Quickstart: Build a Spring Data Azure Cosmos DB v3 app to manage Azure Cosmos DB SQL API data

APPLIES TO: SQL API

In this quickstart, you create and manage an Azure Cosmos DB SQL API account from the Azure portal, and by using a Spring Data Azure Cosmos DB v3 app cloned from GitHub. First, you create an Azure Cosmos DB SQL API account using the Azure portal, then create a Spring Boot app using the Spring Data Azure Cosmos DB v3 connector, and then add resources to your Cosmos DB account by using the Spring Boot application. Azure Cosmos DB is a multi-model database service that lets you quickly create and query document, table, key-value, and graph databases with global distribution and horizontal scale capabilities.

Important

These release notes are for version 3 of Spring Data Azure Cosmos DB. You can find release notes for version 2 here.

Spring Data Azure Cosmos DB supports only the SQL API.

See these articles for information about Spring Data on other Azure Cosmos DB APIs:

Prerequisites

Introductory notes

The structure of a Cosmos DB account. Irrespective of API or programming language, a Cosmos DB account contains zero or more databases, a database (DB) contains zero or more containers, and a container contains zero or more items, as shown in the diagram below:

Azure Cosmos account entities

You may read more about databases, containers and items here. A few important properties are defined at the level of the container, among them provisioned throughput and partition key.

The provisioned throughput is measured in Request Units (RUs) which have a monetary price and are a substantial determining factor in the operating cost of the account. Provisioned throughput can be selected at per-container granularity or per-database granularity, however container-level throughput specification is typically preferred. You may read more about throughput provisioning here.

As items are inserted into a Cosmos DB container, the database grows horizontally by adding more storage and compute to handle requests. Storage and compute capacity are added in discrete units known as partitions, and you must choose one field in your documents to be the partition key which maps each document to a partition. The way partitions are managed is that each partition is assigned a roughly equal slice out of the range of partition key values; therefore you are advised to choose a partition key which is relatively random or evenly-distributed. Otherwise, some partitions will see substantially more requests (hot partition) while other partitions see substantially fewer requests (cold partition), and this is to be avoided. You may learn more about partitioning here.

Create a database account

Before you can create a document database, you need to create a SQL API account with Azure Cosmos DB.

  1. From the Azure portal menu or the Home page, select Create a resource.

  2. On the New page, search for and select Azure Cosmos DB.

  3. On the Azure Cosmos DB page, select Create.

  4. In the Create Azure Cosmos DB Account page, enter the basic settings for the new Azure Cosmos account.

    Setting Value Description
    Subscription Subscription name Select the Azure subscription that you want to use for this Azure Cosmos account.
    Resource Group Resource group name Select a resource group, or select Create new, then enter a unique name for the new resource group.
    Account Name A unique name Enter a name to identify your Azure Cosmos account. Because documents.azure.com is appended to the name that you provide to create your URI, use a unique name.

    The name can only contain lowercase letters, numbers, and the hyphen (-) character. It must be between 3-44 characters in length.
    API The type of account to create Select Core (SQL) to create a document database and query by using SQL syntax.

    The API determines the type of account to create. Azure Cosmos DB provides five APIs: Core (SQL) and MongoDB for document data, Gremlin for graph data, Azure Table, and Cassandra. Currently, you must create a separate account for each API.

    Learn more about the SQL API.
    Location The region closest to your users Select a geographic location to host your Azure Cosmos DB account. Use the location that is closest to your users to give them the fastest access to the data.
    Capacity mode Provisioned throughput or Serverless Select Provisioned throughput to create an account in provisioned throughput mode. Select Serverless to create an account in serverless mode.
    Apply Azure Cosmos DB free tier discount Apply or Do not apply With Azure Cosmos DB free tier, you will get the first 1000 RU/s and 25 GB of storage for free in an account. Learn more about free tier.

    Note

    You can have up to one free tier Azure Cosmos DB account per Azure subscription and must opt-in when creating the account. If you do not see the option to apply the free tier discount, this means another account in the subscription has already been enabled with free tier.

    The new account page for Azure Cosmos DB

  5. In the Global Distribution tab, configure the following details. You can leave the default values for the purpose of this quickstart:

    Setting Value Description
    Geo-Redundancy Disable Enable or disable global distribution on your account by pairing your region with a pair region. You can add more regions to your account later.
    Multi-region Writes Disable Multi-region writes capability allows you to take advantage of the provisioned throughput for your databases and containers across the globe.

