What is KStream and KTable in Kafka?

What is KStream and KTable in Kafka?

In the Kafka Streams DSL, an input stream of an aggregation operation can be a KStream or a KTable, but the output stream will always be a KTable. This allows Kafka Streams to update an aggregate value upon the out-of-order arrival of further records after the value was produced and emitted.

What is the use of Kafka streams?

Kafka Streams is a library for building streaming applications, specifically applications that transform input Kafka topics into output Kafka topics (or calls to external services, or updates to databases, or whatever). It lets you do this with concise code in a way that is distributed and fault-tolerant.

Why use Kafka instead of database?

Kafka has become popular because it’s open-source and capable of scaling to very large numbers of messages. Instead of reading and writing a traditional database, you append events to Kafka, and read from downstream views that represent the present state.

What is Kafka KTable?

KTable is an abstraction of a changelog stream from a primary-keyed table. Each record in this changelog stream is an update on the primary-keyed table with the record key as the primary key.

What is the difference between KStream and KTable?

KStream handles the stream of records. On the other hand, KTable manages the changelog stream with the latest state of a given key. Each data record represents an update.

What is confluent and Kafka?

Confluent is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream. The Confluent Platform makes Kafka easier to build and easier to operate.

Are ktable lookups deterministic in Kafka?

KTable lookups are done on the current KTable state, and thus, out-of-order records can yield non-deterministic result. Furthermore, in older versions of Kafka Streams there is no guarantee that all records will be processed in timestamp order (even if processing records in timestamp order is the goal, it is only best effort).

What is a keyktable in Kafka?

KTable is an abstraction of a changelog stream from a primary-keyed table. Each record in this changelog stream is an update on the primary-keyed table with the record key as the primary key. A KTable is either defined from a single Kafka topic that is consumed message by message or the result of a KTable transformation.

What are join semantics in Kafka Streams?

Join semantics are inspired by SQL join semantics, however, because Kafka Streams offers stream instead of batch processing, semantics do no align completely. In the following, we give a details explanation of the offered join semantics in Kafka Streams.

How does valuejoiner work in Kafka Streams?

Last but not least, in Kafka Streams each join is “customized” by the user with a ValueJoiner function that compute the actual result. Hence, we show output records as “X – Y” with X and Y being the left and right value, respectively, given to the value joiner.