Microsoft DP-420 Online Practice Questions and Exam Preparation

Microsoft DP-420 Online Questions & Answers

• Question 21:

  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 application to use the change feed processor to read the change feed and you configure the application to trigger the function.

  Does this meet the goal?

  A. Yes

  B. No

  Correct Answer: B

  Instead configure an Azure Monitor alert to trigger the function.

  You can set up alerts from the Azure Cosmos DB pane or the Azure Monitor service in the Azure portal.

  Reference:

  https://docs.microsoft.com/en-us/azure/cosmos-db/create-alerts

• Question 22:

  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 change feed and is triggered by an Azure Cosmos DB trigger

  C. a function that pulls items from the change feed and is triggered by a timer trigger

  D. a function that receives items pushed from the conflicts feed and is triggered by an Azure Cosmos DB trigger

  Correct Answer: D

  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

• Question 23:

  You have the following query.

  SELECT * FROM с 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) and a composite index for (sensor ASC, timestamp ASC)

  B. a composite index for (sensor ASC, value ASC, timestamp ASC) and a composite index for (sensor DESC, value DESC, timestamp DESC)

  C. a composite index for (value ASC, sensor ASC) and a composite index for (timestamp ASC, sensor ASC)

  D. a composite index for (sensor ASC, value ASC, timestamp ASC)

  Correct Answer: A

  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/

• Question 24:

  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. leaseCollectionsThroughput

  C. maxItemsPerInvocation

  D. feedPollDelay

  Correct Answer: D

  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.

  Incorrect Answers:

  A: checkpointInterval: When set, it defines, in milliseconds, the interval between lease checkpoints. Default is always after each Function call.

  C: maxItemsPerInvocation: When set, this property sets the maximum number of items received per Function call. If operations in the monitored collection are performed through stored procedures, transaction scope is preserved when reading items from the change feed. As a result, the number of items received could be higher than the specified value so that the items changed by the same transaction are returned as part of one atomic batch.

  Reference: https://docs.microsoft.com/en-us/azure/azure-functions/functions-bindings-cosmosdb-v2-trigger

• Question 25:

  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. Throughput

  B. Write throughput budget

  C. Batch size

  D. Collection action

  Correct Answer: C

  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

  Reference: https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-cosmos-db

• Question 26:

  You plan to create an Azure Cosmos DB Core (SQL) API account that will use customer-managed keys stored in Azure Key Vault.

  You need to configure an access policy in Key Vault to allow Azure Cosmos DB access to the keys.

  Which three permissions should you enable in the access policy? Each correct answer presents part of the solution.

  NOTE: Each correct selection is worth one point.

  A. Wrap Key

  B. Get

  C. List

  D. Update

  E. Sign

  F. Verify

  G. Unwrap Key

  Correct Answer: ABG

  To Configure customer-managed keys for your Azure Cosmos account with Azure Key Vault:

  Add an access policy to your Azure Key Vault instance:

  1.

  From the Azure portal, go to the Azure Key Vault instance that you plan to use to host your encryption keys. Select Access Policies from the left menu:

  2.

  Select + Add Access Policy.

  3.

  Under the Key permissions drop-down menu, select Get, Unwrap Key, and Wrap Key permissions:

  

  

  Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/how-to-setup-cmk

• Question 27:

  You have an Azure Cosmos DB Core (SQL) API account that is used by 10 web apps.

  You need to analyze the data stored in the account by using Apache Spark to create machine learning models. The solution must NOT affect the performance of the web apps.

  Which two actions should you perform? Each correct answer presents part of the solution.

  NOTE: Each correct selection is worth one point.

  A. In an Apache Spark pool in Azure Synapse, create a table that uses cosmos.olapas the data source.

  B. Create a private endpoint connection to the account.

  C. In an Azure Synapse Analytics serverless SQL pool, create a view that uses OPENROWSETand the CosmosDB provider.

  D. Enable Azure Synapse Link for the account and Analytical store on the container.

  E. In an Apache Spark pool in Azure Synapse, create a table that uses cosmos.oltpas the data source.

  Correct Answer: AD

  Explore analytical store with Apache Spark

  1.

  Navigate to the Data hub.

  2.

  Select the Linked tab (1), expand the Azure Cosmos DB group (if you don't see this, select the Refresh button above), then expand the WoodgroveCosmosDb account (2). Right-click on the transactions container (3), select New notebook (4), then select Load to DataFrame (5).

  3.

  In the generated code within Cell 1 (3), notice that the spark.read format is set to cosmos.olap. This instructs Synapse Link to use the container's analytical store. If we wanted to connect to the transactional store, like to read from the change feed or write to the container, we'd use cosmos.oltp instead.

  Reference: https://github.com/microsoft/MCW-Cosmos-DB-Real-Time-Advanced-Analytics/blob/main/Hands-on%20lab/HOL%20step-by%20step%20-%20Cosmos%20DB%20real-time%20advanced%20analytics.md

• Question 28:

  You have a database in an Azure Cosmos DB Core (SQL) API account. The database is backed up every two hours.

  You need to implement a solution that supports point-in-time restore.

  What should you do first?

  A. Enable Continuous Backup for the account.

  B. Configure the Backup and Restore settings for the account.

  C. Create a new account that has a periodic backup policy.

  D. Configure the Point In Time Restore settings for the account.

  Correct Answer: A

  When creating a new Azure Cosmos DB account, in the Backup policy tab, choose continuous mode to enable the point in time restore functionality for the new account. With the point-in-time restore, data is restored to a new account, currently you can't restore to an existing account.

  Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/provision-account-continuous-backup

• Question 29:

  You have a database in an Azure Cosmos DB Core (SQL) API account.

  You need to create an Azure function that will access the database to retrieve records based on a variable named accountnumber. The solution must protect against SQL injection attacks.

  How should you define the command statement in the function?

  A. cmd = "SELECT * FROM Persons pWHERE p.accountnumber = 'accountnumber'"

  B. cmd = "SELECT * FROM Persons pWHERE p.accountnumber = LIKE @accountnumber"

  C. cmd = "SELECT * FROM Persons pWHERE p.accountnumber = @accountnumber"

  D. cmd = "SELECT * FROM Persons pWHERE p.accountnumber = '" + accountnumber + "'"

  Correct Answer: C

  Azure Cosmos DB supports queries with parameters expressed by the familiar @ notation. Parameterized SQL provides robust handling and escaping of user input, and prevents accidental exposure of data through SQL injection.

  For example, you can write a query that takes lastName and address.state as parameters, and execute it for various values of lastName and address.state based on user input.

  SELECT * FROM Families f WHERE f.lastName = @lastName AND f.address.state = @addressState

  Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/sql-query-parameterized-queries

• Question 30:

  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.CosmosDBSourceConnector"

  B. "key.converter": "org.apache.kafka.connect.json.JsonConverter"

  C. "key.converter": "io.confluent.connect.avro.AvroConverter"

  D. "connect.cosmos.containers.topicmap": "iot#telemetry"

  E. "connect.cosmos.containers.topicmap": "iot"

  F. "connector.class": "com.azure.cosmos.kafka.connect.source.CosmosDBSinkConnector"

  Correct Answer: CDF

  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": "https://.documents.azure.com:443/",

  "connect.cosmos.master.key": "",

  "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/