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We are extending our SQL language to optionally enable users to specify the number of partitions of a stream when performing repartitioning.
Azure Stream Analytics users can now partition output to Azure Blob storage based on custom date and time formats.
Visual Studio tooling for Azure Stream Analytics further enhances the local testing capability to help users test their queries against live data or event streams from cloud sources.
Developers who create Stream Analytics modules for Azure IoT Edge can now write custom C# functions and invoke them right in the query through user-defined functions.
To achieve fully parallel topologies, Azure Stream Analytics will transition SQL writes from serial to parallel operations while simultaneously allowing for batch size customizations.
C# user-defined functions (UDF) support for Azure Stream Analytics on IoT Edge is now available in preview.
Version 1.0 of the Azure Event Hubs package for Node.js is now generally available.
Azure Stream Analytics now supports reference data with a maximum size of 300 MB.
You can partition your Azure Stream Analytics output to Blob storage based on any column in the query.
Azure Stream Analytics now includes machine learning model support for spike and dip detection.
Azure Stream Analytics jobs on IoT Edge support C# custom code.
Session windows are available in Azure Stream Analytics.
Stream Analytics offers substream support to help customers process telemetry streams. The OVER keyword extends the TIMESTAMP BY clause for this purpose.
Stream Analytics tools for Visual Studio include native support for CI/CD processes.
Stream Analytics supports GZIP and Deflate streams.
Azure Stream Analytics now supports egress to Azure Functions.
Stream Analytics offers built-in anomaly detection.
Azure Stream Analytics is available in three additional regions: UK West, Canada Central, and Canada East.
Integration of Azure Stream Analytics with Azure Monitoring is in preview.