DP-900 Practice Test 20 — 15 Questions

Question 1

A mobile gaming company is building a new feature that stores player profiles and game settings as key-value pairs. The development team is most familiar with SQL queries and wants to minimize the learning curve. They require low-latency reads and writes, and the data does not require complex joins. Which Azure Cosmos DB API should they choose?

Accepted Answer

A. Core (SQL) API. The Core (SQL) API is the correct choice because it provides native support for SQL queries, which aligns with the development team's familiarity with SQL and minimizes the learning curve. It stores data in JSON documents with key-value pairs, supports low-latency reads and writes, and does not require complex joins, making it ideal for player profiles and game settings.

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B. Azure Cosmos DB for Table API

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C. Azure Cosmos DB for MongoDB API

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D. Azure Cosmos DB for Cassandra API

Question 2

A media company needs to store millions of high-resolution photos for a public website. Each photo can be up to 50 MB. The storage solution must support secure access via URLs. Which Azure service should they use?

Accepted Answer

Azure Blob Storage. Azure Blob Storage is the correct choice because it is designed for storing massive amounts of unstructured data, such as high-resolution photos, and supports objects up to 4.7 TB per blob, easily accommodating 50 MB files. It provides secure access via URLs using shared access signatures (SAS) or public access levels, making it ideal for a public website serving media content.

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Azure Table Storage

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Azure Files

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Azure SQL Database

Question 3

A global e-commerce company uses Azure Cosmos DB with multiple write regions to handle high traffic from users worldwide. For their order processing system, they must guarantee that once an order is recorded, all subsequent reads from any region see the most up-to-date order status. However, they also need low write latency globally. Which configuration should they choose to meet these requirements?

Accepted Answer

Use single-region writes with strong consistency. Strong consistency with single-region writes ensures that all reads in any region return the most recent write, because Cosmos DB replicates writes synchronously to all regions when strong consistency is configured. This guarantees linearizability: once an order is committed, every subsequent read sees that update. Single-region writes avoid the conflict-resolution overhead of multi-region writes while still providing low write latency within the primary region, and reads from secondary regions are served from locally replicated data that is kept fully consistent.

Answer

Use multi-region writes with strong consistency

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Use multi-region writes with bounded staleness consistency

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Use single-region writes with eventual consistency and implement application-level conflict resolution

Question 4

A media publishing company stores high-resolution images and video files for their website. These files are large (hundreds of MBs each) and are accessed only a few times per month, but when accessed, they must be delivered within seconds. Additionally, they need to store a small amount of metadata (e.g., upload date, author) for each file. Which Azure service should they use for storing the binary files?

Accepted Answer

Azure Blob Storage. Azure Blob Storage is designed for storing massive amounts of unstructured binary data, such as high-resolution images and video files. It supports objects up to 4.75 TB in size, offers tiered storage (including cool and archive tiers) to optimize cost for infrequently accessed data, and provides low-latency access (typically under 10 seconds) for retrieval when needed. This makes it the ideal choice for the media publishing company's requirements.

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Azure Table Storage

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Azure File Storage

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Azure Queue Storage

Question 5

A hospital collects patient vital signs every minute using IoT sensors. Each reading contains a timestamp, patient ID, heart rate, blood pressure, and temperature. This data is ingested continuously for real-time monitoring and alerting. Which type of data workload does this scenario best represent?

Accepted Answer

D. Real-time streaming. This scenario requires continuous ingestion of sensor data with immediate processing for real-time monitoring and alerting. Real-time streaming workloads, such as those handled by Azure Stream Analytics or Apache Kafka, are designed to process unbounded data streams with low latency, making option D correct.

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A. Transactional workload

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B. Analytical workload

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C. Batch processing

Question 6

A manufacturing company collects sensor readings from thousands of IoT devices. Each reading consists of a device ID, a timestamp, and a numeric value. The data is stored as key-value pairs and must support low-latency reads and writes at a global scale. The company also needs to query the data by device ID and time range. Which Azure Cosmos DB API should they choose?

