In this tutorial, we will learn to use the Azure Data Factory debug feature to test the pipeline activities during the development stage.
In the previous article, How to schedule Azure Data Factory pipeline executions using Triggers, we discussed the three main types of the Azure Data Factory triggers, how to configure it then use it to schedule a pipeline.
In this article, we will see how to use the Azure Data Factory debug feature to test the pipeline activities during the development stage.
When developing complex and multi-stage Azure Data Factory pipelines, it becomes harder to test the functionality and the performance of the pipeline as one block. Instead, it is highly recommended to test such pipelines when you develop each stage, so that you can make sure that this stage is working as expected, returning the correct result with the best performance, before publishing the changes to the data factory.
Take into consideration that debugging any pipeline activity will execute that activity and perform the action configured in it. For example, if this activity is a copy activity from an Azure Storage Account to an Azure SQL Database, the data will be copied, but the only difference is that the pipeline execution logs in the debug mode will be written to the pipeline output tab only and will not be shown under the pipeline runs in the Monitor page.
SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
In this article, you learn how to set up Azure Data Sync services. In addition, you will also learn how to create and set up a data sync group between Azure SQL database and on-premises SQL Server.
In this article, we will learn to access data in an Azure SQL database from Azure Data Lake Analytics.
This tutorial will help you understand the process to accept an incoming or received data share of Azure SQL Database and integrate it with the desired data repository to start consuming it.
In this tutorial, we will show how to source data from Azure SQL Database to use in a Machine Learning workflow.