From 13f00dcfa2d3bc6d6af5e5de1a6d3fe8205c0a25 Mon Sep 17 00:00:00 2001 From: Jorge Quilcate Otoya Date: Thu, 31 May 2018 06:42:32 +0200 Subject: [PATCH] streams intro --- 04-kafka-streams/README.md | 42 ++++++++++++++++++++++++++-- 04-kafka-streams/stream-process.png | Bin 0 -> 89664 bytes 2 files changed, 39 insertions(+), 3 deletions(-) create mode 100644 04-kafka-streams/stream-process.png diff --git a/04-kafka-streams/README.md b/04-kafka-streams/README.md index 3e30577..6447805 100644 --- a/04-kafka-streams/README.md +++ b/04-kafka-streams/README.md @@ -1,11 +1,47 @@ # Kafka Streams API +Kafka Streams is a library that can be used to enable stream processing +capabilities on your applications. + +This means that you can process data "on the fly" (i.e. subscribe to +events on Kafka) and producer new events. This sounds very similar to +Producer and Consumer API, and it is because those are used inside +Kafka Streams. But plus consuming and producing events, the capabilities to process +the stream is what makes Streams a powerful API. + ## Streams Topology -## DSL: Stateless Operations +There are 2 APIs in Kafka Streams: + +* Processor API +* Streams DSL + +Where the API define `Processor` stages where data that comes from +Sources (i.e. Topics) are processed. + +But we have a DSL that simplifies the processing of data, and have common +operators to process data (e.g. mapping, filtering, joining, etc.) + +The goal of these APIs is to define a `Topology` that represents +the Stream Application. + +![](stream-process.png) + +## Streams DSL + +Inside Kafka Streams DSL API, there are 2 main abstractions: + +* `KStreams` +* `KTable` + +`KStreams` represents data in motion and `KTable` represents data at rest. + +Both notions are key to implement Streaming Applications. + +### DSL: Stateless Operations -## DSL: Stateful Operations +### DSL: Stateful Operations -## Tables and Joins +### Tables and Joins ## 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