Azure Table storage input bindings for Azure Functions

One entity

The following example shows a C# function that reads a single table row. For every message sent to the queue, the function will be triggered.

The row key value "{queueTrigger}" indicates that the row key comes from the queue message string.

public class TableStorage
{
    public class MyPoco
    {
        public string PartitionKey { get; set; }
        public string RowKey { get; set; }
        public string Text { get; set; }
    }

    [FunctionName("TableInput")]
    public static void TableInput(
        [QueueTrigger("table-items")] string input, 
        [Table("MyTable", "MyPartition", "{queueTrigger}")] MyPoco poco, 
        ILogger log)
    {
        log.LogInformation($"PK={poco.PartitionKey}, RK={poco.RowKey}, Text={poco.Text}");
    }
}

CloudTable

CloudTable is only supported in the Functions v2 and and higher runtimes.

Use a CloudTable method parameter to read the table by using the Azure Storage SDK. Here's an example of a function that queries an Azure Functions log table:

using Microsoft.Azure.WebJobs;
using Microsoft.Azure.WebJobs.Host;
using Microsoft.Extensions.Logging;
using Microsoft.Azure.Cosmos.Table;
using System;
using System.Threading.Tasks;

namespace FunctionAppCloudTable2
{
    public class LogEntity : TableEntity
    {
        public string OriginalName { get; set; }
    }
    public static class CloudTableDemo
    {
        [FunctionName("CloudTableDemo")]
        public static async Task Run(
            [TimerTrigger("0 */1 * * * *")] TimerInfo myTimer, 
            [Table("AzureWebJobsHostLogscommon")] CloudTable cloudTable,
            ILogger log)
        {
            log.LogInformation($"C# Timer trigger function executed at: {DateTime.Now}");

            TableQuery<LogEntity> rangeQuery = new TableQuery<LogEntity>().Where(
                TableQuery.CombineFilters(
                    TableQuery.GenerateFilterCondition("PartitionKey", QueryComparisons.Equal, 
                        "FD2"),
                    TableOperators.And,
                    TableQuery.GenerateFilterCondition("RowKey", QueryComparisons.GreaterThan, 
                        "t")));

            // Execute the query and loop through the results
            foreach (LogEntity entity in 
                await cloudTable.ExecuteQuerySegmentedAsync(rangeQuery, null))
            {
                log.LogInformation(
                    $"{entity.PartitionKey}\t{entity.RowKey}\t{entity.Timestamp}\t{entity.OriginalName}");
            }
        }
    }
}

For more information about how to use CloudTable, see Get started with Azure Table storage.

If you try to bind to CloudTable and get an error message, make sure that you have a reference to the correct Storage SDK version.

IQueryable

IQueryable is only supported in the Functions v1 runtime.

The following example shows a C# function that reads multiple table rows where the MyPoco class derives from TableEntity.

public class TableStorage
{
    public class MyPoco : TableEntity
    {
        public string Text { get; set; }
    }

    [FunctionName("TableInput")]
    public static void TableInput(
        [QueueTrigger("table-items")] string input, 
        [Table("MyTable", "MyPartition")] IQueryable<MyPoco> pocos, 
        ILogger log)
    {
        foreach (MyPoco poco in pocos)
        {
            log.LogInformation($"PK={poco.PartitionKey}, RK={poco.RowKey}, Text={poco.Text}");
        }
    }
}

One entity

The following example shows a table input binding in a function.json file and C# script code that uses the binding. The function uses a queue trigger to read a single table row.

The function.json file specifies a partitionKey and a rowKey. The rowKey value "{queueTrigger}" indicates that the row key comes from the queue message string.

{
  "bindings": [
    {
      "queueName": "myqueue-items",
      "connection": "MyStorageConnectionAppSetting",
      "name": "myQueueItem",
      "type": "queueTrigger",
      "direction": "in"
    },
    {
      "name": "personEntity",
      "type": "table",
      "tableName": "Person",
      "partitionKey": "Test",
      "rowKey": "{queueTrigger}",
      "connection": "MyStorageConnectionAppSetting",
      "direction": "in"
    }
  ],
  "disabled": false
}

The configuration section explains these properties.

