Stream Azure Analysis Services Data into Apache Kafka Topics

Apache Kafka is an open-source stream processing platform that is primarily used for building real-time data pipelines and event-driven applications. When paired with the CData JDBC Driver for Azure Analysis Services, Kafka can work with live Azure Analysis Services data. This article describes how to connect, access and stream Azure Analysis Services data into Apache Kafka Topics and to start Confluent Control Center to help users secure, manage, and monitor the Azure Analysis Services data received using Kafka infrastructure in the Confluent Platform.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Azure Analysis Services data. When you issue complex SQL queries to Azure Analysis Services, the driver pushes supported SQL operations, like filters and aggregations, directly to Azure Analysis Services and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Azure Analysis Services data using native data types.

Prerequisites

Before connecting the CData JDBC Driver for streaming Azure Analysis Services data in Apache Kafka Topics, install and configure the following in the client Linux-based system.

1. Confluent Platform for Apache Kafka
2. Confluent Hub CLI Installation
3. Self-Managed Kafka JDBC Source Connector for Confluent Platform

Define a New JDBC Connection to Azure Analysis Services data

1. Download CData JDBC Driver for Azure Analysis Services on a Linux-based system
2. Follow the given instructions to create a new directory extract all the driver contents into it:
   1. Create a new directory named Azure Analysis Services

      		mkdir AAS
      		

   2. Move the downloaded driver file (.zip) into this new directory

      		mv AASJDBCDriver.zip AAS/
      		

   3. Unzip the CData AASJDBCDriver contents into this new directory

      		unzip AASJDBCDriver.zip
      		

3. Open the Azure Analysis Services directory and navigate to the lib folder

   ls
   cd lib/
   

4. Copy the contents of the lib folder of the CData JDBC Driver for Azure Analysis Services into the lib folder of Kafka Connect JDBC. Check the Kafka Connect JDBC folder contents to confirm that the cdata.jdbc.aas.jar file is successfully copied into the lib folder

   cp -r /path/to/CData JDBC Driver for Azure Analysis Services/lib/* /usr/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/
   cd /usr/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/
   

5. Install the CData Azure Analysis Services JDBC driver license using the given command, followed by your Name and Email ID

   	java -jar cdata.jdbc.aas.jar -l
   	

6. Enter the product key or "TRIAL" (In the scenarios of license expiry, please contact our CData Support team)
7. Start the Confluent local services using the command:

   	confluent local services start
   	

   This starts all the Confluent Services like Zookeeper, Kafka, Schema Registry, Kafka REST, Kafka CONNECT, ksqlDB and Control Center. You are now ready to use the CData JDBC driver for Azure Analysis Services to stream messages using Kafka Connect Driver into Kafka Topics on ksqlDB.

   👁 Start the Confluent local services
   
8. Create the Kafka topics manually using a POST HTTP API Request:

    curl --location 'server_address:8083/connectors' 
   	--header 'Content-Type: application/json'
   	--data '{ 
   		"name": "jdbc_source_cdata_aas_01", 
   		"config": { 
   			"connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", 
   			"connection.url": "jdbc:aas:URL=asazure://REGION.asazure.windows.net/server;InitiateOAuth=GETANDREFRESH;",
   		"topic.prefix": "aas-01-", 
   		"mode": "bulk" 
   		} 
   	}'
   

   Let us understand the fields used in the HTTP POST body (shown above):

   • connector.class: Specifies the Java class of the Kafka Connect connector to be used.
   • connection.url: The JDBC connection URL to connect with Azure Analysis Services data.

     Built-in Connection String Designer

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

     		java -jar cdata.jdbc.aas.jar
     		

     Fill in the connection properties and copy the connection string to the clipboard.

     To connect to Azure Analysis Services, set the Url property to a valid server, for instance, asazure://southcentralus.asazure.windows.net/server, in addition to authenticating. Optionally, set Database to distinguish which Azure database on the server to connect to.

     Azure Analysis Services uses the OAuth authentication standard. OAuth requires the authenticating user to interact with Azure Analysis Services using the browser. You can connect without setting any connection properties for your user credentials. See the Help documentation for more information.

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     
   • topic.prefix: A prefix that will be added to the Kafka topics created by the connector. It's set to "aas-01-".
   • mode: Specifies the mode in which the connector operates. In this case, it's set to "bulk", which suggests that the connector is configured to perform bulk data transfer.

   This request adds all the tables/contents from Azure Analysis Services as Kafka Topics.

   Note: The IP Address (server) to POST the request (shown above) is the Linux Network IP Address.

9. Run ksqlDB and list the topics. Use the commands:

   ksql
   list topics;
   

   👁 List the Kafka Topics (BigCommerce is shown)
   
10. To view the data inside the topics, type the SQL Statement:

    PRINT topic FROM BEGINNING;
    

Connecting with the Confluent Control Center

To access the Confluent Control Center user interface, ensure to run the "confluent local services" as described in the above section and type http://<server address>:9021/clusters/ on your local browser.

Get Started Today

Download a free, 30-day trial of the CData JDBC Driver for Azure Analysis Services and start streaming Azure Analysis Services data into Apache Kafka. Reach out to our Support Team if you have any questions.