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NEW QUESTION # 67
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 # 68
You have an Azure Cosmos DB Core (SQL) API account.
You configure the diagnostic settings to send all log information to a Log Analytics workspace.
You need to identify when the provisioned request units per second (RU/s) for resources within the account were modified.
You write the following query.
AzureDiagnostics
| where Category == "ControlPlaneRequests"
What should you include in the query?
- A. | where OperationName startswith "SqlContainersThroughputUpdate"
- B. | where OperationName startswith "SqlContainersDelete"
- C. | where OperationName startswith "MongoCollectionsThroughputUpdate"
- D. | where OperationName startswith "AccountUpdateStart"
Answer: D
Explanation:
The following are the operation names in diagnostic logs for different operations:
RegionAddStart, RegionAddComplete
RegionRemoveStart, RegionRemoveComplete
AccountDeleteStart, AccountDeleteComplete
RegionFailoverStart, RegionFailoverComplete
AccountCreateStart, AccountCreateComplete
*AccountUpdateStart*, AccountUpdateComplete
VirtualNetworkDeleteStart, VirtualNetworkDeleteComplete
DiagnosticLogUpdateStart, DiagnosticLogUpdateComplete
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/audit-control-plane-logs
NEW QUESTION # 69
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.
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?
- A. Create a new synthetic key that contains deviceId and sensor1Value.
- B. Use timestamp as the partition key.
- C. Create a new synthetic key that contains deviceId and a random number.
- D. Create a new synthetic key that contains deviceId and deviceManufacturer.
Answer: C
Explanation:
Use a partition key with a random suffix. Distribute the workload more evenly is to append a random number at the end of the partition key value. When you distribute items in this way, you can perform parallel write operations across partitions.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/synthetic-partition-keys
NEW QUESTION # 70
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 one container. Create a separate document for each order and embed the order items into the order documents.
- B. Create a database for orders and a database for order items.
- C. Create a single database that contains a container for order and a container for order items.
- D. Create a single database that contains one container. Store orders and order items in separate documents in the container.
Answer: A
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 criteria2.
* 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 # 71
The following is a sample of a document in orders.
The orders container uses customer as the partition key.
You need to provide a report of the total items ordered per month by item type. The solution must meet the following requirements:
Ensure that the report can run as quickly as possible.
Minimize the consumption of request units (RUs).
What should you do?
- A. Configure the report to query a new aggregate container. Populate the aggregates by using the change feed.
- B. Configure the report to query a new aggregate container. Populate the aggregates by using SQL queries that run daily.
- C. Configure the report to query orders by using a SQL query.
- D. Configure the report to query orders by using a SQL query through a dedicated gateway.
Answer: A
Explanation:
You can facilitate aggregate data by using Change Feed and Azure Functions, and then use it for reporting.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/change-feed
NEW QUESTION # 72
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.
Answer: A,C
Explanation:
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.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/sql-query-array-contains
NEW QUESTION # 73
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a container named container1 in an Azure Cosmos DB Core (SQL) API account.
You need to make the contents of container1 available as reference data for an Azure Stream Analytics job.
Solution: You create an Azure Synapse pipeline that uses Azure Cosmos DB Core (SQL) API as the input and Azure Blob Storage as the output.
Does this meet the goal?
- A. Yes
- B. No
Answer: B
Explanation:
Instead create an Azure function that uses Azure Cosmos DB Core (SQL) API change feed as a trigger and Azure event hub as the output.
The Azure Cosmos DB change feed is a mechanism to get a continuous and incremental feed of records from an Azure Cosmos container as those records are being created or modified. Change feed support works by listening to container for any changes. It then outputs the sorted list of documents that were changed in the order in which they were modified.
The following diagram represents the data flow and components involved in the solution:
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/changefeed-ecommerce-solution
NEW QUESTION # 74
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cosmos DB Core (SQL) API account named account 1 that uses autoscale throughput.
You need to run an Azure function when the normalized request units per second for a container in account1 exceeds a specific value.
Solution: You configure an Azure Monitor alert to trigger the function.
Does this meet the goal?
- A. No
- B. Yes
Answer: B
Explanation:
You can set up alerts from the Azure Cosmos DB pane or the Azure Monitor service in the Azure portal.
Note: Alerts are used to set up recurring tests to monitor the availability and responsiveness of your Azure Cosmos DB resources. Alerts can send you a notification in the form of an email, or execute an Azure Function when one of your metrics reaches the threshold or if a specific event is logged in the activity log.
NEW QUESTION # 75
You have a container named container1 in an Azure Cosmos DB for NoSQL account named account1.
