Storage Table Transactions

This document explains how to perform transactions against Azure Table Storage. Azure Table Storage supports efficient storage of large amounts of structured data. Transactions are crucial for maintaining data integrity, especially when multiple operations need to be performed atomically.

Understanding Transactions in Azure Table Storage

Azure Table Storage supports two main types of transactions:

• Single Entity Operations: Operations that affect a single entity, such as inserting, updating, or deleting one entity. These are inherently atomic.
• Batch Operations: Operations that allow you to group multiple entity operations (inserts, updates, deletes) into a single request. Azure Table Storage guarantees that a batch operation is atomic: either all operations within the batch succeed, or none of them do.

Constraints on Batch Operations

It's important to be aware of the following constraints for batch operations:

• A batch operation can contain up to 100 entities.
• All entities in a batch operation must belong to the same storage account.
• All entities in a batch operation must belong to the same partition. If entities are from different partitions, the batch operation will fail.
• A batch operation cannot include entity group transactions (EGTs).
• A batch operation cannot mix inserts with updates or deletes. You can have a batch of inserts, or a batch of updates/deletes.

Performing Batch Operations

You can perform batch operations using the Azure Storage SDKs for various languages, or via REST APIs.

Example using Azure SDK for .NET

The following example demonstrates how to perform a batch operation to insert multiple entities into a table. This example assumes you have already initialized your CloudTableClient and CloudTable objects.

using Microsoft.Azure.Cosmos.Table;
using System.Collections.Generic;

// Assume 'table' is an initialized CloudTable object
CloudTable table = ...;

// Create entities to insert
List<ITableEntity> entitiesToInsert = new List<ITableEntity>();

// Entity 1
DynamicTableEntity entity1 = new DynamicTableEntity("PartitionKey1", "RowKey1");
entity1.Properties.Add("Description", new EntityProperty("First entity"));
entitiesToInsert.Add(entity1);

// Entity 2
DynamicTableEntity entity2 = new DynamicTableEntity("PartitionKey1", "RowKey2");
entity2.Properties.Add("Value", new EntityProperty(123));
entitiesToInsert.Add(entity2);

// Create the batch operation
TableBatchOperation batchOperation = new TableBatchOperation();
foreach (var entity in entitiesToInsert)
{
    batchOperation.Insert(entity);
}

// Execute the batch operation
try
{
    TableResult[] results = table.ExecuteBatch(batchOperation);
    Console.WriteLine("Batch operation completed successfully.");
    foreach (var result in results)
    {
        Console.WriteLine($"Operation: {result.OperationType}, ETag: {result.Etag}");
    }
}
catch (StorageException ex)
{
    Console.WriteLine($"Batch operation failed: {ex.Message}");
    // Handle the error
}
            

Performing Updates and Deletes in a Batch

You can use Replace, Merge, or Delete operations within a batch. For updates, Replace replaces the entire entity, while Merge updates only the specified properties. If an entity doesn't exist for a delete or update operation, the operation will still be processed as part of the batch but may result in a specific status code or error for that individual operation, while other operations in the batch might succeed or fail based on the overall batch outcome.

Querying Transaction Results

When you execute a batch operation, the result is an array of TableResult objects, one for each operation in the batch. You can iterate through this array to check the status of each individual operation.

Best Practices for Transactions

• Keep batches small: While the limit is 100 entities, smaller batches can be more manageable and reduce the impact of potential failures.
• Group by partition: Always ensure all entities in a batch share the same partition key to avoid failures.
• Use appropriate SDK methods: Leverage the SDK's batch operation capabilities for efficiency and error handling.
• Handle errors gracefully: Implement robust error handling to manage partial failures or unexpected issues.

Next Steps

Learn more about how to model your data effectively for Azure Table Storage and optimize your queries:

• Modeling Data for Azure Table Storage
• Querying Tables and Entities