[ Ссылка ] | ksqlDB can process streams of data in Apache Kafka® to apply transformations to them. In this video, Michael Drogalis (Principal Product Manager, Confluent) explains in a step-by-step example how stateless operations work in ksqlDB. Examples of stateless operations include filtering, routing, and calculations within a message's payload.
Use promo code KSQLDB101 to get $25 of free Confluent Cloud usage: [ Ссылка ]
Promo code details: [ Ссылка ]
LEARN MORE
► Building Data Pipelines with Apache Kafka and Confluent: [ Ссылка ]
► How to Filter a Stream of Events Using ksqlDB: [ Ссылка ]
► How to Merge Many Streams into One Stream: [ Ссылка ]
► How to Query Structured Data: [ Ссылка ]
► How to Rekey a Stream with a Value: [ Ссылка ]
► How to Split a Stream of Events into Substreams: [ Ссылка ]
► ksqlDB: [ Ссылка ]
► ksqlDB 101 Course: [ Ссылка ]
► 📼 ksqlDB HOWTO – A Mini Video Series 📼: [ Ссылка ]
► Stream Processing: [ Ссылка ]
► Synopsis: [ Ссылка ]
► Use Lambda Functions: [ Ссылка ]
ABOUT CONFLUENT
Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.
#apachekafka #kafka #streamprocessing #ksqldb #confluent
