are generated offline by an Azure Databricks pipeline and stored in Azure AI Search. You want to minimize ingestion latency and optimize throughput when uploading millions of pre-computed vectors. Which client library API pattern should you use?

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

Use SearchClient batch upload APIs with up to 1000 documents per batch

When uploading large batches of documents containing pre-computed vectors to Azure AI Search, using the SearchClient.UploadDocumentsBatch (or mergeOrUpload) method with batched payloads of up to 1000 documents maximizes throughput.

Answer analysis

Option-by-option breakdown

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

  • Use SearchClient batch upload APIs with up to 1000 documents per batch

    Why this is correct

    Batching documents up to the 1000-document limit maximizes indexing throughput in Azure AI Search.

  • Stream vectors directly through the Azure AI Search integrated vectorizer skillset

    Why it's wrong here

    Integrated vectorization is designed for raw text ingestion where the search service generates embeddings; pre-computed embeddings should be uploaded directly via batch APIs.

  • Send documents one-by-one using synchronous CreateOrUpdate API calls

    Why it's wrong here

    Single-document synchronous calls create severe network overhead and throttle ingestion performance.

  • Execute direct SQL INSERT statements against the underlying search partition nodes

    Why it's wrong here

    Direct SQL access to search nodes is not supported; interaction must occur through the Azure AI Search REST or SDK client APIs.

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Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Microsoft exam blueprint

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