Stream SQL 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 SQL Analysis Services, Kafka can work with live SQL Analysis Services data. This article describes how to connect, access and stream SQL Analysis Services data into Apache Kafka Topics and to start Confluent Control Center to help users secure, manage, and monitor the SQL 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 SQL Analysis Services data. When you issue complex SQL queries to SQL Analysis Services, the driver pushes supported SQL operations, like filters and aggregations, directly to SQL 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 SQL Analysis Services data using native data types.

Prerequisites

Before connecting the CData JDBC Driver for streaming SQL 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 SQL Analysis Services data

1. Download CData JDBC Driver for SQL 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 SQL Analysis Services

      		mkdir SSAS
      		

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

      		mv SSASJDBCDriver.zip SSAS/
      		

   3. Unzip the CData SSASJDBCDriver contents into this new directory

      		unzip SSASJDBCDriver.zip
      		

3. Open the SQL 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 SQL Analysis Services into the lib folder of Kafka Connect JDBC. Check the Kafka Connect JDBC folder contents to confirm that the cdata.jdbc.ssas.jar file is successfully copied into the lib folder

   cp -r /path/to/CData JDBC Driver for SQL 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 SQL Analysis Services JDBC driver license using the given command, followed by your Name and Email ID

   	java -jar cdata.jdbc.ssas.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 SQL 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_ssas_01", 
   		"config": { 
   			"connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", 
   			"connection.url": "jdbc:ssas:User=myuseraccount;Password=mypassword;URL=http://localhost/OLAP/msmdpump.dll;",
   		"topic.prefix": "ssas-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 SQL 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 SQL Analysis Services. Either double-click the JAR file or execute the jar file from the command-line.

     		java -jar cdata.jdbc.ssas.jar
     		

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

     To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

     To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

     • HTTP Authentication

       Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

     • Windows (NTLM)

       Set the Windows User and Password and set AuthScheme to "NTLM".

     • Kerberos and Kerberos Delegation

       To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

     • SSL/TLS:

       By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

     You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

     See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

     👁 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 "ssas-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 SQL 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 SQL Analysis Services and start streaming SQL Analysis Services data into Apache Kafka. Reach out to our Support Team if you have any questions.