Microsoft Certified: Azure Cosmos DB Developer Specialty - (DP-420) Exam Questions

Correct Answer: A

• After running the script, there will be an instance of Azure Cosmos DB in North Europe that is writable.

  
  

  Yes - Because the failover-priority-change command is setting North Europe to priority 0, which means it will be the new write region.

  
  

• After running the script, the Azure Cosmos DB instance in West Europe will be writable.

  
  

  No - Because the script changes the failover priority to make North Europe the write region, West Europe will not be writable after the script is run (it will become a read region).

  
  

• The cost of the Azure Cosmos DB account is unaffected by running the script.

  
  

  No - Changing the failover priorities can potentially affect the cost because the pricing can vary based on the number of regions and whether you're enabling multi-region writes, which can change the billing. Additionally, if the Cosmos DB account was single-master and you switch to multi-master by having writes in multiple regions (even temporarily during the failover process), that could also affect the cost.

Correct Answer: D

• Box 1 (Grant permissions to create containers by using): ✓ Role-based access control (RBAC)

  Box 2 (Create containers by using the): ✓ Azure Resource Manager API

  Explanation:

  1. For permissions:

  • Role-based access control (RBAC) is correct because:

    • The account has disableKeyBasedMetadataWriteAccess enabled (which rules out Account keys)

    • DevUser1 has an Azure AD account

    • RBAC is the appropriate method for Azure AD-based authentication and authorization

  1. For container creation:

  • Azure Resource Manager API is correct because:

    • It's the management plane API that handles resource creation

    • It works with RBAC authentication

    • It's designed for administrative operations like creating containers

    • SQL (Core) API is for data operations, not container management

    • Azure AD Graph API is for directory operations, not Cosmos DB management

  These selections will enable DevUser1 to create containers in account1 while maintaining proper security and authentication requirements.

Correct Answer: A

The IS_NUMBER function in Azure Cosmos DB's SQL API is used to determine if the provided expression is a number. Based on the SQL query provided:

1. IS_NUMBER("1234") checks if the string "1234" is a number, which it is not, so it should return false.

   
   

2. IS_NUMBER(1234) checks if the number 1234 is a number, which it is, so it should return true.

   
   

3. IS_NUMBER({prop: 1234}) checks if the JSON object {prop: 1234} is a number, which it is not (it's an object), so it should return false.

Therefore, the output of the query should be:
[{"A": false, "B": true, "C": false}]

Which corresponds to option A.

Correct Answer: C

Create a container that contains a document for each Author and a document for each Book. In each Book document, embed authorId.

Here's why:

Azure Cosmos DB is a NoSQL database service that supports schema-less data, which means you can store your data in one container without needing to define any schema upfront. It offers various APIs, including the Core (SQL) API, which provides a way to query the data using a familiar SQL-like language.

The main advantage of using Cosmos DB for this scenario is its ability to handle large amounts of unstructured data with low latency and high throughput. When designing a data model for Cosmos DB, especially for read-heavy workloads, it's important to optimize for read performance and to minimize the cost of read operations.

Option C takes advantage of the denormalization strategy common in NoSQL databases. By embedding the authorId within each Book document, you can easily retrieve all books for a given author with a single read operation. This approach minimizes the number of cross-partition queries and the associated costs because you do not need to join documents at read time (which can be expensive and slow in a NoSQL database).

Here's a breakdown of why the other options are less optimal:

A. While this option also suggests embedding related data, embedding bookId in the Author document could lead to large documents if an author has written many books. This might impact performance and cost because it could lead to large documents and possibly exceed the maximum document size limits.

B. Storing Author, Book, and Bookauthorlnk documents in the same container without embedding related information requires cross-document join operations to retrieve all books for a given author. This can be more complex and costly in terms of performance and read operations in Cosmos DB.

D. Embedding the data from Bookauthorlnk in both Author and Book documents is redundant and can lead to data inconsistency. Additionally, it increases the size of both documents unnecessarily, which can affect performance and cost.

Therefore, option C is the most cost-effective and performant solution, as it simplifies the data retrieval process and minimizes latency for the most common query pattern of listing books for a given author.

Correct Answer: D

Here are the considerations for each option:

A. Use timestamp as the partition key: This is typically not a good choice because the timestamp is always increasing and all writes will go to a single partition, creating a hot partition problem.

B. Create a new synthetic key that contains deviceId and sensor1Value: If sensor1Value doesn't have a wide range of values or changes infrequently, this could result in a skewed distribution. However, if sensor1Value is highly variable and changes with each write, this could be a good option as it would distribute the writes across different partitions based on the combination of deviceId and sensor1Value.

C. Create a new synthetic key that contains deviceId and deviceManufacturer: This is likely not a good choice because the deviceManufacturer is likely the same for many devices and wouldn't provide a good distribution across partitions. It could create hot partitions if a particular manufacturer has many devices.

