Quickstart: Build a API for Table app with Node.js and Azure Cosmos DB

APPLIES TO: Table

In this quickstart, you create an Azure Cosmos DB for Table account, and use Data Explorer and a Node.js app cloned from GitHub to create tables and entities. Azure Cosmos DB is a multi-model database service that lets you quickly create and query document, table, key-value, and graph databases with multiple-region distribution and horizontal scale capabilities.

Prerequisites

• An Azure account with an active subscription. Create a trial subscription.
• Node.js 0.10.29+ .
• Git.

Sample application

The sample application for this tutorial may be cloned or downloaded from the repository https://github.com/Azure-Samples/msdocs-azure-data-tables-sdk-js. Both a starter and completed app are included in the sample repository.

git clone https://github.com/Azure-Samples/msdocs-azure-data-tables-sdk-js

The sample application uses weather data as an example to demonstrate the capabilities of the API for Table. Objects representing weather observations are stored and retrieved using the API for Table, including storing objects with additional properties to demonstrate the schemaless capabilities of the API for Table.

1 - Create an Azure Cosmos DB account

You first need to create an Azure Cosmos DB Tables API account that will contain the table(s) used in your application. This can be done using the Azure portal, Azure CLI, or Azure PowerShell.

2 - Create a table

Next, you need to create a table within your Azure Cosmos DB account for your application to use. Unlike a traditional database, you only need to specify the name of the table, not the properties (columns) in the table. As data is loaded into your table, the properties (columns) will be automatically created as needed.

3 - Get Azure Cosmos DB connection string

To access your table(s) in Azure Cosmos DB, your app will need the table connection string for the CosmosDB Storage account. The connection string can be retrieved using the Azure portal, Azure CLI or Azure PowerShell.

4 - Install the Azure Data Tables SDK for JS

To access the Azure Cosmos DB for Table from a nodejs application, install the Azure Data Tables SDK package.

  npm install @azure/data-tables

5 - Configure the Table client in env.js file

Copy your Azure Cosmos DB or Storage account connection string from the Azure portal, and create a TableServiceClient object using your copied connection string. Switch to folder 1-strater-app or 2-completed-app. Then, add the value of the corresponding environment variables in configure/env.js file.

const env = {
  connectionString:"A connection string to an Azure Storage or Azure Cosmos DB account.",
  tableName: "WeatherData",
};

The Azure SDK communicates with Azure using client objects to execute different operations against Azure. The TableClient class is the class used to communicate with the Azure Cosmos DB for Table. An application will typically create a single serviceClient object per table to be used throughout the application.

const { TableClient } = require("@azure/data-tables");
const env = require("../configure/env");
const serviceClient = TableClient.fromConnectionString(
  env.connectionString,
  env.tableName
);

---

6 - Implement Azure Cosmos DB table operations

All Azure Cosmos DB table operations for the sample app are implemented in the serviceClient object located in tableClient.js file under service directory.

const { TableClient } = require("@azure/data-tables");
const env = require("../configure/env");
const serviceClient = TableClient.fromConnectionString(
  env.connectionString,
  env.tableName
);

Get rows from a table

The serviceClient object contains a method named listEntities which allows you to select rows from the table. In this example, since no parameters are being passed to the method, all rows will be selected from the table.

const allRowsEntities = serviceClient.listEntities();

Filter rows returned from a table

To filter the rows returned from a table, you can pass an OData style filter string to the listEntities method. For example, if you wanted to get all of the weather readings for Shanghai between midnight July 1, 2021 and midnight July 2, 2021 (inclusive) you would pass in the following filter string.

PartitionKey eq 'Shanghai' and RowKey ge '2021-07-01 12:00' and RowKey le '2021-07-02 12:00'

You can view all OData filter operators on the OData website in the section Filter System Query Option.

When request.args parameter is passed to the listEntities method in the serviceClient class, it creates a filter string for each non-null property value. It then creates a combined filter string by joining all of the values together with an "and" clause. This combined filter string is passed to the listEntities method on the serviceClient object and only rows matching the filter string will be returned. You can use a similar method in your code to construct suitable filter strings as required by your application.

