A PostgreSQL Interface for Azure Data Lake Storage Data

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Azure Data Lake Storage JDBC Driver

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



Use the Remoting features of the Azure Data Lake Storage JDBC Driver to create a PostgreSQL entry-point for data access.

There are a vast number of PostgreSQL clients available on the Internet. From standard Drivers to BI and Analytics tools, PostgreSQL is a popular interface for data access. Using our JDBC Drivers, you can now create PostgreSQL entry-points that you can connect to from any standard client.

To access Azure Data Lake Storage data as a PostgreSQL database, use the CData JDBC Driver for Azure Data Lake Storage and a JDBC foreign data wrapper (FDW). In this article, we compile the FDW, install it, and query Azure Data Lake Storage data from PostgreSQL Server.

Connect to Azure Data Lake Storage Data as a JDBC Data Source

To connect to Azure Data Lake Storage as a JDBC data source, you will need the following:

  • Driver JAR path: The JAR is located in the lib subfolder of the installation directory.
  • Driver class: cdata.jdbc.adls.ADLSDriver

  • JDBC URL: The URL must start with "jdbc:adls:" and can include any of the connection properties in name-value pairs separated with semicolons.

    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.

    A typical JDBC URL is below:

    jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH

Build the JDBC Foreign Data Wrapper

The Foreign Data Wrapper can be installed as an extension to PostgreSQL, without recompiling PostgreSQL. The jdbc2_fdw extension is used as an example (downloadable here).

  1. Add a symlink from the shared object for your version of the JRE to /usr/lib/libjvm.so. For example: ln -s /usr/lib/jvm/java-6-openjdk/jre/lib/amd64/server/libjvm.so /usr/lib/libjvm.so
  2. Start the build: make install USE_PGXS=1

Query Azure Data Lake Storage Data as a PostgreSQL Database

After you have installed the extension, follow the steps below to start executing queries to Azure Data Lake Storage data:

  1. Log into your database.
  2. Load the extension for the database: CREATE EXTENSION jdbc2_fdw;
  3. Create a server object for Azure Data Lake Storage: CREATE SERVER ADLS FOREIGN DATA WRAPPER jdbc2_fdw OPTIONS ( drivername 'cdata.jdbc.adls.ADLSDriver', url 'jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH', querytimeout '15', jarfile '/home/MyUser/CData/CData\ JDBC\ Driver\ for\ Salesforce MyDriverEdition/lib/cdata.jdbc.adls.jar');
  4. Create a user mapping for the username and password of a user known to the MySQL daemon. CREATE USER MAPPING for postgres SERVER ADLS OPTIONS ( username 'admin', password 'test');
  5. Create a foreign table in your local database: postgres=# CREATE FOREIGN TABLE resources ( resources_id text, resources_FullPath text, resources_Permission numeric) SERVER ADLS OPTIONS ( table_name 'resources');
You can now execute SELECT commands to Azure Data Lake Storage: postgres=# SELECT * FROM resources;