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NEW QUESTION # 42
You have a container named container1 in an Azure Cosmos DB for NoSQL account named account1 that is set to the session default consistency level. The average size of an item in container1 is 20 KB.
You have an application named App1 that uses the Azure Cosmos DB SDK and performs a point read on the same set of items in container1 every minute.
You need to minimize the consumption of the request units (RUs) associated to the reads by App1. What should you do?

  • A. In App1, modify the connection policy settings.
  • B. In account1, provision a dedicated gateway and integrated cache
  • C. In account1, change the default consistency level to bounded staleness.
  • D. In App1, change the consistency level of read requests to consistent prefix.

Answer: D

Explanation:
Explanation
The cost of a point read for a 1 KB item is 1 RU. The cost of other operations depends on factors such as item size, indexing policy, consistency level, and query complexity . To minimize the consumption of RUs, you can optimize these factors according to your application needs.
For your scenario, one possible way to minimize the consumption of RUs associated to the reads by App1 is to change the consistency level of read requests to consistent prefix. Consistent prefix is a lower consistency level than session, which is the default consistency level for Azure Cosmos DB. Lower consistency levels consume fewer RUs than higher consistency levels2. Consistent prefix guarantees that reads never see out-of-order writes and that monotonic reads are preserved1. This may be suitable for your application if you can tolerate some eventual consistency.


NEW QUESTION # 43
You have a container in an Azure Cosmos DB Core (SQL) API account.
You need to use the Azure Cosmos DB SDK to replace a document by using optimistic concurrency.
What should you include in the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: ConsistencyLevel
The ItemRequestOptions Class ConsistencyLevel property gets or sets the consistency level required for the request in the Azure Cosmos DB service.
Azure Cosmos DB offers 5 different consistency levels. Strong, Bounded Staleness, Session, Consistent Prefix and Eventual - in order of strongest to weakest consistency.
Box 2: _etag
The ItemRequestOptions class helped us implement optimistic concurrency by specifying that we wanted the SDK to use the If-Match header to allow the server to decide whether a resource should be updated. The If-Match value is the ETag value to be checked against. If the ETag value matches the server ETag value, the resource is updated.
Reference:
https://docs.microsoft.com/en-us/dotnet/api/microsoft.azure.cosmos.itemrequestoptions
https://cosmosdb.github.io/labs/dotnet/labs/10-concurrency-control.html


NEW QUESTION # 44
You have an Azure Cosmos DB Core (SQL) API account that uses a custom conflict resolution policy. The account has a registered merge procedure that throws a runtime exception.
The runtime exception prevents conflicts from being resolved.
You need to use an Azure function to resolve the conflicts.
What should you use?

  • A. a function that pulls items from the conflicts feed and is triggered by a timer trigger
  • B. a function that receives items pushed from the conflicts feed and is triggered by an Azure Cosmos DB trigger
  • C. a function that receives items pushed from the change feed and is triggered by an Azure Cosmos DB trigger
  • D. a function that pulls items from the change feed and is triggered by a timer trigger

Answer: B

Explanation:
Explanation
The Azure Cosmos DB Trigger uses the Azure Cosmos DB Change Feed to listen for inserts and updates across partitions. The change feed publishes inserts and updates, not deletions.
Reference: https://docs.microsoft.com/en-us/azure/azure-functions/functions-bindings-cosmosdb


NEW QUESTION # 45
You have an Azure Cosmos DB Core (SQL) API account named account1.
You have the Azure virtual networks and subnets shown in the following table.

The vnet1 and vnet2 networks are connected by using a virtual network peer.
The Firewall and virtual network settings for account1 are configured as shown in the exhibit.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 46
You have a container named container1 in an Azure Cosmos DB Core (SQL) API account. Upserts of items in container1 occur every three seconds.
You have an Azure Functions app named function1 that is supposed to run whenever items are inserted or replaced in container1.
You discover that function1 runs, but not on every upsert.
You need to ensure that function1 processes each upsert within one second of the upsert.
Which property should you change in the Function.json file of function1?

