Implement a query operation by using a continuation token

When working with large datasets in Microsoft Azure Cosmos DB, it’s essential to implement efficient querying mechanisms. One such mechanism is the use of a continuation token. In this article, we will guide you through the process of designing and implementing native applications that utilize a continuation token in Azure Cosmos DB.

Prerequisites

Before you can start implementing the query operation, make sure you have set up an Azure Cosmos DB account. You can either create a new account or use an existing one. Additionally, create a container within your Cosmos DB account to store the data. Define the schema, indexing policies, and other settings based on your application requirements.

Inserting Data into the Container

In order to illustrate the query operation, let’s assume that we have already inserted some sample data into the container. We can use the .NET SDK to insert a document into the container:

csharp
using Microsoft.Azure.Cosmos;

// Create a new CosmosClient instance
CosmosClient client = new CosmosClient(“connection-string”);

// Get the container reference
Container container = client.GetContainer(“database-id”, “container-id”);

// Create a new document
MyDocument document = new MyDocument
{
Id = “1”,
Name = “John Doe”
};

// Insert the document into the container
await container.CreateItemAsync(document);

Implementing the Query Operation

Now, let’s implement the query operation that utilizes a continuation token:

csharp
using Microsoft.Azure.Cosmos;
using System;

// Create a new CosmosClient instance
CosmosClient client = new CosmosClient(“connection-string”);

// Get the container reference
Container container = client.GetContainer(“database-id”, “container-id”);

// Define the SQL query
string query = “SELECT * FROM c”;

// Set the feed options
QueryRequestOptions requestOptions = new QueryRequestOptions
{
MaxItemCount = 10, // Number of items to retrieve per page
MaxConcurrency = 1, // Number of concurrent operations
PartitionKey = new PartitionKey(“partition-key-value”)
};

// Execute the query
FeedIterator queryIterator = container.GetItemQueryIterator(
query,
continuationToken: null, // Set to null for the first page
requestOptions);

while (queryIterator.HasMoreResults)
{
FeedResponse response = await queryIterator.ReadNextAsync();

// Process the retrieved documents
foreach (MyDocument document in response)
{
Console.WriteLine(document.Name);
}

// Get the continuation token for the next page
string continuationToken = response.ContinuationToken;
}

Let’s break down the code:

• Step 1: We create a new instance of the CosmosClient and obtain a reference to the container where the data is stored.
• Step 2: We define the SQL query that selects all items from the container.
• Step 3: We set the feed options, including the maximum number of items to retrieve per page (in this example, 10), the maximum concurrency level (1 operation at a time), and the partition key value.
• Step 4: We initialize the query iterator by passing the query, null for the initial continuation token (as this is the first page), and the feed options to the GetItemQueryIterator method.
• Step 5: We iterate through the results while there are more pages available.
• Step 6:Inside the loop, we process the retrieved documents as required. In this example, we simply print the document names.
• Step 7: After processing the documents, we obtain the continuation token from the response using response.ContinuationToken. This token can be used to retrieve the next page of results in subsequent iterations.
• Step 8: The process continues until all data has been retrieved.

By utilizing the continuation token, your application can fetch query results in a paginated manner, optimizing performance and reducing strain on system resources.

As a conclusion, implementing a query operation with a continuation token is a powerful technique to retrieve large datasets from Azure Cosmos DB efficiently. By following the steps outlined in this article, you can design and build native applications that leverage the scalability and performance benefits of Azure Cosmos DB.