Azure Stream Analytics documentation

About Azure Stream Analytics

Overview

• What is Azure Stream Analytics?
• Azure Stream Analytics solution patterns

Quickstart

• Create a job with Azure portal

Tutorial

• Capture Event Hubs data in parquet format
• Write to a delta table in Data Lake Storage Gen2
• Build real time Power BI dashboards with no code editor
• Analyze fraudulent call data and visualize results

Concept

• Choose a streaming analytics technology
• Choose a development tool for your jobs

Connect a job to a data source

Overview

• Learn about input types

Concept

• Stream input data
• Join reference data for lookups

How-To Guide

• Use reference data from a SQL Database
• Troubleshoot input connections
• Process Apache Kafka for Event Hubs events
• Process data from Azure Event Hubs

Send data to an output sink

Overview

• Learn about output types

Concept

• Output to Azure Cosmos DB
• Output to Azure SQL Database
• Custom blob output partitioning
• Output error handling policies

How-To Guide

• Troubleshoot output connections

Monitor and troubleshoot your job

Concept

• Stream Analytics job metrics
• Stream Analytics dimensions for job metrics

How-To Guide

• Monitor and manage jobs using Azure portal
• Monitor and manage jobs from Visual Studio
• Analyze job performance using job metrics and dimensions
• Debug queries locally using job diagram in Visual Studio Code
• Troubleshoot using resource logs
• Debug using the job diagram
• Troubleshoot data errors

Review temporal concepts

Concept

• Common query patterns
• Understand time handling in Stream Analytics
• Internal checkpoint and replay

Transform data with Stream Analytics queries

Concept

• Introduction to windowing functions
• Introduction to geospatial functions
• Parse JSON and Avro data

How-To Guide

• Troubleshoot query logic
• Write JavaScript user-defined aggregates
• Develop .NET user-defined functions for IoT Edge jobs

Tutorial

• Run a JavaScript user-defined function
• Run a C# user-defined function on a Stream Analytics Edge job

Analyze with machine learning

How-To Guide

• Use machine learning to detect anomalies
• Perform sentiment analysis with Machine Learning Studio (classic)
• Scale jobs with Machine Learning Studio (classic) functions

Create and manage jobs with developer tools

How-To Guide

• Explore jobs with Visual Studio Code
• Test queries with sample data in Visual Studio Code
• Install tools for Visual Studio
• Test queries with sample data in Visual Studio
• Test queries with live data in Visual Studio
• View jobs in Visual Studio
• Develop an IoT Edge job in Visual Studio

video

• Author, manage and test with Visual Studio Code

Try Stream Analytics tutorials and solutions

Tutorial

• Real-time fraud detection
• Trigger an Azure Function

How-To Guide

• Build solutions with geofencing and geospatial aggregation
• Run jobs on IoT Edge
• Build a sentiment analysis solution
• Build an IoT solution
• High-frequency trading simulation
• Alert based on adjustable rule thresholds

Deploy Stream Analytics jobs

How-To Guide

• Set up a CI/CD pipeline with Visual Studio Code
• Set up a CI/CD pipeline with Visual Studio
• Use REST APIs to set up CI/CD for IoT Edge jobs

Scale Stream Analytics jobs

How-To Guide

• Scale with streaming units
• Scale with query parallelization
• Scale jobs to increase throughput
• Optimize processing by repartitioning