DP-900 Practice Test 16 — 15 Questions

Question 1

A social media application stores user posts in Azure Cosmos DB. Each post has fields: PostID (unique), UserID, Timestamp, Content, LikesCount. The application frequently queries for all posts by a specific UserID ordered by Timestamp descending. To minimize Request Unit (RU) consumption, which partition key and indexing strategy should be used?

Accepted Answer

Partition key: UserID, and create a composite index on (UserID, Timestamp DESC). Option A is correct because UserID is the most frequently filtered attribute, making it an ideal partition key to distribute data evenly and avoid cross-partition queries. Adding a composite index on (UserID, Timestamp DESC) allows the query to be served from a single physical partition with an index seek, minimizing RU consumption by avoiding a full scan or sort operation.

Answer

Partition key: Timestamp, and sort by UserID in the query

Answer

Partition key: PostID, and use ORDER BY Timestamp

Answer

Partition key: UserID, and use ORDER BY PostID

Question 2

A library management system uses Azure SQL Database. The Books table has 500,000 rows with columns: BookID (primary key, clustered), Title, Author, ISBN, PublishedYear, CopiesAvailable. Queries frequently filter by Author and then sort results by PublishedYear in descending order. The queries also return the Title and CopiesAvailable columns. Which indexing strategy will most improve query performance for these operations?

Accepted Answer

Create a nonclustered index on (Author, PublishedYear DESC) and include (Title, CopiesAvailable). Option A is correct because it creates a covering nonclustered index on (Author, PublishedYear DESC) that directly supports the filter (Author) and sort (PublishedYear DESC) operations. Including Title and CopiesAvailable as non-key columns makes the index covering, meaning all required columns are in the index leaf level, so SQL Server can satisfy the query entirely from the index without key lookups to the clustered index. This minimizes I/O and improves query performance.

Answer

Create a nonclustered index on Author only

Answer

Create a nonclustered index on PublishedYear DESC

Answer

Keep only the existing clustered index on BookID

Question 3

A social media application stores user profiles as JSON documents. Each profile has standard fields like userId, name, and email, but also optional fields such as education and work history. The application needs to query profiles by userId with low latency and also run SQL-like queries to find all profiles with a specific work history value. Which Azure Cosmos DB API should they choose?

Accepted Answer

SQL (Core) API. The SQL (Core) API is the correct choice because it natively supports querying JSON documents with SQL-like syntax, enabling both low-latency point reads by userId and complex queries on nested fields like work history. It provides automatic indexing of all JSON properties, which ensures efficient execution of queries across optional fields without requiring schema management.

Answer

MongoDB API

Answer

Gremlin (Graph) API

Answer

Table API

Question 4

A social networking application stores user profiles as JSON documents in Azure Cosmos DB. Each profile includes fields such as 'userName', 'email', 'followersCount', and optional 'interests'. The application needs to perform fast point reads by 'userName' (under 10 ms) and also run queries to find all users with a 'followersCount' greater than a certain value. The development team prefers to use a query syntax similar to SQL. Which Azure Cosmos DB API should they choose?

Accepted Answer

Azure Cosmos DB for NoSQL (SQL API). Azure Cosmos DB for NoSQL (SQL API) is the correct choice because it natively supports SQL-like query syntax for querying JSON documents, enabling the required queries such as filtering by 'followersCount'. It also provides fast point reads (under 10 ms) by using the 'userName' field as the partition key, ensuring efficient direct access to individual documents.

Answer

Azure Cosmos DB for MongoDB

Answer

Azure Cosmos DB for Table

Answer

Azure Cosmos DB for Apache Cassandra

Question 5

A company runs an e-commerce application on Azure SQL Database. The database experiences high transaction volume during business hours (9 AM to 6 PM) but very low activity at night and on weekends. They want to optimize costs by paying only for the compute resources used, while ensuring the database can automatically scale up during peak periods and scale down (or pause) during idle times. Which Azure SQL Database purchasing model and compute tier should they choose?

Accepted Answer

vCore-based purchasing model with serverless compute tier. The vCore-based purchasing model with serverless compute tier is correct because it automatically scales compute resources based on workload demand and can pause during idle periods, charging only for consumed compute and storage. This matches the requirement of high transaction volume during business hours and low activity at night/weekends, optimizing costs by eliminating charges for unused compute capacity.

