DP-420 Online Practice Questions and Answers

Correct Answer:

Box 1: Serverless capacity mode Azure Cosmos DB serverless best fits scenarios where you expect intermittent and unpredictable traffic with long idle times. Because provisioning capacity in such situations isn't required and may be cost-prohibitive, Azure Cosmos DB serverless should be considered in the following use-cases:

1.

Getting started with Azure Cosmos DB

2.

Running applications with bursty, intermittent traffic that is hard to forecast, or low (<10%) average-to-peak traffic ratio

3.

Developing, testing, prototyping and running in production new applications where the traffic pattern is unknown

4.

Integrating with serverless compute services like Azure Functions

Box 2: Provisioned throughput capacity mode and autoscale throughput The use cases of autoscale include: Variable or unpredictable workloads: When your workloads have variable or unpredictable spikes in usage, autoscale helps by automatically scaling up and down based on usage. Examples include retail websites that have different traffic patterns depending on seasonality; IOT workloads that have spikes at various times during the day; line of business applications that see peak usage a few times a month or year, and more. With autoscale, you no longer need to manually provision for peak or average capacity.

Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/serverless https://docs.microsoft.com/en-us/azure/cosmos-db/provision-throughput-autoscale#use-cases-of-autoscale

Correct Answer:

Box 1: country

The country field is filterable.

Note: filterable: Indicates whether to enable the field to be referenced in $filter queries. Filterable differs from searchable in how strings are handled. Fields of type Edm.String or Collection(Edm.String) that are filterable do not undergo lexical

analysis, so comparisons are for exact matches only.

Box 2: name

The name field is not Retrievable.

Retrievable: Indicates whether the field can be returned in a search result. Set this attribute to false if you want to use a field (for example, margin) as a filter, sorting, or scoring mechanism but do not want the field to be visible to the end user.

Note: searchable: Indicates whether the field is full-text searchable and can be referenced in search queries.

Reference:

https://docs.microsoft.com/en-us/rest/api/searchservice/create-index

Correct Answer: A

Correct Answer: A

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 "all the properties of the updated items"

Correct Answer: A

The solution is incorrect because there is no "isTom" parameter in the Azure Cosmos DB SDK. The correct parameter is "isTombstone".

Correct Answer: B

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 optimize the data store for reading data, 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 design that you could implement is B. In a company container, create a document for each company. Embed the users into company documents. Use the company ID as the partition key.

This design has the following advantages:

It stores companies and users as self-contained documents that can be easily retrieved by company ID1.

It avoids storing redundant data or creating additional containers for users1. It allows you to browse by company and browse the users by company with simple queries1.

It shows a details page for the company and all the related users by fetching a single document1.

It leverages the benefits of embedding data, such as reducing the number of requests, improving query performance, and simplifying data consistency2.

This design also has some limitations, such as:

It may not be suitable for some users who 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 users need to be associated with more than one

company or queried independently from companies2. It may not be scalable for companies that have more than 1,000 users, as it could result in hot partitions or throttling2. Depending on your specific use case and requirements, you may

need to adjust this design 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.

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/

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

Correct Answer: D

Explanation:

Time to live for containers and items

The time to live value is set in seconds, and it is interpreted as a delta from the time that an item was last modified. You can set time to live on a container or an item within the container:

Time to Live on a container (set using DefaultTimeToLive):

If missing (or set to null), items are not expired automatically.

If present and the value is set to "-1", it is equal to infinity, and items don't expire by default.

If present and the value is set to some non-zero number "n" – items will expire "n" seconds after their last modified time.

Reference:

https://learn.microsoft.com/en-us/azure/cosmos-db/nosql/time-to-live

Correct Answer: B

Explanation:

Set up a CI/CD pipeline with the Azure Cosmos DB Emulator build task in Azure DevOps

The Azure Cosmos DB Emulator provides a local environment that emulates the Azure Cosmos DB service for development purposes. The emulator allows you to develop and test your application locally, without creating an Azure

subscription or incurring any costs.

Reference:

https://learn.microsoft.com/en-us/azure/cosmos-db/tutorial-setup-ci-cd