  • A. checkpointInterval
  • B. maxItemsPerInvocation
  • C. leaseCollectionsThroughput
  • D. feedPollDelay

Answer: D

Explanation:
Explanation
With an upsert operation we can either insert or update an existing record at the same time.
FeedPollDelay: The time (in milliseconds) for the delay between polling a partition for new changes on the feed, after all current changes are drained. Default is 5,000 milliseconds, or 5 seconds.
Reference: https://docs.microsoft.com/en-us/azure/azure-functions/functions-bindings-cosmosdb-v2-trigger


NEW QUESTION # 47
You have a database named telemetry in an Azure Cosmos DB Core (SQL) API account that stores IoT data.
The database contains two containers named readings and devices.
Documents in readings have the following structure.
id
deviceid
timestamp
ownerid
measures (array)
- type
- value
- metricid
Documents in devices have the following structure.
id
deviceid
owner
- ownerid
- emailaddress
- name
brand
model
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: Yes
Need to join readings and devices.
Box 2: No
Only readings is required. All required fields are in readings.
Box 3: No
Only devices is required. All required fields are in devices.


NEW QUESTION # 48
You need to provide a solution for the Azure Functions notifications following updates to con-product. The solution must meet the business requirements and the product catalog requirements.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  • A. Configure the trigger for each function to use a different leaseCollectionName
  • B. Configure the trigger for each function to use the same leaseCollectionPrefix
  • C. Configure the trigger for each function to use a different leaseCollectionPrefix
  • D. Configure the trigger for each function to use the same leaseCollectionNair.e

Answer: C,D

Explanation:
leaseCollectionPrefix: when set, the value is added as a prefix to the leases created in the Lease collection for this Function. Using a prefix allows two separate Azure Functions to share the same Lease collection by using different prefixes.
Scenario: Use Azure Functions to send notifications about product updates to different recipients.
Trigger the execution of two Azure functions following every update to any document in the con-product container.
Reference:
https://docs.microsoft.com/en-us/azure/azure-functions/functions-bindings-cosmosdb-v2-trigger


NEW QUESTION # 49
You have an Azure Cosmos DB Core (SQL) API account.
You run the following query against a container in the account.
SELECT
IS_NUMBER("1234") AS A,
IS_NUMBER(1234) AS B,
IS_NUMBER({prop: 1234}) AS C
What is the output of the query?

  • A. [{"A": true, "B": true, "C": false}]
  • B. [{"A": false, "B": true, "C": false}]
  • C. [{"A": true, "B": true, "C": true}]
  • D. [{"A": true, "B": false, "C": true}]

Answer: B

Explanation:
IS_NUMBER returns a Boolean value indicating if the type of the specified expression is a number.
"1234" is a string, not a number.


NEW QUESTION # 50
You have a container in an Azure Cosmos DB Core (SQL) API account.
You need to use the Azure Cosmos DB SDK to replace a document by using optimistic concurrency.
What should you include in the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/dotnet/api/microsoft.azure.cosmos.itemrequestoptions
https://cosmosdb.github.io/labs/dotnet/labs/10-concurrency-control.html


NEW QUESTION # 51
You have the indexing policy shown in the following exhibit.

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 52
You are developing an application that will use an Azure Cosmos DB Core (SQL) API account as a data source.
You need to create a report that displays the top five most ordered fruits as shown in the following table.

A collection that contains aggregated data already exists. The following is a sample document:
{
"name": "apple",
"type": ["fruit", "exotic"],
"orders": 10000
}
Which two queries can you use to retrieve data for the report? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A)

B)

C)

D)

  • A. Option A
  • B. Option C
  • C. Option D
  • D. Option B

Answer: C,D

Explanation:
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.


NEW QUESTION # 53
You have a database named db1 in an Azure Cosmos DB for NoSQL
You are designing an application that will use dbl.
In db1, you are creating a new container named coll1 that will store in coll1.
The following is a sample of a document that will be stored in coll1.

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?

