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

Prerequisites

Before connecting the CData JDBC Driver for streaming REST 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 REST data

1. Download CData JDBC Driver for REST 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 REST

      		mkdir REST
      		

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

      		mv RESTJDBCDriver.zip REST/
      		

   3. Unzip the CData RESTJDBCDriver contents into this new directory

      		unzip RESTJDBCDriver.zip
      		

3. Open the REST directory and navigate to the lib folder

   ls
   cd lib/
   

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

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

   	java -jar cdata.jdbc.rest.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 REST 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_rest_01", 
   		"config": { 
   			"connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", 
   			"connection.url": "jdbc:rest:DataModel=Relational;URI=C:/people.xml;Format=XML;",
   		"topic.prefix": "rest-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 REST 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 REST. Either double-click the JAR file or execute the jar file from the command-line.

     		java -jar cdata.jdbc.rest.jar
     		

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

     See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models REST APIs as bidirectional database tables and XML/JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

     After setting the and providing any authentication values, set to "XML" or "JSON" and set to more closely match the data representation to the structure of your data.

     The property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

     • Document (default): Model a top-level, document view of your REST data. The data provider returns nested elements as aggregates of data.
     • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
     • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

     See the Modeling REST Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

     👁 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 "rest-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 REST 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 REST and start streaming REST data into Apache Kafka. Reach out to our Support Team if you have any questions.