Learn more
 

Ready to get started?

Download a free trial of the Azure Data Lake Storage Driver to get started:

 Download Now

Learn more:

Azure Data Lake Storage Icon Azure Data Lake Storage JDBC Driver

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

In this article

Related articles

Use JayDeBeApi to access Azure Data Lake Storage Data in Python


Use standard Python scripting and the development environment of your choice to access live Azure Data Lake Storage data.

Access Azure Data Lake Storage data with Python scripts and standard SQL on any machine where Python and Java can be installed. You can use the CData JDBC Driver for Azure Data Lake Storage and the JayDeBeApi module to work with remote Azure Data Lake Storage data in Python. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular Python language. This article shows how to use the driver to execute SQL queries to Azure Data Lake Storage and visualize Azure Data Lake Storage data with standard Python.

Use the JayDeBeApi module

JayDeBeApi is a Python library that serves as a JDBC (Java Database Connectivity) bridge, allowing Python programs to interact with Java databases, including CData JDBC Drivers. Use the pip install command to install the module:

pip install JayDeBeApi

Create the JDBC URL

Once you have JayDeBeApi installed, you are ready to work with Azure Data Lake Storage data in Python using SQL.

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.

Below is a sample variable assignment, including a typical JDBC connection string:

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

Access Azure Data Lake Storage data in Python

With the JDBC URL configured, you only need the absolute path to the JDBC driver JAR file, which is in the "lib" folder in the installation directory ("C:\Program Files\CData[product_name] 20XX\lib\cdata.jdbc.adls.jar" on Windows).

NOTE: If you haven't already, set the JAVA_HOME environment variable to the Java installation directory.

Use code similar to the follow to read and print data from Azure Data Lake Storage:

import jaydebeapi #The JDBC connection string jdbc_url = "jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH" username = "****" password = "****" #The absolute Path to the JDBC driver JAR file, typically: jdbc_driver_jar = "C:\Program Files\CData[product_name] 20XX\lib\cdata.jdbc.adls.jar" conn = jaydebeapi.connect( "cdata.jdbc.adls.jar", jdbc_url, [username, password], jdbc_driver_jar, ) cursor = conn.cursor() cursor.execute("SELECT * FROM Resources;") results = cursor.fetchall() for row in results: print(row) cursor.close() conn.close()

Free trial & more information

Download a free, 30-day trial of the CData JDBC Driver for Azure Data Lake Storage and start working with your live Azure Data Lake Storage data in Python. Reach out to our Support Team if you have any questions.