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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 PostgreSQL, Kafka can work with live PostgreSQL data. This article describes how to connect, access and stream PostgreSQL data into Apache Kafka Topics and to start Confluent Control Center to help users secure, manage, and monitor the PostgreSQL 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 PostgreSQL data. When you issue complex SQL queries to PostgreSQL, the driver pushes supported SQL operations, like filters and aggregations, directly to PostgreSQL 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 PostgreSQL data using native data types.
Before connecting the CData JDBC Driver for streaming PostgreSQL data in Apache Kafka Topics, install and configure the following in the client Linux-based system.
mkdir PostgreSQL
mv PostgreSQLJDBCDriver.zip PostgreSQL/
unzip PostgreSQLJDBCDriver.zip
ls cd lib/
cp -r /path/to/CData JDBC Driver for PostgreSQL/lib/* /usr/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/ cd /usr/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/
java -jar cdata.jdbc.postgresql.jar -l
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 PostgreSQL to stream messages using Kafka Connect Driver into Kafka Topics on ksqlDB.
๐ Start the Confluent local services curl --location 'server_address:8083/connectors'
--header 'Content-Type: application/json'
--data '{
"name": "jdbc_source_cdata_postgresql_01",
"config": {
"connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector",
"connection.url": "jdbc:postgresql:User=postgres;Password=admin;Database=postgres;Server=127.0.0.1;Port=5432;",
"topic.prefix": "postgresql-01-",
"mode": "bulk"
}
}'
Let us understand the fields used in the HTTP POST body (shown above):
For assistance in constructing the JDBC URL, use the connection string designer built into the CData JDBC Driver for PostgreSQL. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.postgresql.jar
Fill in the connection properties and copy the connection string to the clipboard.
To connect to PostgreSQL, set the Server, Port (the default port is 5432), and Database connection properties and set the User and Password you wish to use to authenticate to the server. If the Database property is not specified, the data provider connects to the user's default database.
You can use SSH (Secure Shell) to authenticate with PostgreSQL, whether the instance is hosted on-premises or in supported cloud environments. SSH authentication ensures that access is encrypted (as compared to direct network connections).
To connect to PostgreSQL via SSH in Password Auth mode, set the following connection properties:
To connect to PostgreSQL via SSH in Password Auth mode, set the following connection properties:
This request adds all the tables/contents from PostgreSQL as Kafka Topics.
Note: The IP Address (server) to POST the request (shown above) is the Linux Network IP Address.
ksql list topics;๐ List the Kafka Topics (BigCommerce is shown)
PRINT topic FROM BEGINNING;
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.
๐ Connect with Confluent Control CenterDownload a free, 30-day trial of the CData JDBC Driver for PostgreSQL and start streaming PostgreSQL data into Apache Kafka. Reach out to our Support Team if you have any questions.
Download a free trial of the PostgreSQL Driver to get started:
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