Stream Analytics Tools for Visual Studio Code

Author, manage, and test your Stream Analytics job both locally and in the cloud with rich IntelliSense and native source control.

Prerequisites

• Install .NET Core SDK.

Getting started tutorials

• Create an Azure Stream Analytics Job in Visual Studio Code
• Test Stream Analytics queries locally with Visual Studio Code
• Continuously integration and deployment with Stream Analytics CI/CD npm package

Supported Operating Systems

• Windows, macOS, Linux

Features

Create and manage an ASA job

• Create a new Stream Analytics project
• Preview local and live input data
• Export an existing ASA job to the local machine
• Complete Stream Analytics query with IntelliSense
  • Syntax coloring, auto completion, error marker
  • Input column, UDF/UDA, temp result name auto completion
  • Function signature and parameter list
• Configure .NET custom deserializer to read input data
• Create JavaScript function (UDF/UDA)
• Create .NET user-defined function
• Create Azure Machine Learning function

Run/Debug a job locally

• Improve query parallelism using job diagram simulator
• Test job locally using local sample data
• Test job locally against live stream input

Compile and submit job

• Compile job and generate Azure Resource Manager templates
  • Compile in Visual Studio Code
  • Compile on an arbitrary machine using azure-streamanalytics-cicd npm package
• Submit job to Azure

Stream Analytics Explorer

• List jobs and clusters in the cloud
• View inputs, outputs, job query, and job configurations
• Start/stop job, open job view in Azure portal
• View and monitor jobs in cloud with job monitor
  • View job diagram and job summary
  • Test connection to input and output
  • View job query
  • Debug with metrics and logs
  • Move job between clusters

Current Limitations

• Germany Central, Germany North, and all China regions are not supported
• This extension only works for Stream Analytics cloud jobs
• Only Managed Identity authentication is supported for Power BI as output sink
• Only Managed Identity authentication is supported for Azure Data Lake Storage Gen1 as output sink
• Opening a job in Azure portal in Stream Analytics Explorer is not supported on Linux
• Azure Machine Learning Studio is not supported
• The following features are not supported in local testing
  • JavaScript function on Linux and Mac
  • Avro input format is not supported

Create a Stream Analytics project

• Create a new ASA project

  

• Export an existing job to the local machine

  

• Define Stream Analytics query

  

• Add inputs or outputs

  

• Preview inputs

  

• Configure job properties

  

• Create JavaScript function (UDF/UDA)

  

Run/Debug a job locally

• Improve query parallelism using job diagram simulator.

  

• Test locally with sample data.

  

• Test locally with live input and output to local file.

  

• Test locally with live input and output to online adapters (e.g., EventHub, Blob storage or SQL database).

  

Compile Stream Analytics job

• Compile script

  • Syntax check
  • Generate ARM templates for deployment

  

Submit job to Azure

Stream Analytics Explorer

• List jobs in the cloud

• View inputs, outputs, job query and job configurations

• Start, stop, delete, refresh job and open job view in Azure portal

  

• View cloud job diagram and job summary with job monitor

  

• Test connection to input and output

  

• View job query

  

• Debug with metrics and logs

  

npm package for CI/CD

The azure-streamanalytics-cicd NPM package is for auto deployment scenario. It can be used on an arbitrary machine.

Make sure the asaproj.json and JobConfig.json files are in the same folder with the script file.

azure-streamanalytics-cicd build -scriptPath <scriptFullPath> [-outputPath <outputPath>]

Found a Bug?

• Contact ASAToolsFeedback.
• Open a issue on https://github.com/Microsoft/vscode-asa/issues.