  • A. orderDate
  • B. customerId
  • C. orderId
  • D. id

Answer: B

Explanation:
Explanation
Based on the characteristics of the application and the provided document structure, the most suitable partition key value for coll1 in the given scenario would be the customerId, Option B.
The application frequently creates new orders by different customers and customers often view their past order history. Using customerId as the partition key would ensure that all orders associated with a particular customer are stored in the same partition. This enables efficient querying of past order history for a specific customer and reduces cross-partition queries, resulting in lower costs and improved performance.
a partition key is a JSON property (or path) within your documents that is used by Azure Cosmos DB to distribute data among multiple partitions3. A partition key should have a high cardinality, which means it should have many distinct values, such as hundreds or thousands1. A partition key should also align with the most common query patterns of your application, so that you can efficiently retrieve data by using the partition key value1.
Based on these criteria, one possible partition key that you could use for coll1 is B. customerId.
This partition key has the following advantages:
* It has a high cardinality, as each customer will have a unique ID
* It aligns with the query patterns of the application, as customers will often view their past order history3.
* It minimizes costs, as it reduces the number of cross-partition queries and optimizes the storage and throughput utilization1.
This partition key also has some limitations, such as:
* It may not be optimal for scenarios where orders need to be queried independently from customers or aggregated by date or other criteria
* It may result in hot partitions or throttling if some customers create orders more frequently than others or have more data than others
* It may not support transactions across multiple customers, as transactions are scoped to a single logical partition2.
Depending on your specific use case and requirements, you may need to adjust this partition key or choose a different one. For example, you could use a synthetic partition key that concatenates multiple properties of an item2, or you could use a partition key with a random or pre-calculated suffix to distribute the workload more evenly2.


NEW QUESTION # 54
You have a database in an Azure Cosmos DB SQL API Core (SQL) account that is used for development.
The database is modified once per day in a batch process.
You need to ensure that you can restore the database if the last batch process fails. The solution must minimize costs.
How should you configure the backup settings? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation


NEW QUESTION # 55
You have an Azure Cosmos DB Core (SQL) API account named storage1 that uses provisioned throughput capacity mode.
The storage1 account contains the databases shown in the following table.

The databases contain the containers shown in the following table.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: No
Four containers with 1000 RU/s each.
Box 2: No
Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container.
Box 3: Yes
Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container. Can very well add an additional container.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/plan-manage-costs
https://azure.microsoft.com/en-us/pricing/details/cosmos-db/


NEW QUESTION # 56
You need to select the partition key for con-iot1. The solution must meet the IoT telemetry requirements.
What should you select?

  • A. the temperature
  • B. the timestamp
  • C. the humidity
  • D. the device ID

Answer: D

Explanation:
The partition key is what will determine how data is routed in the various partitions by Cosmos DB and needs to make sense in the context of your specific scenario. The IoT Device ID is generally the "natural" partition key for IoT applications.
Scenario: The iotdb database will contain two containers named con-iot1 and con-iot2.
Ensure that Azure Cosmos DB costs for IoT-related processing are predictable.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/iot-using-cosmos-db


NEW QUESTION # 57
You have an Azure Cosmos DB for NoSQL account named account1 that has a single read-write region and one additional read region. Account1 uses the strong default consistency level.
You have an application that uses the eventual consistency level when submitting requests to account1.
How will writes from the application be handled?

  • A. Azure Cosmos DB will reject writes from the application.
  • B. Writes will use the strong consistency level.
  • C. Writes will use the eventual consistency level.
  • D. The write order is not guaranteed during replication.

Answer: B

Explanation:
Explanation
This is because the write concern is mapped to the default consistency level configured on your Azure Cosmos DB account, which is strong in this case. Strong consistency ensures that every write operation is synchronously committed to every region associated with your Azure Cosmos DB account. The eventual consistency level that the application uses only applies to the read operations. Eventual consistency offers higher availability and better performance, but it does not guarantee the order or latency of the reads.


NEW QUESTION # 58
You have a container named container1 in an Azure Cosmos DB Core (SQL) API account.
You need to provide a user named User1 with the ability to insert items into container1 by using role-based access control (RBAC). The solution must use the principle of least privilege.
Which roles should you assign to User1?

  • A. DocumentDB Account Contributor only
  • B. Cosmos DB Built-in Data Contributor only
  • C. DocumentDB Account Contributor and Cosmos DB Built-in Data Contributor
  • D. CosmosDB Operator only

Answer: D

Explanation:
Cosmos DB Operator: Can provision Azure Cosmos accounts, databases, and containers. Cannot access any data or use Data Explorer.
Incorrect Answers:
B: DocumentDB Account Contributor can manage Azure Cosmos DB accounts. Azure Cosmos DB is formerly known as DocumentDB.
C: DocumentDB Account Contributor: Can manage Azure Cosmos DB accounts.


