How to work with Active Directory Data in Apache Spark using SQL

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Active Directory, Spark can work with live Active Directory data. This article describes how to connect to and query Active Directory data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Active Directory data due to optimized data processing built into the driver. When you issue complex SQL queries to Active Directory, the driver pushes supported SQL operations, like filters and aggregations, directly to Active Directory 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 work with and analyze Active Directory data using native data types.

Install the CData JDBC Driver for Active Directory

Download the CData JDBC Driver for Active Directory installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Active Directory Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Active Directory JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for Active Directory/lib/cdata.jdbc.activedirectory.jar
   

2. With the shell running, you can connect to Active Directory with a JDBC URL and use the SQL Context load() function to read a table.

   To establish a connection, set the following properties:

   • Valid User and Password credentials (e.g., Domain\BobF or cn=Bob F,ou=Employees,dc=Domain).
   • Server information, including the IP or host name of the Server, as well as the Port.

   • BaseDN: This will limit the scope of LDAP searches to the height of the distinguished name provided.

     Note: Specifying a narrow BaseDN may greatly increase performance; for example, cn=users,dc=domain will only return results contained within cn=users and its children.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Active Directory JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.activedirectory.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.)
   

   Configure the connection to Active Directory, using the connection string generated above.

   scala> val activedirectory_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:activedirectory:User=cn=Bob F,ou=Employees,dc=Domain;Password=bob123;Server=10.0.1.2;Port=389;").option("dbtable","User").option("driver","cdata.jdbc.activedirectory.ActiveDirectoryDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Active Directory data as a temporary table:

   scala> activedirectory_df.registerTable("user")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> activedirectory_df.sqlContext.sql("SELECT Id, LogonCount FROM User WHERE CN = Administrator").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   👁 Data in Apache Spark (Salesforce is shown)
   

Using the CData JDBC Driver for Active Directory in Apache Spark, you are able to perform fast and complex analytics on Active Directory data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.