    Note

    The following options are not available if you select Serverless as the Capacity mode:

    • Apply Free Tier Discount
    • Geo-redundancy
    • Multi-region Writes
  6. Optionally you can configure additional details in the following tabs:

    • Networking - Configure access from a virtual network.
    • Backup Policy - Configure either periodic or continuous backup policy.
    • Encryption - Use either service-managed key or a customer-managed key.
    • Tags - Tags are name/value pairs that enable you to categorize resources and view consolidated billing by applying the same tag to multiple resources and resource groups.
  7. Select Review + create.

  8. Review the account settings, and then select Create. It takes a few minutes to create the account. Wait for the portal page to display Your deployment is complete.

    The Azure portal Notifications pane

  9. Select Go to resource to go to the Azure Cosmos DB account page.

    The Azure Cosmos DB account page

Add a container

You can now use the Data Explorer tool in the Azure portal to create a database and container.

  1. Select Data Explorer > New Container.

    The Add Container area is displayed on the far right, you may need to scroll right to see it.

    The Azure portal Data Explorer, Add Container pane

  2. In the Add container page, enter the settings for the new container.

    Setting Suggested value Description
    Database ID ToDoList Enter Tasks as the name for the new database. Database names must contain from 1 through 255 characters, and they cannot contain /, \\, #, ?, or a trailing space. Check the Share throughput across containers option, it allows you to share the throughput provisioned on the database across all the containers within the database. This option also helps with cost savings.
    Database throughput You can provision Autoscale or Manual throughput. Manual throughput allows you to scale RU/s yourself whereas autoscale throughput allows the system to scale RU/s based on usage. Select Manual for this example.

    Leave the throughput at 400 request units per second (RU/s). If you want to reduce latency, you can scale up the throughput later by estimating the required RU/s with the capacity calculator.

    Note: This setting is not available when creating a new container in a serverless account.
    Container ID Items Enter Items as the name for your new container. Container IDs have the same character requirements as database names.
    Partition key /category The sample described in this article uses /category as the partition key.

    Don't add Unique keys or turn on Analytical store for this example. Unique keys let you add a layer of data integrity to the database by ensuring the uniqueness of one or more values per partition key. For more information, see Unique keys in Azure Cosmos DB. Analytical store is used to enable large-scale analytics against operational data without any impact to your transactional workloads.

    Select OK. The Data Explorer displays the new database and container.

Add sample data

You can now add data to your new container using Data Explorer.

  1. From the Data Explorer, expand the Tasks database, expand the Items container. Select Items, and then select New Item.

    Create new documents in Data Explorer in the Azure portal

  2. Now add a document to the container with the following structure.

    {
        "id": "1",
        "category": "personal",
        "name": "groceries",
        "description": "Pick up apples and strawberries.",
        "isComplete": false
    }
    
  3. Once you've added the json to the Documents tab, select Save.

    Copy in json data and select Save in Data Explorer in the Azure portal

  4. Create and save one more document where you insert a unique value for the id property, and change the other properties as you see fit. Your new documents can have any structure you want as Azure Cosmos DB doesn't impose any schema on your data.

Query your data

You can use queries in Data Explorer to retrieve and filter your data.

  1. At the top of the Items tab in Data Explorer, review the default query SELECT * FROM c. This query retrieves and displays all documents from the container ordered by ID.

    Default query in Data Explorer is SELECT * FROM c

  2. To change the query, select Edit Filter, replace the default query with ORDER BY c._ts DESC, and then select Apply Filter.

    Change the default query by adding ORDER BY c._ts DESC and clicking Apply Filter

    The modified query displays the documents in descending order based on their time stamp, so now your second document is listed first.

    Changed query to ORDER BY c._ts DESC and clicking Apply Filter

If you're familiar with SQL syntax, you can enter any supported SQL queries in the query predicate box. You can also use Data Explorer to create stored procedures, UDFs, and triggers for server-side business logic.

Data Explorer provides easy Azure portal access to all of the built-in programmatic data access features available in the APIs. You also use the portal to scale throughput, get keys and connection strings, and review metrics and SLAs for your Azure Cosmos DB account.

Clone the sample application

Now let's switch to working with code. Let's clone a SQL API app from GitHub, set the connection string, and run it. You'll see how easy it is to work with data programmatically.

Run the following command to clone the sample repository. This command creates a copy of the sample app on your computer.

git clone https://github.com/Azure-Samples/azure-spring-data-cosmos-java-sql-api-getting-started.git

Review the code

This step is optional. If you're interested in learning how the database resources are created in the code, you can review the following snippets. Otherwise, you can skip ahead to Run the app .