Answer

DTU-based purchasing model

Answer

vCore-based purchasing model with provisioned compute tier

Answer

vCore-based purchasing model with Hyperscale service tier

Question 6

A company is migrating an on-premises SQL Server database to Azure. The database is 800 GB, uses SQL Server Agent jobs for scheduled tasks, and needs to link to another on-premises SQL Server instance via linked servers. The company wants a fully managed service with minimal application changes. Which Azure SQL service should they choose?

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance is correct because it provides near 100% compatibility with on-premises SQL Server, including support for SQL Server Agent jobs and linked servers, while being a fully managed platform-as-a-service (PaaS) offering. This allows the company to migrate the 800 GB database with minimal application changes, as it preserves the existing instance-level features without requiring a rearchitecture.

Answer

Azure SQL Database elastic pool

Answer

Azure SQL Database single database

Answer

Azure Synapse Analytics dedicated SQL pool

Question 7

A company uses Azure SQL Database for an e-commerce platform. The Orders table has columns: OrderID (primary key, clustered), CustomerID, OrderDate, TotalAmount. Queries frequently filter on CustomerID and a range of OrderDate, and then sort the results by OrderDate in descending order. The queries also return the TotalAmount column. Which indexing strategy will most improve query performance for these operations?

Accepted Answer

Create a nonclustered index on (CustomerID, OrderDate DESC) with included column TotalAmount. Option A is correct because it creates a covering index that matches the query's filter predicates (CustomerID equality, OrderDate range) and sort order (OrderDate DESC). By including TotalAmount as an included column, the index fully satisfies the query without needing to access the clustered index (key lookup), minimizing I/O and improving performance.

Answer

Create a nonclustered index on (OrderDate DESC, CustomerID) with included column TotalAmount

Answer

Change the clustered index to be on (CustomerID, OrderDate DESC)

Answer

Create a nonclustered index on (OrderDate DESC) without including TotalAmount

Question 8

A company uses Azure Synapse Analytics dedicated SQL pool to store a large fact table with billions of rows. The table is distributed using hash distribution on the SaleDate column. Queries that join this fact table with a small dimension table (Product) on ProductID are slow because the join requires shuffling data across distributions. Which design change would most improve the performance of these join queries?

Accepted Answer

Replicate the Product dimension table to all distributions.. Replicating the Product dimension table to all distributions eliminates the need to shuffle data across distributions during the join. In Azure Synapse dedicated SQL pool, hash distribution distributes rows across 60 distributions based on the hash of the distribution column (SaleDate). When joining on ProductID, which is not the distribution column, data must be moved between distributions. Replicating the small dimension table ensures each distribution has a local copy, allowing the join to be performed without data movement, significantly improving performance.

Answer

Change the distribution of the fact table to round-robin.

Answer

Partition the fact table by SaleDate.

Answer

Create a nonclustered index on ProductID in the fact table.

Question 9

A company is migrating a legacy on-premises database to Azure. They require the ability to run cross-database queries within the same logical server, full control over database collation settings, and want to minimize management overhead for infrastructure patching. The database size is under 1 TB and they do not need instance-level features like SQL Agent jobs or linked servers. Which Azure SQL offering should they choose?

Accepted Answer

Azure SQL Database. Azure SQL Database is the correct choice because it supports cross-database queries within the same logical server via elastic queries, allows full control over database-level collation settings, and is a fully managed Platform-as-a-Service (PaaS) offering that handles infrastructure patching automatically. With a database size under 1 TB and no need for instance-level features like SQL Agent jobs or linked servers, Azure SQL Database meets all requirements while minimizing management overhead.

Answer

Azure SQL Managed Instance

Answer

SQL Server on Azure Virtual Machine

Answer

Azure Synapse SQL pool

Question 10

A gaming company stores player game scores in Azure Cosmos DB. Each document contains PlayerID, GameID, Score, Timestamp. The most common query is: 'Get all scores for a specific game ordered by score descending'. Which partition key should be chosen 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 queries to the exact physical partition(s) containing that GameID. This avoids cross-partition fan-out, minimizing RU consumption. A partition key that matches the query filter ensures efficient index lookup and data retrieval.