NEW QUESTION # 59
You have an app that stores data in an Azure Cosmos DB Core (SQL) API account The app performs queries that return large result sets.
You need to return a complete result set to the app by using pagination. Each page of results must return 80 items.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - Configure the MaxItemCount in QueryRequestOptions
2 - Run the query and provide a continuation token
3 - Append the results to a variable


NEW QUESTION # 60
You have an Azure Cosmos DB for NoSQL account.
The change feed is enabled on a container named invoice.
You create an Azure function that has a trigger on the change feed.
What is received by the Azure function?

  • A. only the changed properties and the system-defined properties of the updated items
  • B. all the properties of the original items and the updated items
  • C. all the properties of the updated items
  • D. only the partition key and the changed properties of the updated items

Answer: C

Explanation:
Explanation
According to the Azure Cosmos DB documentation12, the change feed is a persistent record of changes to a container in the order they occur. The change feed outputs the sorted list of documents that were changed in the order in which they were modified.
The Azure function that has a trigger on the change feed receives all the properties of the updated items2. The change feed does not include the original items or only the changed properties. The change feed also includes some system-defined properties such as _ts (the last modified timestamp) and _lsn (the logical sequence number)3.
Therefore, the correct answer is: A. all the properties of the updated items


NEW QUESTION # 61
You have an Azure Cosmos DB Core (SQL) API account used by an application named App1.
You open the Insights pane for the account and see the following chart.

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: incorrect connection URLs
400 Bad Request: Returned when there is an error in the request URI, headers, or body. The response body will contain an error message explaining what the specific problem is.
The HyperText Transfer Protocol (HTTP) 400 Bad Request response status code indicates that the server cannot or will not process the request due to something that is perceived to be a client error (for example, malformed request syntax, invalid request message framing, or deceptive request routing).
Box 2: 6 thousand
201 Created: Success on PUT or POST. Object created or updated successfully.
Note:
200 OK: Success on GET, PUT, or POST. Returned for a successful response.
404 Not Found: Returned when a resource does not exist on the server. If you are managing or querying an index, check the syntax and verify the index name is specified correctly.
Reference: https://docs.microsoft.com/en-us/rest/api/searchservice/http-status-codes


NEW QUESTION # 62
You are implementing an Azure Data Factory data flow that will use an Azure Cosmos DB (SQL API) sink to write a dataset. The data flow will use 2,000 Apache Spark partitions.
You need to ensure that the ingestion from each Spark partition is balanced to optimize throughput.
Which sink setting should you configure?

  • A. Batch size
  • B. Collection action
  • C. Write throughput budget
  • D. Throughput

Answer: A

Explanation:
Batch size: An integer that represents how many objects are being written to Cosmos DB collection in each batch. Usually, starting with the default batch size is sufficient. To further tune this value, note:
Cosmos DB limits single request's size to 2MB. The formula is "Request Size = Single Document Size * Batch Size". If you hit error saying "Request size is too large", reduce the batch size value.
The larger the batch size, the better throughput the service can achieve, while make sure you allocate enough RUs to empower your workload.
Incorrect Answers:
A: Throughput: Set an optional value for the number of RUs you'd like to apply to your CosmosDB collection for each execution of this data flow. Minimum is 400.
B: Write throughput budget: An integer that represents the RUs you want to allocate for this Data Flow write operation, out of the total throughput allocated to the collection.
D: Collection action: Determines whether to recreate the destination collection prior to writing.
None: No action will be done to the collection.
Recreate: The collection will get dropped and recreated


NEW QUESTION # 63
You have a container in an Azure Cosmos DB Core (SQL) API account. The container stores telemetry data from IoT devices. The container uses telemetryId as the partition key and has a throughput of 1,000 request units per second (RU/s). Approximately 5,000 IoT devices submit data every five minutes by using the same telemetryId value.
You have an application that performs analytics on the data and frequently reads telemetry data for a single IoT device to perform trend analysis.
The following is a sample of a document in the container.

You need to reduce the amount of request units (RUs) consumed by the analytics application.
What should you do?

  • A. Increase the offerThroughput value for the container.
  • B. Decrease the offerThroughput value for the container.
  • C. Move the data to a new container that uses a partition key of date.
  • D. Move the data to a new container that has a partition key of deviceId.

