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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Maintain an Azure Cosmos DB solution | 25-30% | - Monitor and troubleshoot Azure Cosmos DB solutions
|
| Topic 2: Integrate an Azure Cosmos DB solution | 5-10% | - Enable analytical workloads
|
| Topic 3: Optimize an Azure Cosmos DB solution | 15-20% | - Define and implement indexing strategy
|
| Topic 4: Design and implement data models | 35-40% | - Design a data partitioning strategy
|
| Topic 5: Design and implement data distribution | 5-10% | - Design and implement multi-region writes
|
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NEW QUESTION # 270
You have an Azure Cosmos DB for NoSQL account that frequently receives the same three queries.
You need to configure indexing to minimize RUs consumed by the queries.
Which type of index should you use for each query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1 = Range Azure Cosmos DB supports three types of indexes: range, spatial and composite. For the query you provided, which is an equality query on a single property, the best type of index to use is range. Range index is based on an ordered tree-like structure and it is used for equality queries, range queries and checking for the presence of a property1. Range index also supports any string or number2.
Box 2 = Composite
Azure Cosmos DB supports three types of indexes: range, spatial and composite. For the query you provided, which is an order by query on two properties, the best type of index to use is composite. Composite index is used for optimizing order by queries on multiple properties1. Composite index allows you to specify a list of property paths and sort orders that are used for ordering items2.
Box 3 = spatial
Azure Cosmos DB supports three types of indexes: range, spatial and composite. For the query you provided, which is a spatial query on a point property, the best type of index to use is spatial. Spatial index is used for querying items based on their location or proximity to a given point1. Spatial index supports point, polygon and linestring data types2.
NEW QUESTION # 271
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 database in an Azure Cosmos DB for NoSQL account that is configured for multi- region writes.
You need to use the Azure Cosmos DB SDK to implement the conflict resolution policy for a container. The solution must ensure that any conflicts are sent to the conflicts feed.
Solution: You set ConflictResolutionMode to Custom. You set ResolutionProcedure to a custom stored procedure. You configure the custom stored procedure to use the isTombstone parameter to resolve conflicts.
Does this meet the goal?
Answer: A
NEW QUESTION # 272
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 the function to have an Azure CosmosDB trigger.
Does this meet the goal?
Answer: A
Explanation:
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.
NEW QUESTION # 273
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?
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.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/sql-query-is-number
NEW QUESTION # 274
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.
Answer: C
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 # 275
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