Here's the C# script code:

public static void Run(string myQueueItem, Person personEntity, ILogger log)
{
    log.LogInformation($"C# Queue trigger function processed: {myQueueItem}");
    log.LogInformation($"Name in Person entity: {personEntity.Name}");
}

public class Person
{
    public string PartitionKey { get; set; }
    public string RowKey { get; set; }
    public string Name { get; set; }
}

CloudTable

IQueryable isn't supported in the Functions runtime for versions 2.x and higher). An alternative is to use a CloudTable method parameter to read the table by using the Azure Storage SDK. Here's an example of a function that queries an Azure Functions log table:

{
  "bindings": [
    {
      "name": "myTimer",
      "type": "timerTrigger",
      "direction": "in",
      "schedule": "0 */1 * * * *"
    },
    {
      "name": "cloudTable",
      "type": "table",
      "connection": "AzureWebJobsStorage",
      "tableName": "AzureWebJobsHostLogscommon",
      "direction": "in"
    }
  ],
  "disabled": false
}

#r "Microsoft.WindowsAzure.Storage"
using Microsoft.WindowsAzure.Storage.Table;
using System;
using System.Threading.Tasks;
using Microsoft.Extensions.Logging;

public static async Task Run(TimerInfo myTimer, CloudTable cloudTable, ILogger log)
{
    log.LogInformation($"C# Timer trigger function executed at: {DateTime.Now}");

    TableQuery<LogEntity> rangeQuery = new TableQuery<LogEntity>().Where(
    TableQuery.CombineFilters(
        TableQuery.GenerateFilterCondition("PartitionKey", QueryComparisons.Equal, 
            "FD2"),
        TableOperators.And,
        TableQuery.GenerateFilterCondition("RowKey", QueryComparisons.GreaterThan, 
            "a")));

    // Execute the query and loop through the results
    foreach (LogEntity entity in 
    await cloudTable.ExecuteQuerySegmentedAsync(rangeQuery, null))
    {
        log.LogInformation(
            $"{entity.PartitionKey}\t{entity.RowKey}\t{entity.Timestamp}\t{entity.OriginalName}");
    }
}

public class LogEntity : TableEntity
{
    public string OriginalName { get; set; }
}

For more information about how to use CloudTable, see Get started with Azure Table storage.

If you try to bind to CloudTable and get an error message, make sure that you have a reference to the correct Storage SDK version.

IQueryable

The following example shows a table input binding in a function.json file and C# script code that uses the binding. The function reads entities for a partition key that is specified in a queue message.

Here's the function.json file:

{
  "bindings": [
    {
      "queueName": "myqueue-items",
      "connection": "MyStorageConnectionAppSetting",
      "name": "myQueueItem",
      "type": "queueTrigger",
      "direction": "in"
    },
    {
      "name": "tableBinding",
      "type": "table",
      "connection": "MyStorageConnectionAppSetting",
      "tableName": "Person",
      "direction": "in"
    }
  ],
  "disabled": false
}

The configuration section explains these properties.

The C# script code adds a reference to the Azure Storage SDK so that the entity type can derive from TableEntity:

#r "Microsoft.WindowsAzure.Storage"
using Microsoft.WindowsAzure.Storage.Table;
using Microsoft.Extensions.Logging;

public static void Run(string myQueueItem, IQueryable<Person> tableBinding, ILogger log)
{
    log.LogInformation($"C# Queue trigger function processed: {myQueueItem}");
    foreach (Person person in tableBinding.Where(p => p.PartitionKey == myQueueItem).ToList())
    {
        log.LogInformation($"Name: {person.Name}");
    }
}

public class Person : TableEntity
{
    public string Name { get; set; }
}

The following example shows an HTTP triggered function which returns a list of person objects who are in a specified partition in Table storage. In the example, the partition key is extracted from the http route, and the tableName and connection are from the function settings.

public class Person {
    private String PartitionKey;
    private String RowKey;
    private String Name;

    public String getPartitionKey() { return this.PartitionKey; }
    public void setPartitionKey(String key) { this.PartitionKey = key; }
    public String getRowKey() { return this.RowKey; }
    public void setRowKey(String key) { this.RowKey = key; }
    public String getName() { return this.Name; }
    public void setName(String name) { this.Name = name; }
}

@FunctionName("getPersonsByPartitionKey")
public Person[] get(
        @HttpTrigger(name = "getPersons", methods = {HttpMethod.GET}, authLevel = AuthorizationLevel.FUNCTION, route="persons/{partitionKey}") HttpRequestMessage<Optional<String>> request,
        @BindingName("partitionKey") String partitionKey,
        @TableInput(name="persons", partitionKey="{partitionKey}", tableName="%MyTableName%", connection="MyConnectionString") Person[] persons,
        final ExecutionContext context) {

    context.getLogger().info("Got query for person related to persons with partition key: " + partitionKey);

    return persons;
}

The TableInput annotation can also extract the bindings from the json body of the request, like the following example shows.

