Azure 流分析预览功能Azure Stream Analytics preview features

本文汇总了当前以预览版提供的 Azure 流分析的所有功能。This article summarizes all the features currently in preview for Azure Stream Analytics. 建议不要在生产环境中使用预览功能。Using preview features in a production environment isn't recommended.

公共预览版Public previews

以下功能以公共预览版提供。The following features are in public preview. 现在可以使用这些功能,但请勿在生产环境中使用它们。You can take advantage of these features today, but don't use them in your production environment.

联机缩放Online scaling

通过联机缩放,如果需要更改 SU 分配,无需停止作业。With online scaling, you are not required to stop your job if you need to change the SU allocation. 可以增加或减少正在运行的作业的 SU 容量,而无需将其停止。You can increase or decrease the SU capacity of a running job without having to stop it. 这基于客户对流分析目前提供的长时间运行的任务关键管道的承诺。This builds on the customer promise of long-running mission-critical pipelines that Stream Analytics offers today. 有关详细信息,请参阅配置 Azure 流分析流式处理单元For more information, see Configure Azure Stream Analytics Streaming Units.

通过 Azure 机器学习管理的自定义 ML 模型进行实时高性能评分Real-time high performance scoring with custom ML models managed by Azure Machine Learning

Azure 流分析通过利用自定义预先训练的机器学习模型(由 Azure 机器学习管理,并在 Azure Kubernetes 服务 (AKS) 或 Azure 容器实例 (ACI) 中托管),并使用不需要编写代码的工作流,来支持高性能实时评分。Azure Stream Analytics supports high-performance, real-time scoring by leveraging custom pre-trained Machine Learning models managed by Azure Machine Learning, and hosted in Azure Kubernetes Service (AKS) or Azure Container Instances (ACI), using a workflow that does not require you to write code. 注册即可获取预览版Sign up for preview

其他预览Other previews

如若请求,还可以使用以下预览功能。The following features are also available in preview on request.

支持 Azure StackSupport for Azure Stack

此功能在 Azure IoT Edge 运行时启用,利用自定义 Azure Stack 功能,比如以原生方式支持在 Azure Stack 上运行的本地输入和输出(例如事件中心、IoT 中心、Blob 存储)。This feature enabled on the Azure IoT Edge runtime, leverages custom Azure Stack features, such as native support for local inputs and outputs running on Azure Stack (for example Event Hubs, IoT Hub, Blob Storage). 利用这一新的集成,你可以构建混合体系结构,该体系结构可以在数据生成的位置附近分析数据,从而降低延迟并最大程度增加见解。This new integration enables you to build hybrid architectures that can analyze your data close to where it is generated, lowering latency and maximizing insights. 可以通过此功能构建混合体系结构,该体系结构可以在数据生成的位置附近分析数据,从而降低延迟并最大程度增加见解。This feature enables you to build hybrid architectures that can analyze your data close to where it is generated, lowering latency and maximizing insights. 必须注册才能获取此预览版。You must sign up for this preview.