Answer: D

Explanation:
Explanation
The partition key is what will determine how data is routed in the various partitions by Cosmos DB and needs to make sense in the context of your specific scenario. The IoT Device ID is generally the "natural" partition key for IoT applications.
Reference: https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/iot-using-cosmos-db


NEW QUESTION # 64
You plan to store order data in Azure Cosmos DB for NoSQL account. The data contains information about orders and their associated items.
You need to develop a model that supports order read operations. The solution must minimize the number or requests.

  • A. Create a single database that contains a container for order and a container for order items.
  • B. Create a single database that contains one container. Create a separate document for each order and embed the order items into the order documents.
  • C. Create a database for orders and a database for order items.
  • D. Create a single database that contains one container. Store orders and order items in separate documents in the container.

Answer: B

Explanation:
Explanation
Azure Cosmos DB is a multi-model database that supports various data models, such as documents, key-value, graph, and column-family3. The core content-model of Cosmos DB's database engine is based on atom-record-sequence (ARS), which allows it to store and query different types of data in a flexible and efficient way3.
To develop a model that supports order read operations and minimizes the number of requests, you should consider the following factors:
* The size and shape of your data
* The frequency and complexity of your queries
* The latency and throughput requirements of your application
* The trade-offs between storage efficiency and query performance
Based on these factors, one possible model that you could implement is B. Create a single database that contains one container. Create a separate document for each order and embed the order items into the order documents.
This model has the following advantages:
* It stores orders and order items as self-contained documents that can be easily retrieved by order ID1.
* It avoids storing redundant data or creating additional containers for order items1.
* It allows you to view the order history of a customer with simple queries1.
* It leverages the benefits of embedding data, such as reducing the number of requests, improving query performance, and simplifying data consistency2.
This model also has some limitations, such as:
* It may not be suitable for some order items that have data that is greater than 2 KB, as it could exceed the maximum document size limit of 2 MB2.
* It may not be optimal for scenarios where order items need to be queried independently from orders or aggregated by other criteria
* It may not support transactions across multiple orders or customers, as transactions are scoped to a single logical partition2.
Depending on your specific use case and requirements, you may need to adjust this model or choose a different one. For example, you could use a hybrid data model that combines embedding and referencing data2
, or you could use a graph data model that expresses entities and relationships as vertices and edges.


NEW QUESTION # 65
You need to configure an Apache Kafka instance to ingest data from an Azure Cosmos DB Core (SQL) API account. The data from a container named telemetry must be added to a Kafka topic named iot. The solution must store the data in a compact binary format.
Which three configuration items should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  • A. "connector.class": "com.azure.cosmos.kafka.connect.source.CosmosDBSinkConnector"
  • B. "connect.cosmos.containers.topicmap": "iot"
  • C. "connector.class": "com.azure.cosmos.kafka.connect.source.CosmosDBSourceConnector"
  • D. "key.converter": "org.apache.kafka.connect.json.JsonConverter"
  • E. "key.converter": "io.confluent.connect.avro.AvroConverter"
  • F. "connect.cosmos.containers.topicmap": "iot#telemetry"

Answer: A,E,F

Explanation:
Explanation
C: Avro is binary format, while JSON is text.
F: Kafka Connect for Azure Cosmos DB is a connector to read from and write data to Azure Cosmos DB. The Azure Cosmos DB sink connector allows you to export data from Apache Kafka topics to an Azure Cosmos DB database. The connector polls data from Kafka to write to containers in the database based on the topics subscription.
D: Create the Azure Cosmos DB sink connector in Kafka Connect. The following JSON body defines config for the sink connector.
Extract:
"connector.class": "com.azure.cosmos.kafka.connect.sink.CosmosDBSinkConnector",
"key.converter": "org.apache.kafka.connect.json.AvroConverter"
"connect.cosmos.containers.topicmap": "hotels#kafka"
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/sql/kafka-connector-sink
https://www.confluent.io/blog/kafka-connect-deep-dive-converters-serialization-explained/


NEW QUESTION # 66
......


Achieving the Microsoft DP-420 certification demonstrates to employers and colleagues that a candidate has the skills and knowledge to design and implement cloud-native applications using Azure Cosmos DB. This certification is a valuable credential for professionals who want to advance their careers in cloud computing and data management.


The Microsoft DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Exam is a certification exam that measures the candidate's proficiency in developing and implementing cloud-native applications using Microsoft Azure Cosmos DB. The exam is designed to test the candidate's skills and knowledge in building and managing distributed applications that can scale and perform efficiently in the cloud.

 

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