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

correct parameter is "isTombstone".

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Step 1: Configure the MaxItemCount in QueryRequestOptions

You can specify the maximum number of items returned by a query by setting the MaxItemCount.

The MaxItemCount is specified per request and tells the query engine to return that number of items

or fewer.

Box 2: Run the query and provide a continuation token

In the .NET SDK and Java SDK you can optionally use continuation tokens as a bookmark for your

query's progress. Azure Cosmos DB query executions are stateless at the server side and can be

resumed at any time using the continuation token.

If the query returns a continuation token, then there are additional query results.

Step 3: Append the results to a variable

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

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Box 1: No

Each physical partition should have its own index, but since no index is used, the query is not cross-

partition.

Box 2: No

Index utilization is 0% and Index Look up time is also zero.

Box 3: Yes

A partition key index will be created, and the query will perform across the partitions.

Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/how-to-query-container

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Box 1: No

Four containers with 1000 RU/s each.

Box 2: No

Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container.

Box 3: Yes

Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container. Can very well add an

additional container.

Reference:

https://docs.microsoft.com/en-us/azure/cosmos-db/plan-manage-costs

https://azure.microsoft.com/en-us/pricing/details/cosmos-db/

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

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.

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

You can facilitate aggregate data by using Change Feed and Azure Functions, and then use it for

reporting.

Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/change-feed