Create a Data Access Object for Azure Data Lake Storage Data using JDBI

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Azure Data Lake Storage JDBC Driver

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



A brief overview of creating a SQL Object API for Azure Data Lake Storage data in JDBI.

JDBI is a SQL convenience library for Java that exposes two different style APIs, a fluent style and a SQL object style. The CData JDBC Driver for Azure Data Lake Storage integrates connectivity to live Azure Data Lake Storage data in Java applications. By pairing these technologies, you gain simple, programmatic access to Azure Data Lake Storage data. This article walks through building a basic Data Access Object (DAO) and the accompanying code to read Azure Data Lake Storage data.

Create a DAO for the Azure Data Lake Storage Resources Entity

The interface below declares the desired behavior for the SQL object to create a single method for each SQL statement to be implemented.

public interface MyResourcesDAO { //request specific data from Azure Data Lake Storage (String type is used for simplicity) @SqlQuery("SELECT Permission FROM Resources WHERE Type = :type") String findPermissionByType(@Bind("type") String type); /* * close with no args is used to close the connection */ void close(); }

Open a Connection to Azure Data Lake Storage

Collect the necessary connection properties and construct the appropriate JDBC URL for connecting to Azure Data Lake Storage.

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 connection string for Azure Data Lake Storage will typically look like the following:

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

Use the configured JDBC URL to obtain an instance of the DAO interface. The particular method shown below will open a handle bound to the instance, so the instance needs to be closed explicitly to release the handle and the bound JDBC connection.

DBI dbi = new DBI("jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH"); MyResourcesDAO dao = dbi.open(MyResourcesDAO.class); //do stuff with the DAO dao.close();

Read Azure Data Lake Storage Data

With the connection open to Azure Data Lake Storage, simply call the previously defined method to retrieve data from the Resources entity in Azure Data Lake Storage.

//disply the result of our 'find' method String permission = dao.findPermissionByType("FILE"); System.out.println(permission);

Since the JDBI library is able to work with JDBC connections, you can easily produce a SQL Object API for Azure Data Lake Storage by integrating with the CData JDBC Driver for Azure Data Lake Storage. Download a free trial and work with live Azure Data Lake Storage data in custom Java applications today.