Kafka - Avro Converter

Kafka Commit Log Messaging Process

About

Data Serialization - AVRO in Kafka.

The Avro converter is normally used with the Schema Registry in order to properly lookup the schema for the Avro data.

Documentation / Reference





Discover More
Log Consumer
Kafka - Consumer

A consumer. A sink connector is a consumer. kafka-console-consumer is a command line to read data from a Kafka topic and write it to standard output. The configs can be overridden by...
Kafka Commit Log Messaging Process
Kafka - Schema Registry

schema registry Schema registry is recommended if you plan to use Avro for a data format because it can help you with: serialization and schema evolution. with schema knowledge the Avro...
Kafka Commit Log Messaging Process
Kafka - Stream Application

in Kafka. The stream API The Kafka cluster stores streams of records in categories called topics. configuration-parameters|Doc...
Kafka Commit Log Messaging Process
Kafka - kafka-avro-console-consumer utility

The kafka-avro-console-consumer is a the kafka-console-consumer with a avro formatter (io.confluent.kafka.formatter.AvroMessageFormatter) This console uses the Avro converter with the Schema Registry...
Kafka Commit Log Messaging Process
Kafka - kafka-avro-console-producer utility

The kafka-avro-console-producer is a producer command line to read data from standard input and write it to a Kafka topic in an avro format. This console uses the Avro converter with the Schema Registry...
Converter Basics
Kafka Connect - Converter (Read/Write - I/O)

A converter is a connect concept. It's the code used to persist data from a Connector. Converters are decoupled from connectors themselves to allow for reuse. For example, using the same Avro...
Kafka Commit Log Messaging Process
Kafka Connect - Sqlite in Distributed Mode

Sqlite JDBC source connector demo. The same steps than in the article but with a distributed worker Install Docker: Install Git: If you want to make the call with the kafka console utilities...



Share this page:
Follow us:
Task Runner