Steam Analytics
-->
The Azure Stream Analytics service makes it easy to ingest, process, and analyze streaming data from Azure Event Hubs, enabling powerful insights to drive real-time actions. This integration allows you to quickly create a hot-path analytics pipeline. You can use the Azure portal to visualize incoming data and write a Stream Analytics query. Once your query is ready, you can move it into production in only a few clicks.
Key benefits
Steam & Game Stats Updated: April 23, 2021 @ 5:21pm Our on-going goal with Steam is to improve the service we offer customers. We believe that by sharing this data, we'll be able to spot problems earlier, improve the Steam service more efficiently, and ultimately build better products and experiences. Performance by Internet Service Provider (ISP) Shown below are the average download rates for Steam clients on the most popular Internet Service Providers for, sorted by the number of bytes delivered to that network.
Here are the key benefits of Azure Event Hubs and Azure Stream Analytics integration:
See All Results For This Question
- Preview data – You can preview incoming data from an event hub in the Azure portal.
- Test your query – Prepare a transformation query and test it directly in the Azure portal. For the query language syntax, see Stream Analytics Query Language documentation.
- Deploy your query to production – You can deploy the query into production by creating and starting an Azure Stream Analytics job.
End-to-end flow
Wallpaper Engine
Sign in to the Azure portal.
Navigate to your Event Hubs namespace and then navigate to the event hub, which has the incoming data.
Select Process Data on the event hub page.
Select Explore on the Enable real-time insights from events tile.
You see a query page with values already set for the following fields:
Your event hub as an input for the query.
Sample SQL query with SELECT statement.
An output alias to refer to your query test results.
Note
When you use this feature for the first time, this page asks for your permission to create a consumer group and a policy for your event hub to preview incoming data.
Select Create in the Input preview pane as shown in the preceding image.
You'll immediately see a snapshot of the latest incoming data in this tab.
The serialization type in your data is automatically detected (JSON/CSV). You can manually change it as well to JSON/CSV/AVRO.
You can preview incoming data in the table format or raw format.
If your data shown isn't current, select Refresh to see the latest events.
Here is an example of data in the table format:
Here is an example of data in the raw format:
Select Test query to see the snapshot of test results of your query in the Test results tab. You can also download the results.
Write your own query to transform the data. See Stream Analytics Query Language reference.
Once you've tested the query and you want to move it in to production, select Deploy query. To deploy the query, create an Azure Stream Analytics job where you can set an output for your job, and start the job. To create a Stream Analytics job, specify a name for the job, and select Create.
Note
We recommend that you create a consumer group and a policy for each new Azure Stream Analytics job that you create from the Event Hubs page. Consumer groups allow only five concurrent readers, so providing a dedicated consumer group for each job will avoid any errors that might arise from exceeding that limit. A dedicated policy allows you to rotate your key or revoke permissions without impacting other resources.
Your Stream Analytics job is now created where your query is the same that you tested, and input is your event hub.
To complete the pipeline, set the output of the query, and select Start to start the job.
Note
Before starting the job, don't forget to replace the outputalias by the output name you created in Azure Stream Analytics.
Known limitations
While testing your query, the test results take approximately 6 seconds to load. We're working on improving the performance of testing. However, when deployed in production, Azure Stream Analytics will have subsecond latency.
Streaming units
More Videos For Steam Analytics »
Your Azure Stream Analytics job defaults to three streaming units (SUs). To adjust this setting, select Scale on the left menu in the Stream Analytics job page in the Azure portal. To learn more about streaming units, see Understand and adjust Streaming Units.
Next steps
Steam: Game And Player Statistics
To learn more about Stream Analytics queries, see Stream Analytics Query Language