JOB SIMULATION HOW TO

You can also adjust Streaming Units to stimulate how streaming nodes are allocated with different SUs. Then you can use Refresh simulation to get the new diagram. However, if you are using aggregate function among all partitions, having a parallel query might not be applicable for your scenarios.įor this example, you add the PartitionId to line#22 and save your change. These are edit suggestions for improving your query parallelism. You must include live input and output in the query.Configure live input and live output for your Stream Analytics job.

If you haven't installed it yet, follow this guide to install. As an example, we're using a nonparallel job that takes the input data from an event hub and sends the results to another event hub. In this tutorial, you learn to improve query performance based on edit suggestions and make it executed in parallel. The Job simulation feature simulates how the job would be running topology in Azure. If you want to learn more about query parallelization, see Leverage query parallelization in Azure Stream Analytics. The query logic partitioning is determined by the keys used for aggregations (GROUP BY). It greatly reduces overall execution time of the query and hence less streaming hours are needed.įor a job to be parallel, all inputs, outputs and query steps must be aligned and use the same partition keys. Query parallelism divides the workload of a query by creating multiple processes (or streaming nodes) and executes it in parallel. You learn to visualize a query execution with different number of streaming units and improve query parallelism based on the edit suggestions.

JOB SIMULATION HOW TO

This article demonstrates how to use the Job Simulation in the Azure portal and Visual Studio Code (VS Code) to evaluate the query parallelism for a Stream Analytics job. One way to improve the performance of an Azure Stream Analytics (ASA) job is to apply parallelism in query.