D. Create a new synthetic key that contains deviceId and a random number: This could be a good choice because the random number would help distribute the writes across multiple partitions. However, care must be taken to ensure that the random number has a proper range and distribution to effectively distribute the data.

The best option would likely be D, creating a new synthetic key that contains deviceId and a random number, provided that the random number is well distributed. This would ensure that the writes are spread across different partitions, minimizing skew and avoiding hot partitions.

In practice, you would also need to ensure that the random number does not affect your ability to efficiently query the data. You might want to include logic in your application to manage the random number generation to ensure even distribution and to handle queries effectively.

Correct Answer: B

1. Query: SELECT * FROM c where c.orderDate = "2019-05-03"

   • Since the partition key is orderId and the query is filtering by orderDate, this query will not filter by partition key and will therefore result in a cross-partition query.

   • Answer: Yes
     

2. Query: SELECT * FROM c where c.customerId = "5425"

   • Again, as this query is filtering by customerId and not by the partition key orderId, this query will also result in a cross-partition query.

   • Answer: Yes

     
     

3. Query: SELECT * FROM c where c.orderDate = "2019-05-03" and c.orderId = "9d7816e6-f401-42ba-ad05-0e03de35c0b8"

   • This query is filtering by orderDate and orderId. Even though orderDate is included, the presence of the partition key orderId with a specific value means that the query can be directed to a single partition, thus avoiding a cross-partition query.

   • Answer: No

     
     

In summary, only the third query will not run as a cross-partition query because it includes the partition key with a specific value, which allows Cosmos DB to target a single partition. The first two queries do not include the partition key and will scan across multiple partitions.

Correct Answer: C

Based on this requirement, here are the considerations for selecting the partition key and unique key:

• Partition Key: The partition key should be chosen to evenly distribute the data and requests across multiple partitions, ensuring scalability and performance. Given that each small business is a discrete unit and would likely perform operations on its employees' data, companyId would be a suitable partition key. It would distribute the data across different partitions for each company.

  
  

• Unique Key: A unique key ensures that within a partition, the value of the unique key is different for every item. Since you need to ensure that the emailAddress is unique for each employee within the same company, the unique key should be set to emailAddress. However, the uniqueness is scoped to the partition key, meaning that an emailAddress must be unique within the same companyId.

  
  

Therefore, for the hotspot options provided:

• Partition key: You should set it to companyId.

• Unique key: You should set it to emailAddress.

  
  

This setup will ensure that each employee within the same company has a unique email address in the database.

Correct Answer: BD

ARRAY_CONTAINS returns a Boolean indicating whether the array contains the specified value. You can check for a partial or full match of an object by using a boolean expression within the command.

Incorrect Answers:

A: Default sorting ordering is Ascending. Must use Descending order.

C: Order on Orders not on Type.

Reference:

https://docs.microsoft.com/en-us/azure/cosmos-db/sql/sql-query-array-contains

Correct Answer: C

Move the data to a new container that uses a partition key of deviceId.

Why it is correct:

The partition key choice is fundamental in optimizing the performance and cost of Azure Cosmos DB. The analytics application frequently reads telemetry data for a single IoT device to perform trend analysis, which indicates that most queries are scoped to a single deviceId. By using deviceId as the partition key, all the telemetry data for a specific device will reside in the same partition. This colocation optimizes the RU consumption for the following reasons:

• Efficient Partition Scans: Queries scoped to a single partition key will consume fewer RUs because the data is collocated, and the database engine does not need to span multiple partitions to retrieve it.

• Reduced Cross-Partition Queries: Currently, with telemetryId as the partition key, if multiple devices use the same telemetryId, a read operation to retrieve data for a single device may require a cross-partition query, which is more expensive in terms of RUs than a single-partition query.

• Improved Throughput Utilization: A more evenly distributed workload across partitions prevents bottlenecks on a single partition key, which can result from having many devices writing with the same telemetryId. This change spreads the load across device-specific partitions, potentially reducing contention and improving throughput utilization.
  

Therefore, by restructuring the data model to use deviceId as the partition key, the analytics application will perform more RU-efficient operations, which aligns with the goal of reducing RU consumption.

Correct Answer: C

When you choose Autoscale throughput for an Azure Cosmos DB container, the service will automatically scale the throughput of your database or container based on its usage. However, even if the actual usage goes down to zero, you are not charged for zero throughput.

Autoscale throughput provides a range within which the throughput can scale, and it guarantees instant and automatic scaling within this range. The minimum amount you are charged is 10% of the maximum throughput you configure. If you set the maximum throughput to 20,000 RU/s, the minimum for which you will be charged is 10% of that amount.

Therefore, for a maximum RU/s of 20,000, the charge when the usage is zero would still be for 2,000 RU/s, which is 10% of the maximum.

The correct answer is: C. 2,000