You configure container1 to use Always Encrypted by using an encryption policy as shown in the C# and the Java exhibits. (Click the C# tab to view the encryption policy in C#. Click the Java tab to see the encryption policy in Java.)
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
According to the Azure Cosmos DB documentation , Always Encrypted is a feature designed to protect sensitive data, such as credit card numbers or national identification numbers, stored in Azure Cosmos DB.
Always Encrypted allows clients to encrypt sensitive data inside client applications and never reveal the encryption keys to the database.
To use Always Encrypted, you need to define an encryption policy for each container that specifies which properties should be encrypted and which data encryption keys (DEK) should be used. The DEKs are stored in Azure Cosmos DB and are wrapped by customer-managed keys (CMK) that are stored in Azure Key Vault.
Based on the encryption policy shown in the exhibits, the creditcard property is encrypted with a DEK named dek1, and the SSN property is encrypted with a DEK named dek2. Both DEKs are wrapped by a CMK named cmk1.
To answer your statements:
* You can perform a query that filters on the creditcard property = No. This is because the creditcard property is encrypted and cannot be used for filtering or sorting operations1.
* You can perform a query that filters on the SSN property = No. This is also because the SSN property is encrypted and cannot be used for filtering or sorting operations1.
* An application can be allowed to read the creditcard property while being restricted from reading the SSN property = Yes. This is possible by using different CMKs to wrap different DEKs and applying access policies on the CMKs in Azure Key Vault. For example, if you use cmk2 to wrap dek2 instead of cmk1, you can grant an application access to cmk1 but not cmk2, which means it can read the creditcard property but not the SSN property2.
NEW QUESTION # 76
You have an Azure Cosmos DB for NoSQL 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 pulls items from the change feed and is triggered by a timer 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 receives items pushed from the conflicts feed and is triggered by an Azure Cosmos DB trigger
Answer: D
NEW QUESTION # 77
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#telemetry"
- C. "key.converter": "org.apache.kafka.connect.json.JsonConverter"
- D. "connect.cosmos.containers.topicmap": "iot"
- E. "connector.class": "com.azure.cosmos.kafka.connect.source.CosmosDBSourceConnector"
- F. "key.converter": "io.confluent.connect.avro.AvroConverter"
Answer: A,B,F
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"
Incorrect Answers:
B: JSON is plain text.
Note, full example:
{
"name": "cosmosdb-sink-connector",
"config": {
"connector.class": "com.azure.cosmos.kafka.connect.sink.CosmosDBSinkConnector",
"tasks.max": "1",
"topics": [
"hotels"
],
"value.converter": "org.apache.kafka.connect.json.AvroConverter",
"value.converter.schemas.enable": "false",
"key.converter": "org.apache.kafka.connect.json.AvroConverter",
"key.converter.schemas.enable": "false",
"connect.cosmos.connection.endpoint": "Error! Hyperlink reference not valid.",
"connect.cosmos.master.key": "<cosmosdbprimarykey>",
"connect.cosmos.databasename": "kafkaconnect",
"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 # 78
You have an Azure Cosmos DB for NoSQL account that has multiple write regions.
You need to receive an alert when requests that target the database exceed the available request units per second (RU/s).
Which Azure Monitor signal should you use?
- A. Document Quota
- B. Data Usage
- C. Region Removed
- D. Metadata Requests
Answer: A
Explanation:
Explanation
Azure Monitor is a service that provides comprehensive monitoring for Azure resources, including Azure Cosmos DB. You can use Azure Monitor to collect, analyze, and alert on metrics and logs from your Azure Cosmos DB account. You can create alerts for Azure Cosmos DB using Azure Monitor based on the metrics, activity log events, or Log Analytics logs on your account1.
For your scenario, if you want to receive an alert when requests that target the database exceed the available request units per second (RU/s), you should use the Document Quota metric. This metric measures the percentage of RU/s consumed by your account or container. You can create an alert rule on this metric from the Azure portal by following these steps2:
* In the Azure portal, select the Azure Cosmos DB account you want to monitor.
* Under the Monitoring section of the sidebar, select Alerts, and then select New alert rule.
* In the Create alert rule pane, fill out the Scope section by selecting your subscription name and resource type (Azure Cosmos DB accounts).
* In the Condition section, select Add condition and choose Document Quota from the list of signals.
* In the Configure signal logic pane, specify the threshold value and operator for your alert condition. For example, you can choose Greater than or equal to 90 as the threshold value and operator to receive an alert when your RU/s consumption reaches 90% or more of your provisioned throughput.
* In the Alert rule details section, specify a name and description for your alert rule.