@FunctionName("GetPersonsByKeysFromRequest")
public HttpResponseMessage get(
        @HttpTrigger(name = "getPerson", methods = {HttpMethod.GET}, authLevel = AuthorizationLevel.FUNCTION, route="query") HttpRequestMessage<Optional<String>> request,
        @TableInput(name="persons", partitionKey="{partitionKey}", rowKey = "{rowKey}", tableName="%MyTableName%", connection="MyConnectionString") Person person,
        final ExecutionContext context) {

    if (person == null) {
        return request.createResponseBuilder(HttpStatus.NOT_FOUND)
                    .body("Person not found.")
                    .build();
    }

    return request.createResponseBuilder(HttpStatus.OK)
                    .header("Content-Type", "application/json")
                    .body(person)
                    .build();
}

The following example uses the Filter to query for persons with a specific name in an Azure Table, and limits the number of possible matches to 10 results.

@FunctionName("getPersonsByName")
public Person[] get(
        @HttpTrigger(name = "getPersons", methods = {HttpMethod.GET}, authLevel = AuthorizationLevel.FUNCTION, route="filter/{name}") HttpRequestMessage<Optional<String>> request,
        @BindingName("name") String name,
        @TableInput(name="persons", filter="Name eq '{name}'", take = "10", tableName="%MyTableName%", connection="MyConnectionString") Person[] persons,
        final ExecutionContext context) {

    context.getLogger().info("Got query for person related to persons with name: " + name);

    return persons;
}

The following example shows a table input binding in a function.json file and JavaScript code that uses the binding. The function uses a queue trigger to read a single table row.

The function.json file specifies a partitionKey and a rowKey. The rowKey value "{queueTrigger}" indicates that the row key comes from the queue message string.

{
  "bindings": [
    {
      "queueName": "myqueue-items",
      "connection": "MyStorageConnectionAppSetting",
      "name": "myQueueItem",
      "type": "queueTrigger",
      "direction": "in"
    },
    {
      "name": "personEntity",
      "type": "table",
      "tableName": "Person",
      "partitionKey": "Test",
      "rowKey": "{queueTrigger}",
      "connection": "MyStorageConnectionAppSetting",
      "direction": "in"
    }
  ],
  "disabled": false
}

The configuration section explains these properties.

Here's the JavaScript code:

module.exports = function (context, myQueueItem) {
    context.log('Node.js queue trigger function processed work item', myQueueItem);
    context.log('Person entity name: ' + context.bindings.personEntity.Name);
    context.done();
};

The following function uses a queue trigger to read a single table row as input to a function.

In this example, the binding configuration specifies an explicit value for the table's partitionKey and uses an expression to pass to the rowKey. The rowKey expression, {queueTrigger}, indicates that the row key comes from the queue message string.

Binding configuration in function.json:

{
  "bindings": [
    {
      "queueName": "myqueue-items",
      "connection": "MyStorageConnectionAppSetting",
      "name": "MyQueueItem",
      "type": "queueTrigger",
      "direction": "in"
    },
    {
      "name": "PersonEntity",
      "type": "table",
      "tableName": "Person",
      "partitionKey": "Test",
      "rowKey": "{queueTrigger}",
      "connection": "MyStorageConnectionAppSetting",
      "direction": "in"
    }
  ],
  "disabled": false
}

PowerShell code in run.ps1:

param($MyQueueItem, $PersonEntity, $TriggerMetadata)
Write-Host "PowerShell queue trigger function processed work item: $MyQueueItem"
Write-Host "Person entity name: $($PersonEntity.Name)"

The following function uses a queue trigger to read a single table row as input to a function.

In this example, binding configuration specifies an explicit value for the table's partitionKey and uses an expression to pass to the rowKey. The rowKey expression, {id} indicates that the row key comes from the queue message string.

