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NEW QUESTION # 84
You need to create a data store for a directory of small and medium-sized businesses (SMBs). The data store must meet the following requirements:
* Store companies and the users employed by them. Each company will have less than 1,000 users.
* Some users have data that is greater than 2 KB.
* Associate each user to only one company.
* Provide the ability to browse by company.
* Provide the ability to browse the users by company.
* Whenever a company or user profile is selected, show a details page for the company and all the related users.
* Be optimized for reading data.
Which design should you implement to optimize the data store for reading data?
Answer: C
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 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 users .
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.
NEW QUESTION # 85
You are designing an Azure Cosmos DB for NoSQL solution to store data from IoT devices.
Writes from the devices will be occur every second. Data will be retained indefinitely.
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?
Answer: D
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.
Incorrect Answers:
A: You will also not like to partition the data on "DateTime", because this will create a hot partition. Imagine you have partitioned the data on time, then for a given minute, all the calls will hit one partition. If you need to retrieve the data for a customer, then it will be a fan-out query because data may be distributed on all the partitions.
B: Senser1Value has only two values.
C: All the devices could have the same manufacturer.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/sql/synthetic-partition-keys
NEW QUESTION # 86
Drag and Drop Question
You have an Azure Cosmos DB for NoSQL database that hosts a container named Container1.
Container1 stores customer documents that have the following structure.
You need to retrieve the city of residence and the age of each customer who is older than 40.
Which three statements should you run in sequence to build the query? To answer, move the appropriate statements from the list of statements to the answer area and arrange them in the correct order.
Answer:
Explanation:
NEW QUESTION # 87
Hotspot Question
You have an Azure Cosmos DB for NoSQL database named DB1 that hosts a container named Container1. The partition key for Container1 is /city.
You are developing a cloud-native app named App1 that will store customer information in DB1.
App1 will perform transactional batch operations to update the items in Container1.
You need to configure App1 to meet the following requirements:
- Ensure that batch operations are rolled back if an item's ETag value
has changed since the value was last read.
- Ensure that all operations in the batch apply to a single partition
key value.
How should you complete the C# code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 88
Hotspot Question
You are migrating a relational database to Azure Cosmos DB for NoSQL. The existing database contains the following relational tables.
The most commonly executed query for each reference table is to return all the items in the reference table.
You need to migrate all the reference tables to Azure Cosmos DB. The solution must minimize the number of containers.
How should you configure storage for the reference tables? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 89
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