const filterEntities = async function (option) {
  /*
    You can query data according to existing fields
    option provides some conditions to query,eg partitionKey, rowKeyDateTimeStart, rowKeyDateTimeEnd
    minTemperature, maxTemperature, minPrecipitation, maxPrecipitation
  */
  const filterEntitiesArray = [];
  const filters = [];
  if (option.partitionKey) {
    filters.push(`PartitionKey eq '${option.partitionKey}'`);
  }
  if (option.rowKeyDateTimeStart) {
    filters.push(`RowKey ge '${option.rowKeyDateTimeStart}'`);
  }
  if (option.rowKeyDateTimeEnd) {
    filters.push(`RowKey le '${option.rowKeyDateTimeEnd}'`);
  }
  if (option.minTemperature !== null) {
    filters.push(`Temperature ge ${option.minTemperature}`);
  }
  if (option.maxTemperature !== null) {
    filters.push(`Temperature le ${option.maxTemperature}`);
  }
  if (option.minPrecipitation !== null) {
    filters.push(`Precipitation ge ${option.minPrecipitation}`);
  }
  if (option.maxPrecipitation !== null) {
    filters.push(`Precipitation le ${option.maxPrecipitation}`);
  }
  const res = serviceClient.listEntities({
    queryOptions: {
      filter: filters.join(" and "),
    },
  });
  for await (const entity of res) {
    filterEntitiesArray.push(entity);
  }

  return filterEntitiesArray;
};

Insert data using a TableEntity object

The simplest way to add data to a table is by using a TableEntity object. In this example, data is mapped from an input model object to a TableEntity object. The properties on the input object representing the weather station name and observation date/time are mapped to the PartitionKey and RowKey properties respectively which together form a unique key for the row in the table. Then the additional properties on the input model object are mapped to dictionary properties on the TableEntity object. Finally, the createEntity method on the serviceClient object is used to insert data into the table.

Modify the insertEntity function in the example application to contain the following code.

const insertEntity = async function (entity) {

  await serviceClient.createEntity(entity);

};

Upsert data using a TableEntity object

If you try to insert a row into a table with a partition key/row key combination that already exists in that table, you will receive an error. For this reason, it is often preferable to use the upsertEntity instead of the createEntity method when adding rows to a table. If the given partition key/row key combination already exists in the table, the upsertEntity method will update the existing row. Otherwise, the row will be added to the table.

const upsertEntity = async function (entity) {

  await serviceClient.upsertEntity(entity, "Merge");

};

Insert or upsert data with variable properties

One of the advantages of using the Azure Cosmos DB for Table is that if an object being loaded to a table contains any new properties then those properties are automatically added to the table and the values stored in Azure Cosmos DB. There is no need to run DDL statements like ALTER TABLE to add columns as in a traditional database.

This model gives your application flexibility when dealing with data sources that may add or modify what data needs to be captured over time or when different inputs provide different data to your application. In the sample application, we can simulate a weather station that sends not just the base weather data but also some additional values. When an object with these new properties is stored in the table for the first time, the corresponding properties (columns) will be automatically added to the table.

To insert or upsert such an object using the API for Table, map the properties of the expandable object into a TableEntity object and use the createEntity or upsertEntity methods on the serviceClient object as appropriate.

In the sample application, the upsertEntity function can also implement the function of insert or upsert data with variable properties

const insertEntity = async function (entity) {
  await serviceClient.createEntity(entity);
};

const upsertEntity = async function (entity) {
  await serviceClient.upsertEntity(entity, "Merge");
};

Update an entity

Entities can be updated by calling the updateEntity method on the serviceClient object.

In the sample app, this object is passed to the upsertEntity method in the serviceClient object. It updates that entity object and uses the upsertEntity method save the updates to the database.

const updateEntity = async function (entity) {
  await serviceClient.updateEntity(entity, "Replace");
};

7 - Run the code

Run the sample application to interact with the Azure Cosmos DB for Table. The first time you run the application, there will be no data because the table is empty. Use any of the buttons at the top of application to add data to the table.

Selecting the Insert using Table Entity button opens a dialog allowing you to insert or upsert a new row using a TableEntity object.

Selecting the Insert using Expandable Data button brings up a dialog that enables you to insert an object with custom properties, demonstrating how the Azure Cosmos DB for Table automatically adds properties (columns) to the table when needed. Use the Add Custom Field button to add one or more new properties and demonstrate this capability.

Use the Insert Sample Data button to load some sample data into your Azure Cosmos DB Table.

Select the Filter Results item in the top menu to be taken to the Filter Results page. On this page, fill out the filter criteria to demonstrate how a filter clause can be built and passed to the Azure Cosmos DB for Table.

Clean up resources

When you are finished with the sample application, you should remove all Azure resources related to this article from your Azure account. You can do this by deleting the resource group.

Next steps

In this quickstart, you've learned how to create an Azure Cosmos DB account, create a table using the Data Explorer, and run an app. Now you can query your data using the API for Table.