Binding configuration in the function.json file:

{
  "scriptFile": "__init__.py",
  "bindings": [
    {
      "name": "messageJSON",
      "type": "table",
      "tableName": "messages",
      "partitionKey": "message",
      "rowKey": "{id}",
      "connection": "AzureWebJobsStorage",
      "direction": "in"
    },
    {
      "authLevel": "function",
      "type": "httpTrigger",
      "direction": "in",
      "name": "req",
      "methods": [
        "get",
        "post"
      ],
      "route": "messages/{id}"
    },
    {
      "type": "http",
      "direction": "out",
      "name": "$return"
    }
  ],
  "disabled": false
}

Python code in the __init__.py file:

import json

import azure.functions as func

def main(req: func.HttpRequest, messageJSON) -> func.HttpResponse:

    message = json.loads(messageJSON)
    return func.HttpResponse(f"Table row: {messageJSON}")

In C# class libraries, use the following attributes to configure a table input binding:

• TableAttribute

  The attribute's constructor takes the table name, partition key, and row key. The attribute can be used on an out parameter or on the return value of the function, as shown in the following example:

  [FunctionName("TableInput")]
  public static void Run(
      [QueueTrigger("table-items")] string input, 
      [Table("MyTable", "Http", "{queueTrigger}")] MyPoco poco, 
      ILogger log)
  {
      ...
  }
  

  You can set the Connection property to specify the storage account to use, as shown in the following example:

  [FunctionName("TableInput")]
  public static void Run(
      [QueueTrigger("table-items")] string input, 
      [Table("MyTable", "Http", "{queueTrigger}", Connection = "StorageConnectionAppSetting")] MyPoco poco, 
      ILogger log)
  {
      ...
  }
  

  For a complete example, see the C# example.

• StorageAccountAttribute

  Provides another way to specify the storage account to use. The constructor takes the name of an app setting that contains a storage connection string. The attribute can be applied at the parameter, method, or class level. The following example shows class level and method level:

  [StorageAccount("ClassLevelStorageAppSetting")]
  public static class AzureFunctions
  {
      [FunctionName("TableInput")]
      [StorageAccount("FunctionLevelStorageAppSetting")]
      public static void Run( //...
  {
      ...
  }
  

The storage account to use is determined in the following order:

• The Table attribute's Connection property.
• The StorageAccount attribute applied to the same parameter as the Table attribute.
• The StorageAccount attribute applied to the function.
• The StorageAccount attribute applied to the class.
• The default storage account for the function app ("AzureWebJobsStorage" app setting).

Attributes are not supported by C# Script.

In the Java functions runtime library, use the @TableInput annotation on parameters whose value would come from Table storage. This annotation can be used with native Java types, POJOs, or nullable values using Optional<T>.

Attributes are not supported by JavaScript.

Attributes are not supported by PowerShell.

Attributes are not supported by Python.

• Read one row in

  Set partitionKey and rowKey. Access the table data by using a method parameter T <paramName>. In C# script, paramName is the value specified in the name property of function.json. T is typically a type that implements ITableEntity or derives from TableEntity. The filter and take properties are not used in this scenario.

• Read one or more rows

  Access the table data by using a method parameter IQueryable<T> <paramName>. In C# script, paramName is the value specified in the name property of function.json. T must be a type that implements ITableEntity or derives from TableEntity. You can use IQueryable methods to do any filtering required. The partitionKey, rowKey, filter, and take properties are not used in this scenario.

  Note

  IQueryable isn't supported in the Functions v2 runtime. An alternative is to use a CloudTable paramName method parameter to read the table by using the Azure Storage SDK. If you try to bind to CloudTable and get an error message, make sure that you have a reference to the correct Storage SDK version.

• Read one row in

  Set partitionKey and rowKey. Access the table data by using a method parameter T <paramName>. In C# script, paramName is the value specified in the name property of function.json. T is typically a type that implements ITableEntity or derives from TableEntity. The filter and take properties are not used in this scenario.

• Read one or more rows

  Access the table data by using a method parameter IQueryable<T> <paramName>. In C# script, paramName is the value specified in the name property of function.json. T must be a type that implements ITableEntity or derives from TableEntity. You can use IQueryable methods to do any filtering required. The partitionKey, rowKey, filter, and take properties are not used in this scenario.

  Note

  IQueryable isn't supported in the Functions v2 runtime. An alternative is to use a CloudTable paramName method parameter to read the table by using the Azure Storage SDK. If you try to bind to CloudTable and get an error message, make sure that you have a reference to the correct Storage SDK version.

The TableInput attribute gives you access to the table row that triggered the function.

Set the filter and take properties. Don't set partitionKey or rowKey. Access the input table entity (or entities) using context.bindings.<BINDING_NAME>. The deserialized objects have RowKey and PartitionKey properties.

Data is passed to the input parameter as specified by the name key in the function.json file. Specifying The partitionKey and rowKey allows you to filter to specific records. See the PowerShell example for more detail.

Table data is passed to the function as a JSON string. De-serialize the message by calling json.loads as shown in the input example.