Accepted Answer

Table API. The Table API is the correct choice because it is designed for key-value workloads with a schema-less design, supporting low-latency reads and writes at global scale. It allows querying by partition key (device ID) and row key (timestamp) to efficiently retrieve data by device ID and time range, matching the IoT sensor data requirements.

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Core (SQL) API

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MongoDB API

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Gremlin API

Question 7

A gaming company stores player scores in Azure Cosmos DB using the NoSQL API. Each document contains: PlayerID (unique to player), GameID, Score, Timestamp. The most common query is: 'Retrieve all scores for a specific GameID, ordered by Score descending.' Which property should be chosen as the partition key to minimize Request Unit (RU) consumption?

Accepted Answer

GameID. GameID is the correct partition key because the most common query filters on GameID, and Cosmos DB routes each query to the physical partition(s) containing that GameID's data. Using GameID ensures the query touches only the relevant partition(s), minimizing RU consumption by avoiding cross-partition fan-out. A partition key that matches the filter predicate is essential for efficient, single-partition queries.

Answer

PlayerID

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Score

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Timestamp

Question 8

A mobile app stores user preferences as JSON documents in Azure Cosmos DB. The document includes userId, theme, language, and notification settings. The most common query retrieves the document for a specific userId. To minimize cost and ensure even distribution, which property should be chosen as the partition key?

Accepted Answer

userId. The userId property is the ideal partition key because it provides high cardinality (each user has a unique ID) and ensures even request distribution across physical partitions. Since the most common query retrieves a document by userId, using it as the partition key makes those queries point reads (single-partition queries), which are the most cost-efficient and fastest in Azure Cosmos DB.

Answer

theme

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language

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a concatenation of userId and language

Question 9

A mobile game company stores player scores in Azure Cosmos DB. Each document contains the fields PlayerID (unique to the player), GameID, Score, and Timestamp. The most common query is: 'Retrieve all scores for a specific GameID, ordered by Score descending.' Which property should be chosen as the partition key to minimize Request Unit (RU) consumption?

Accepted Answer

GameID. GameID is the correct partition key because the most common query filters on GameID, and using it as the partition key ensures that all documents for a given GameID are stored in the same physical partition. This allows the query to target a single partition, minimizing cross-partition fan-out and reducing Request Unit (RU) consumption. A partition key that matches the query filter is essential for efficient, low-latency reads in Azure Cosmos DB.

Answer

PlayerID

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Score

Answer

Timestamp

Question 10

A gaming company stores player profiles as JSON documents. Each profile can have different attributes; for example, some profiles include an 'achievements' field while others include a 'purchaseHistory' field. The application must retrieve profiles by player ID with single-digit-millisecond latency and also support SQL-like queries on any attribute. Which Azure data store should the company use?

Accepted Answer

B. Azure Cosmos DB Core (SQL) API. Azure Cosmos DB Core (SQL) API is the correct choice because it natively stores JSON documents with flexible schemas, supports indexing on any attribute for SQL-like queries, and guarantees single-digit-millisecond latency for point reads by player ID. This meets the requirement for both fast key-based lookups and ad-hoc querying across varying profile attributes.

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A. Azure Table Storage

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C. Azure Blob Storage

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D. Azure Database for PostgreSQL

Question 11

A mobile gaming company stores player activity logs as JSON documents. Each document has a unique ActivityID, a PlayerID, a timestamp, and a variable set of attributes depending on the game event (e.g., level started, item purchased). The application requires low-latency point reads by ActivityID and needs to query logs by PlayerID for a given time range. Schema flexibility is critical because new game events are added frequently. Which Azure Cosmos DB API should they choose?

Accepted Answer

NoSQL API (formerly SQL API). The NoSQL API (formerly SQL API) is the correct choice because it natively supports JSON documents with flexible schemas, enabling the variable attributes required for new game events. It provides low-latency point reads by ActivityID via direct partition key lookups and supports efficient queries by PlayerID within a time range using composite indexes or cross-partition queries with filtering. This API is optimized for schema-agnostic, document-based workloads and offers the richest query capabilities for JSON data in Azure Cosmos DB.

