Use the CData JDBC Driver for Azure Data Lake Storage in MicroStrategy

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Azure Data Lake Storage JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Azure Data Lake Storage.



Connect to Azure Data Lake Storage data in MicroStrategy Developer using the CData JDBC Driver for Azure Data Lake Storage.

MicroStrategy is an analytics and mobility platform that enables data-driven innovation. When you pair MicroStrategy with the CData JDBC Driver for Azure Data Lake Storage, you gain database-like access to live Azure Data Lake Storage data from MicroStrategy, expanding your reporting and analytics capabilities. In this article, we walk through creating a database instance for Azure Data Lake Storage in MicroStrategy Developer and create a Warehouse Catalog for the Azure Data Lake Storage data.

The CData JDBC Driver offers unmatched performance for interacting with live Azure Data Lake Storage data in MicroStrategy due to optimized data processing built into the driver. When you issue complex SQL queries from MicroStrategy to Azure Data Lake Storage, the driver pushes supported SQL operations, like filters and aggregations, directly to Azure Data Lake Storage and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze Azure Data Lake Storage data using native MicroStrategy data types.

Connect to Azure Data Lake Storage in MicroStrategy Developer

You can connect to Azure Data Lake Storage in MicroStrategy Developer by adding a database instance based on the CData JDBC Driver for Azure Data Lake Storage.* Before you begin, you will need to install the JDBC Driver for Azure Data Lake Storage on the machine hosting the MicroStrategy Intelligence Server that your instance of MicroStrategy Developer is connected to.

  1. Open MicroStrategy Developer and select a Project Source.
  2. Navigate to Administration -> Configuration Managers -> Database Instances and right-click to add a new instance.
  3. Name the instance, select Generic DBMS as the database connection type, and create a new database connection.
  4. In the database connection wizard, name the connection and create a new Database Login name, setting the user and password for Azure Data Lake Storage.
  5. On the Advanced tab for the connection wizard, set the additional connection string parameters as follows.
    • Add the JDBC keyword to the connection string.
    • Set MSTR_JDBC_JAR_FOLDER to the path of the directory containing the JAR file for the JDBC driver. (C:\Program Files\CData JDBC Driver for Azure Data Lake Storage\lib\ on Windows.)
    • Set DRIVER to cdata.jdbc.adls.ADLSDriver, the driver class.
    • Set URL to the JDBC URL for the Azure Data Lake Storage driver, which contains the necessary connection properties.

      Authenticating to a Gen 1 DataLakeStore Account

      Gen 1 uses OAuth 2.0 in Azure AD for authentication.

      For this, an Active Directory web application is required. You can create one as follows:

      1. Sign in to your Azure Account through the .
      2. Select "Azure Active Directory".
      3. Select "App registrations".
      4. Select "New application registration".
      5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
      6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
      7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

      To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

      • Schema: Set this to ADLSGen1.
      • Account: Set this to the name of the account.
      • OAuthClientId: Set this to the application Id of the app you created.
      • OAuthClientSecret: Set this to the key generated for the app you created.
      • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
      • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

      Authenticating to a Gen 2 DataLakeStore Account

      To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

      • Schema: Set this to ADLSGen2.
      • Account: Set this to the name of the account.
      • FileSystem: Set this to the file system which will be used for this account.
      • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
      • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

      Built-in Connection String Designer

      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.

      When you configure the JDBC URL, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

    Typical additional connection string properties follow:

    JDBC;MSTR_JDBC_JAR_FOLDER=PATH\TO\JAR\;DRIVER=cdata.jdbc.adls.ADLSDriver;URL={jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;};
  6. Ensure that you have not selected an ODBC data source (this will trigger MicroStrategy to use the additional connection string parameters to build the database instance) and click OK.
  7. Click OK to close the database instance wizard.
  8. In the Project Source, right-click the project and open the Project configuration.
  9. Navigate to Database Instances, select the newly created database instance, and click OK.
  10. Close MicroStrategy Developer and restart the connected MicroStrategy Intelligence Server to complete the database instance creation.

With the database instance configured, you will now be able to connect to Azure Data Lake Storage data from the Warehouse Catalog and Data Import.

Connect to Azure Data Lake Storage Data from the Warehouse Catalog

Once you have created a database instance based on the JDBC Driver for Azure Data Lake Storage, you can connect to data from the Warehouse Catalog.

  1. Select your project and click Schema -> Warehouse Catalog.
  2. In the Read Settings for the Catalog, click Settings and set the queries to retrieve the schema:
    • To retrieve the list of tables, use the following query: SELECT * FROM SYS_TABLES
    • To retrieve the list of columns for selected tables, use the following query: SELECT DISTINCT CatalogName NAME_SPACE, TableName TAB_NAME, ColumnName COL_NAME, DataTypeName DATA_TYPE, Length DATA_LEN, NumericPrecision DATA_PREC, NumericScale DATA_SCALE FROM SYS_TABLECOLUMNS WHERE TableName IN (#TABLE_LIST#) ORDER BY 1,2,3
  3. Select tables to be used in the project.

Using the CData JDBC Driver for Azure Data Lake Storage in MicroStrategy, you can easily create robust visualizations and reports on Azure Data Lake Storage data. Read our other articles on connecting to Azure Data Lake Storage in MictroStrategy Web and connecting to Azure Data Lake Storage in MicroStrategy Desktop for more information.


Note: Connecting using a JDBC Driver requires a 3- or 4-Tier Architecture.