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PassTestking facilitates you with three different formats of its DP-420 exam study material. These DP-420 exam dumps formats make it comfortable for every Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420) test applicant to study according to his objectives. Users can download a free Microsoft DP-420 demo to evaluate the formats of our DP-420 practice exam material before purchasing.
Microsoft DP-420 exam covers a range of topics, including Cosmos DB databases, containers, and partitions. It also covers the different data models supported by Cosmos DB, including document, graph, and key-value models. DP-420 Exam also covers best practices for designing and implementing Cosmos DB solutions, including designing partition keys, optimizing queries, and implementing data consistency models.
DP-420 Practice Exam Materials: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB and DP-420 Study Guide - PassTestkingOne of the advantages of taking the PassTestking Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420) practice exam (desktop and web-based) is that it helps applicants to focus on their weak areas. It also helps applicants to track their progress and make improvements. Microsoft DP-420 Practice Exams are particularly helpful in identifying areas where one needs more practice. Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q119-Q124):NEW QUESTION # 119
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 database for orders and a database 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 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: 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 # 120
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, change the consistency level of read requests to consistent prefix.
B. In App1, modify the connection policy settings.
C. In account1, provision a dedicated gateway and integrated cache
D. In account1, change the default consistency level to bounded staleness.
Answer: C
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 complexity1. 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 # 121
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 (value ASC, sensor ASC) and a composite index for (timestamp ASC, sensor ASC)
B. a composite index for (sensor ASC, value ASC) and a composite index for (sensor ASC, timestamp ASC)
C. a composite index for (sensor ASC, value ASC, timestamp ASC) and a composite index for (sensor DESC, value DESC, timestamp DESC)
D. a composite index for (sensor ASC, value ASC, timestamp ASC)
Answer: B
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.
NEW QUESTION # 122
You have a database in an Azure Cosmos DB Core (SQL) API account.
You plan to create a container that will store employee data for 5,000 small businesses. Each business will have up to 25 employees. Each employee item will have an emailAddress value.
You need to ensure that the emailAddress value for each employee within the same company is unique.
To what should you set the partition key and the unique key? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
Explanation
Box 1: CompanyID
After you create a container with a unique key policy, the creation of a new or an update of an existing item resulting in a duplicate within a logical partition is prevented, as specified by the unique key constraint. The partition key combined with the unique key guarantees the uniqueness of an item within the scope of the container.
For example, consider an Azure Cosmos container with Email address as the unique key constraint and CompanyID as the partition key. When you configure the user's email address with a unique key, each item has a unique email address within a given CompanyID. Two items can't be created with duplicate email addresses and with the same partition key value.
Box 2: emailAddress
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/unique-keys
NEW QUESTION # 123
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 # 124
......
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