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MongoDB API

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Cassandra API

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Gremlin API

Question 12

A ride-sharing application needs to store real-time GPS location updates from drivers and passengers. The data is ingested as key-value pairs where the key is the user ID and the value is a timestamped location. The application requires low-latency reads and writes for millions of concurrent users, and the data model is simple with no need for complex queries or joins. Which Azure NoSQL database API should be used for this workload?

Accepted Answer

Azure Cosmos DB Table API. Azure Cosmos DB Table API is the correct choice because it provides a key-value store with low-latency reads and writes, ideal for high-throughput scenarios like real-time GPS updates. It supports a simple schema-less data model where each item is a key-value pair, and it offers single-millisecond latency at the 99th percentile for both reads and writes, meeting the requirement for millions of concurrent users without complex queries or joins.

Answer

Azure Cosmos DB SQL (Core) API

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Azure Cosmos DB for MongoDB API

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Azure Cosmos DB for Apache Gremlin API

Question 13

A media company stores video metadata in Azure Table Storage. Each video has a unique VideoID, and the application frequently queries for videos uploaded on a specific date. The current table uses PartitionKey = VideoID and RowKey = UploadDate. Queries filtering by UploadDate are slow and consume many transactions. Which design change will most optimize queries that retrieve all videos from a given date?

Accepted Answer

C. Change the PartitionKey to a date-based value (e.g., YYYY-MM-DD) and use VideoID as the RowKey.. Option C is correct because Azure Table Storage queries are most efficient when the PartitionKey is used as the primary filter. By changing the PartitionKey to a date-based value (e.g., YYYY-MM-DD), queries for all videos uploaded on a specific date become partition scans, which are fast and consume minimal transactions. Using VideoID as the RowKey still allows unique identification of each video within that date partition.

Answer

A. Use UploadDate as the RowKey only, but keep PartitionKey as VideoID.

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B. Create a secondary index on UploadDate.

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D. Migrate the data to Azure Cosmos DB Table API for better indexing.

Question 14

A media company stores high-definition video files for on-demand streaming. The files are accessed very frequently for the first 30 days after upload, then rarely (about once per month) for the next year, and after one year they are rarely accessed but must be retained for compliance (about once per year). Which set of access tier transitions minimizes cost while meeting access requirements?

Accepted Answer

Hot for 30 days, then Cool for 11 months, then Archive. Option A is correct because it aligns the Azure Blob Storage access tier transitions with the access pattern: Hot tier for the first 30 days of frequent access, Cool tier for the next 11 months of monthly access, and Archive tier after one year for rare compliance access. This minimizes cost by moving data to progressively cheaper storage tiers as access frequency drops, while still meeting the access requirements (Cool supports monthly access, Archive supports yearly access with retrieval time).

Answer

Hot for 30 days, then Archive immediately

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Cool for 30 days, then Cool for 11 months, then Archive

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Hot for 365 days, then Archive

Question 15

A manufacturing company stores IoT sensor data as JSON documents in Azure Cosmos DB. Each document contains a device ID, a timestamp, and a varying set of sensor readings. The application frequently queries data by device ID and a time range to retrieve all readings for a specific device over a period. The development team wants to use an API that supports SQL-like queries on this JSON data. Which Azure Cosmos DB API should they choose?

Accepted Answer

Azure Cosmos DB Core (SQL) API. The Azure Cosmos DB Core (SQL) API is the correct choice because it natively supports querying JSON documents using SQL-like syntax, which aligns with the requirement to run SQL-like queries on JSON data. This API provides a rich query language for filtering by device ID and timestamp ranges, making it ideal for the described IoT scenario where documents have varying sensor readings.

Answer

Azure Cosmos DB MongoDB API

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Azure Cosmos DB Cassandra API

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Azure Cosmos DB Gremlin API