Introduction

In this article, we will explore the process of developing U-SQL jobs locally for Azure Data Lake Analytics. Azure Data Lake Analytics is a cloud-based service that allows you to process big data and perform analytics tasks. By developing U-SQL jobs locally, developers can efficiently test and debug their code before deploying it to the Azure cloud.

Setting up a local development environment

The first step in developing U-SQL jobs locally is to set up a local development environment. Visual Studio Data Tools provides the necessary tools and project constructs for developing U-SQL jobs. Install Visual Studio on your local machine, and then configure the Data storage and processing toolset component. This component includes the Azure Data Lake and Stream Analytics Tools, which are essential for developing projects related to Azure Data Lake Analytics.

Once the installation is complete, open Visual Studio and navigate to the Data Lake menu. From here, you can access the Data Lake Analytics Explorer, which allows you to connect to your Azure account and view the sample data and files stored in the data lake storage account.

Developing and executing U-SQL Jobs locally

With the local development environment set up, you can now create a new project for your U-SQL jobs. In Visual Studio, go to the File menu and click on New Project. Select the U-SQL sample application project template and provide a name for your project.

Within the project, you will find U-SQL script files in the solution explorer pane. Open the desired script file and analyze its contents. This script reads data from a source file and writes the output to a destination file. You can modify the script to suit your specific requirements.

To execute the U-SQL job, click on the Start button from the toolbar. Visual Studio will compile the job and display the job graph, which provides a visual representation of the job’s execution flow. Once the compilation is complete, the job will start executing. You can monitor the job’s progress and view execution statistics in a pop-up window.

After the job completes successfully, you can verify the source and destination files to ensure that the data has been processed correctly.

Conclusion

Developing U-SQL jobs locally for Azure Data Lake Analytics provides developers with a cost-effective and efficient way to test and debug their code before deploying it to the Azure cloud. By using Visual Studio and the Azure Data Lake Analytics Explorer, developers can easily develop, execute, and monitor U-SQL jobs from their local machines. This enables faster development cycles and ensures the accuracy of the code before it is deployed to production.