Application configuration file

Here we showcase how Spring Boot and Spring Data enhance user experience - the process of establishing a Cosmos client and connecting to Cosmos resources is now config rather than code. At application startup Spring Boot handles all of this boilerplate using the settings in application.properties:

cosmos.uri=${ACCOUNT_HOST}
cosmos.key=${ACCOUNT_KEY}
cosmos.secondaryKey=${SECONDARY_ACCOUNT_KEY}

dynamic.collection.name=spel-property-collection
# Populate query metrics
cosmos.queryMetricsEnabled=true

Once you create an Azure Cosmos DB account, database, and container, just fill-in-the-blanks in the config file and Spring Boot/Spring Data will automatically do the following: (1) create an underlying Java SDK CosmosClient instance with the URI and key, and (2) connect to the database and container. You're all set - no more resource management code!

Java source

The Spring Data value-add also comes from its simple, clean, standardized and platform-independent interface for operating on datastores. Building on the Spring Data GitHub sample linked above, below are CRUD and query samples for manipulating Azure Cosmos DB documents with Spring Data Azure Cosmos DB.

  • Item creation and updates by using the save method.

    
    logger.info("Saving user : {}", testUser1);
    userRepository.save(testUser1);
    
    
  • Point-reads using the derived query method defined in the repository. The findByIdAndLastName performs point-reads for UserRepository. The fields mentioned in the method name cause Spring Data to execute a point-read defined by the id and lastName fields:

    
    // to find by Id, please specify partition key value if collection is partitioned
    final User result = userRepository.findByIdAndLastName(testUser1.getId(), testUser1.getLastName());
    logger.info("Found user : {}", result);
    
    
  • Item deletes using deleteAll:

    
    userRepository.deleteAll();
    
    
  • Derived query based on repository method name. Spring Data implements the UserRepository findByFirstName method as a Java SDK SQL query on the firstName field (this query could not be implemented as a point-read):

    
    Flux<User> users = reactiveUserRepository.findByFirstName("testFirstName");
    users.map(u -> {
        logger.info("user is : {}", u);
        return u;
    }).subscribe();
    
    

Run the app

Now go back to the Azure portal to get your connection string information and launch the app with your endpoint information. This enables your app to communicate with your hosted database.

  1. In the git terminal window, cd to the sample code folder.

    cd azure-spring-data-cosmos-java-sql-api-getting-started/azure-spring-data-cosmos-java-getting-started/
    
  2. In the git terminal window, use the following command to install the required Spring Data Azure Cosmos DB packages.

    mvn clean package
    
  3. In the git terminal window, use the following command to start the Spring Data Azure Cosmos DB application:

    mvn spring-boot:run
    
  4. The app loads application.properties and connects the resources in your Azure Cosmos DB account.

  5. The app will perform point CRUD operations described above.

  6. The app will perform a derived query.

  7. The app doesn't delete your resources. Switch back to the portal to clean up the resources from your account if you want to avoid incurring charges.

Review SLAs in the Azure portal

The Azure portal monitors your Cosmos DB account throughput, storage, availability, latency, and consistency. Charts for metrics associated with an Azure Cosmos DB Service Level Agreement (SLA) show the SLA value compared to actual performance. This suite of metrics makes monitoring your SLAs transparent.

To review metrics and SLAs:

  1. Select Metrics in your Cosmos DB account's navigation menu.

  2. Select a tab such as Latency, and select a timeframe on the right. Compare the Actual and SLA lines on the charts.

    Azure Cosmos DB metrics suite

  3. Review the metrics on the other tabs.

Clean up resources

When you're done with your app and Azure Cosmos DB account, you can delete the Azure resources you created so you don't incur more charges. To delete the resources:

  1. In the Azure portal Search bar, search for and select Resource groups.

  2. From the list, select the resource group you created for this quickstart.

    Select the resource group to delete

  3. On the resource group Overview page, select Delete resource group.

    Delete the resource group

  4. In the next window, enter the name of the resource group to delete, and then select Delete.

Next steps

In this quickstart, you've learned how to create an Azure Cosmos DB SQL API account, create a document database and container using the Data Explorer, and run a Spring Data app to do the same thing programmatically. You can now import additional data into your Azure Cosmos DB account.

Trying to do capacity planning for a migration to Azure Cosmos DB? You can use information about your existing database cluster for capacity planning.