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DP-420 試験練習問題

Azure Cosmos DB AI Developer

DP-420 の PDF 練習問題。資料の言語は 英語です。購入はこの試験のみで、自動更新はありません。

試験概要

DP-420 は「Azure Cosmos DB AI Developer」の認定試験です。試験形式、時間、対応言語は以下をご確認ください。最新の出題範囲や受験条件は公式サイトをご参照ください。

試験コード
DP-420
公式の試験・資格名
Azure Cosmos DB AI Developer
試験形式
Proctored assessment; interactive items may be included
試験時間
100 分
受験可能な言語
英語、日本語、簡体字中国語、韓国語、ドイツ語、フランス語、スペイン語、ポルトガル語（ブラジル）、繁体字中国語、イタリア語

公式試験の対応言語と練習問題ファイルの言語は異なります。試験の版と言語は公式の予約ページでご確認ください。

公式情報： 公式サイト
情報確認日：2026-10-20

対応言語

  • 英語
  • 簡体字中国語
購入前にお試し

最初の 20 問を無料プレビュー

全 271 問

題庫の元の順序で表示します。回答欄を開くと、正解と収録されている解説を確認できます。

問題の言語：英語。問題文・選択肢・正解・解説は元の題庫の言語で表示します。

免責事項：ExamPico の問題はすべてインターネット上の情報を整理したもので、学習参考用として提供しています。

問題 16

Question#16Topic1

You have a database named db1 in an Azure Cosmos DB Core (SQL) API account.
You are designing an application that will use db1.
In db1, you are creating a new container named coll1 that will store online orders.
The following is a sample of a document that will be stored in coll1.
Question illustration
The application will have the following characteristics:
✑ New orders will be created frequently by different customers.
✑ Customers will often view their past order history.
You need to select the partition key value for coll1 to support the application. The solution must minimize costs.
To what should you set the partition key?

  1. A. orderId
  2. B. customerId
  3. C. orderDate
  4. D. id
正解と解説を表示

正解

B

解説

customerId is the optimal partition key because customers frequently view their past order history — all orders for one customer share the same partition key, enabling efficient single-partition queries with minimal RU cost. orderId would scatter each order into its own partition, making customer history queries cross-partition. orderDate creates hot partitions (all orders on the same date) and cross-partition queries for customer-specific lookups.

問題 17

Question#17Topic1

You have a container in an Azure Cosmos DB Core (SQL) API account that stores data about orders.
The following is a sample of an order document.
Question illustration
Documents are up to 2 KB.
You plan to receive one million orders daily.
Customers will frequently view their past order history.
You are the evaluating whether to use orderDate as the partition key.
What are two effects of using orderDate as the partition key? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  1. A. You will exceed the maximum number of partition key values
  2. B. You will exceed the maximum storage per partition
  3. C. There will always be a hot partition
  4. D. Queries will run cross-partition
正解と解説を表示

正解

CD

解説

Using orderDate as the partition key with 1 million orders daily causes all that day's writes to target the same logical partition, creating a persistent hot partition (C). Customer order history queries filter by customerId, not orderDate, forcing expensive cross-partition fan-out queries (D). You will not exceed maximum partition key values (A) because dates provide sufficient cardinality, and 2 KB documents alone may not immediately exceed 20 GB per partition (B) though hot-partition throttling is the primary concern.

問題 18

Question#18Topic1

You have a container in an Azure Cosmos DB Core (SQL) API account. The container stores data about families. Data about parents, children, and pets are stored as separate documents.
Each document contains the address of each family. Members of the same family share the same partition key named familyId.
You need to update the address for each member of the same family that share the same address. The solution must meet the following requirements:
✑ Be atomic, consistent, isolated, and durable (ACID).
✑ Provide the lowest latency.
What should you do?

  1. A. Update the document of each family member separately by using a patch operation
  2. B. Update the document of each family member separately and set the consistency level to strong
  3. C. Update the document of each family member by using a transactional batch operation
正解と解説を表示

正解

C

解説

Transactional batch operations in Azure Cosmos DB provide ACID guarantees for multiple operations within the same logical partition (same partition key value). All family members share familyId as the partition key, so updating each member's address in one transactional batch is atomic, consistent, isolated, and durable with the lowest latency. Separate patch or update operations are not atomic across documents, and strong consistency alone does not provide cross-document atomicity.

問題 19

Question#19Topic1

You are designing an Azure Cosmos DB Core (SQL) API solution to store data from IoT devices. Writes from the devices will be occur every second.
The following is a sample of the data.
Question illustration
You need to select a partition key that meets the following requirements for writes:
✑ Minimizes the partition skew
✑ Avoids capacity limits
✑ Avoids hot partitions
What should you do?

  1. A. Create a new synthetic key that contains deviceId and timestamp
  2. B. Use timestamp as the partition key
  3. C. Use deviceManufacturer as the partition key
  4. D. Use sensor1Value as the partition key
正解と解説を表示

正解

A

解説

With writes every second per IoT device, deviceId alone can concentrate sustained write load on one logical partition per device. A synthetic key combining deviceId and timestamp distributes writes across time-based sub-partitions for each device, reducing hot-partition risk and partition skew while maintaining queryability by device. Timestamp alone creates global hot partitions; deviceManufacturer and sensor1Value have insufficient cardinality for even write distribution.

問題 20

Question#20Topic1

You need to create a data store for a directory of small and medium-sized businesses (SMBs). The data store must meet the following requirements:
✑ Store companies and the users employed by them. Each company will have less than 1,000 users.
✑ Some users have data that is greater than 2 KB.
✑ Associate each user to only one company.
✑ Provide the ability to browse by company.
✑ Provide the ability to browse the users by company.
✑ Whenever a company or user profile is selected, show a details page for the company and all the related users.
✑ Be optimized for reading data.
Which design should you implement to optimize the data store for reading data?

  1. A. In a directory container, create a document for each company and a document for each user. Use the company ID as the partition key.
  2. B. Create a user container that uses the user ID as the partition key and a company container that uses the company ID as the partition key. Add the company ID to each user document.
  3. C. In a user container, create a document for each user. Embed the company into each user document. Use the user ID as the partition key.
  4. D. In a company container, create a document for each company. Embed the users into company documents. Use the company ID as the partition key.
正解と解説を表示

正解

D

解説

The workload is read-optimized: browse by company, browse users by company, and show company details with all related users in one view. Embedding users in company documents within a company container partitioned by companyId delivers all required data in a single point read per company page. Separate user/company containers require multiple round trips; embedding company in user documents makes company browsing cross-partition; each company has fewer than 1,000 users, keeping documents within practical size limits.

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