If you have a stream of events in a Kafka topic and wish to transform a field in each event, you an use ksqlDB's scalar functions or implement your own scalar UDF if your needs aren't met by the built-in functions.
As a concrete example, consider a topic with events that represent movies. Each event has a single attribute that combines its title and its release year into a string. The following ksqlDB query uses the string SPLIT function to create events in a new topic with title and release date turned into their own attributes.
First we need to create a stream of movies. This line of ksqlDB DDL creates a stream and its underlying Kafka topic to represent a stream of movies. If the topic already exists, then ksqlDB simply registers it as the source of data underlying the new stream. The stream has three fields: id, the movie ID; title, the title with the year appended; and genre, movie's genre.
CREATE STREAM raw_movies (id INT KEY, title VARCHAR, genre VARCHAR)
WITH (kafka_topic='movies', partitions=1, value_format = 'avro');
Given the stream of movies, break the title field into separate attributes for the title and release year using the SPLIT function. CAST is also used to convert the resulting release year's data type from string to integer.
SELECT id,
SPLIT(title, '::')[1] as title,
CAST(SPLIT(title, '::')[2] AS INT) AS year,
genre
FROM raw_movies
EMIT CHANGES;