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The CData JDBC Driver for Azure Data Lake Storage enables you to access Azure Data Lake Storage as a JDBC data source, providing integration with rapid development tools in IDEs. This article shows how to use the data source configuration wizard to connect to Azure Data Lake Storage data in IntelliJ.
Follow the steps below to add the driver JAR and define connection properties required to connect to Azure Data Lake Storage data.
In the Data Source Properties dialog that appears, the following properties are required:
Database URL: Enter the connection URL in the JDBC URL property. The URL must start with jdbc:adls: and includes connection properties separated with semicolons.
Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.
For this, an Active Directory web application is required. You can create one as follows:
To authenticate against a Gen 1 DataLakeStore account, the following properties are required:
To authenticate against a Gen 2 DataLakeStore account, the following properties are required:
For assistance in constructing the JDBC URL, use the connection string designer built into the Azure Data Lake Storage JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.adls.jar
Fill in the connection properties and copy the connection string to the clipboard.
👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)A typical JDBC URL is the following:
jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH;
To discover schema information, right-click the data source you just created and click Refresh Tables. To query a table, right-click it and then click Open Tables Editor.
👁 The results of a query in IntelliJ. (Salesforce is shown.)Download a free trial of the Azure Data Lake Storage Driver to get started:
Download NowLearn more:
👁 Azure Data Lake Storage IconRapidly create and deploy powerful Java applications that integrate with Azure Data Lake Storage.