Azure Analysis Services unlocks datasets with potentially billions of rows for non-technical business users to perform interactive analysis. Such large datasets can benefit from features such as asynchronous refresh.
We are pleased to introduce the REST API for Azure Analysis Services. Using any programming language that supports REST calls, you can now perform asynchronous data-refresh operations. This includes synchronization of read-only replicas for query scale out. Please see the blog post Introducing query replica scale-out for Azure Analysis Services for more information on query scale out.
Data-refresh operations can take some time depending on various factors, including data volume and level of optimization using partitions. These operations have traditionally been invoked with existing methods such as using TOM (Tabular Object Model), PowerShell cmdlets for Analysis Services, or TMSL (Tabular Model Scripting Language). The traditional methods may require long-running HTTP connections. A lot of work has been done to ensure the stability of these methods, but given the nature of HTTP, it may be more reliable to avoid long-running HTTP connections from client applications.
The REST API for Azure Analysis Services enables data-refresh operations to be carried out asynchronously. It therefore does not require long-running HTTP connections from client applications. Additionally, there are other built-in features for reliability such as auto retries and batched commits.
Please visit our documention page for details on how to use the REST API for Azure Analysis Services. It covers how to perform asynchronous refreshes, check their status, and cancel them if necessary. Similar information is provided for query-replica synchronization. Additionally, the C# RestApiSample on GitHub code sample is provided.
Source: Azure Blog Feed