Answer

PlayerID

Answer

Score

Answer

Timestamp

Question 11

A company runs an e-commerce application on Azure SQL Database. The Orders table has millions of rows. Queries that filter on CustomerID and order by OrderDate DESC are slow. The table currently has a clustered index on OrderID (the primary key). Which indexing strategy will most improve performance for these queries?

Accepted Answer

Create a nonclustered index on (CustomerID, OrderDate DESC) with included columns for other needed columns.. Option B is correct because creating a nonclustered index on (CustomerID, OrderDate DESC) with included columns allows the query to filter on CustomerID and sort by OrderDate in descending order using a single index seek, avoiding a sort operation. This leverages the index's key order to directly return rows in the desired order, which is critical for performance on large tables in Azure SQL Database.

Answer

Create a nonclustered index on CustomerID including OrderDate.

Answer

Rebuild the clustered index to be on CustomerID.

Answer

Create a nonclustered index on OrderDate.

Question 12

A company uses Azure SQL Database for an order management system. The Orders table has millions of rows with columns: OrderID (primary key, clustered), CustomerID, OrderDate, Status (e.g., 'Shipped', 'Pending'), TotalAmount. Queries frequently filter on OrderDate and Status, and sort results by OrderDate in descending order. They return several columns including TotalAmount. Which indexing strategy will most improve query performance?

Accepted Answer

Create a nonclustered index on (OrderDate DESC, Status) INCLUDE (CustomerID, TotalAmount). Option A is correct because it creates a covering nonclustered index that matches the query's filter and sort order exactly. The index on (OrderDate DESC, Status) allows SQL Server to seek directly on OrderDate and Status, and the descending order avoids a sort operation for the ORDER BY OrderDate DESC clause. Including CustomerID and TotalAmount as included columns makes this a covering index, so the query can be satisfied entirely from the index without key lookups to the clustered index, which is critical for performance on a table with millions of rows.

Answer

Create a clustered index on (OrderDate, Status)

Answer

Create a nonclustered index on (Status) only

Answer

Create a columnstore index on the entire table

Question 13

A company needs to store order data for an e-commerce platform. The system requires high concurrency, fast inserts, and the ability to enforce referential integrity between tables (e.g., Customers and Orders). Which Azure service should they use?

Accepted Answer

Azure SQL Database. Azure SQL Database is a fully managed relational database service that supports high concurrency, fast inserts, and enforces referential integrity through foreign key constraints. It provides ACID transactions and row-level locking to handle concurrent writes efficiently, making it ideal for e-commerce order processing where data consistency between Customers and Orders tables is critical.

Answer

Azure Cosmos DB

Answer

Azure Blob Storage

Answer

Azure Data Lake Storage Gen2

Question 14

A company has multiple independent databases for different business units, each with low to moderate usage and varying workload patterns. They want to consolidate these databases into a single Azure SQL Database deployment option to share resources and reduce costs, while ensuring that databases do not starve each other of resources. Which Azure SQL Database deployment option should they choose?

Accepted Answer

Elastic pool. Elastic pools are designed for exactly this scenario: multiple databases with low to moderate usage and varying workload patterns. They allow databases to share a fixed pool of resources (eDTUs or vCores) while using built-in resource governance to prevent any single database from starving others, thus optimizing cost and performance.

Answer

Single database (DTU model)

Answer

Managed Instance

Answer

Database per server (hyperscale)

Question 15

A company's application uses Microsoft SQL Server with multiple databases that need to run complex queries joining tables across databases. They are migrating to Azure and need a fully managed relational database service with high availability, automated backups, and minimal management overhead. They do not need a separate SQL Server installation and want to avoid managing VMs. Which Azure deployment option should they choose?

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance is the correct choice because it provides near-100% compatibility with on-premises SQL Server, including support for cross-database queries and linked servers, while being a fully managed platform-as-a-service (PaaS) offering. It eliminates the need to manage VMs or a separate SQL Server installation, and it includes built-in high availability (99.99% SLA) and automated backups, meeting all stated requirements.

Answer

Azure SQL Database single database

Answer

SQL Server on Azure Virtual Machines

Answer

Azure SQL Database elastic pool