* In the Actions section, select Add action group and choose how you want to receive notifications for your alert. For example, you can choose Email/SMS/Push/Voice as an action type and enter your email address or phone number as a receiver.
* Review your alert rule settings and select Create alert rule to save it.
NEW QUESTION # 79
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 # 80
You have an Azure Cosmos DB Core (SQL) API account named account1 that has the disableKeyBasedMetadataWriteAccess property enabled.
You are developing an app named App1 that will be used by a user named DevUser1 to create containers in account1. DevUser1 has a non-privileged user account in the Azure Active Directory (Azure AD) tenant.
You need to ensure that DevUser1 can use App1 to create containers in account1.
What should you do? 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/azure/cosmos-db/secure-access-to-data
https://docs.microsoft.com/en-us/rest/api/resources/
NEW QUESTION # 81
You have an Azure Cosmos DB database that contains a container named container 1. The container1 container is configured with a maximum of 20,000 RU/s and currently contains 240 GB of data.
You need to estimate the costs of container1 based on the current usage.
How many RU/s will be charged?
- A. 4.000
- B. 0
- C. 20,000
- D. 1
Answer: A
NEW QUESTION # 82
You have a container in an Azure Cosmos DB for NoSQL account. The database that has a manual throughput of 30,000 request units per second (RU/s). The current consumption details are shewn in the following chart.
Normalized RU Consumption (%) By PartitionKeyRangeID
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 # 83
You have a container named container! in an Azure Cosmos DB for NoSQL account.
You need to provide a user named User1 with the ability to insert items into container1 by using role-based access The solution must use the principle of least privilege.
Which roles should you assign to User1?
- A. Cosmos DB Built-in Data Contributor only
- B. DocumentDB Account Contribute only
- C. Cosmos DB Operator only
- D. DocumentDB Account Contributor and Cosmos DB Built-in Data Contributor
Answer: A
Explanation:
The Cosmos DB Built-in Data Contributor role provides the necessary permissions to insert items into a container in an Azure Cosmos DB for NoSQL account. This role grants the minimum required privileges for the described task, adhering to the principle of least privilege.
NEW QUESTION # 84
You have a database named db1 in an Azure Cosmos DB for NoSQL account named account1. The db1 database has a manual throughput of 4,000 request units per second (RU/s).
You need to move db1 from manual throughput to autoscale throughput by using the Azure CLI. The solution must provide a minimum of 4,000 RU/s and a maximum of 40,000 RU/s.
How should you complete the CLI statements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Migrate
40000
According to the Azure CLI reference1, you need to use the az cosmosdb sql database throughput migrate command to migrate the throughput of the SQL database between autoscale and manually provisioned. You also need to use the --throughput-type parameter to specify the type of throughput to migrate to, and the --max-throughput parameter to specify the maximum throughput resource can scale to (RU/s).
To complete the CLI statements, you should replace the missing values with:
* --throughput-type autoscale
* --max-throughput 40000
The final command should look like this:
az cosmosdb sql database throughput migrate \
--account-name account1 \
--name db1 \
--resource-group rg1 \
--throughput-type autoscale \
--max-throughput 40000
NEW QUESTION # 85
You have the following query.
SELECT * FROM
WHERE c.sensor = "TEMP1"
AND c.value < 22
AND c.timestamp >= 1619146031231
You need to recommend a composite index strategy that will minimize the request units (RUs) consumed by the query.
What should you recommend?
- A. a composite index for (sensor ASC, value ASC, timestamp ASC) and a composite index for (sensor DESC, value DESC, timestamp DESC)
- B. a composite index for (value ASC, sensor ASC) and a composite index for (timestamp ASC, sensor ASC)
- C. a composite index for (sensor ASC, value ASC, timestamp ASC)
- D. a composite index for (sensor ASC, value ASC) and a composite index for (sensor ASC, timestamp ASC)
Answer: D
Explanation:
If a query has a filter with two or more properties, adding a composite index will improve performance.
Consider the following query:
SELECT * FROM c WHERE c.name = "Tim" and c.age > 18
In the absence of a composite index on (name ASC, and age ASC), we will utilize a range index for this query.
We can improve the efficiency of this query by creating a composite index for name and age.
Queries with multiple equality filters and a maximum of one range filter (such as >,<, <=, >=, !=) will utilize the composite index.
Reference:
https://azure.microsoft.com/en-us/blog/three-ways-to-leverage-composite-indexes-in-azure-cosmos-db/
NEW QUESTION # 86
You plan to use a multi-region Azure Cosmos DB for NoSQL account to store data for a new application suite. The suite contains the applications shown in the following table.
Each application should use the weakest consistency level possible.
Which consistency level should you configure for each application? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 87
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