From 0942b80ad6f9b9681446d952864d6d03ce90ca53 Mon Sep 17 00:00:00 2001 From: Victoria Bialas Date: Tue, 23 Apr 2019 19:15:59 -0700 Subject: [PATCH 1/2] KAFKA-8227 DOCS Fixed missing links duality of streams tables Signed-off-by: Victoria Bialas --- docs/streams/core-concepts.html | 25 +++++++++++++++---------- 1 file changed, 15 insertions(+), 10 deletions(-) diff --git a/docs/streams/core-concepts.html b/docs/streams/core-concepts.html index 1e1aeb7b1aa07..eb5db3d21f96e 100644 --- a/docs/streams/core-concepts.html +++ b/docs/streams/core-concepts.html @@ -63,7 +63,7 @@

Stream Processing Topology There are two special processors in the topology: @@ -160,21 +160,26 @@

Duality of

Any stream processing technology must therefore provide first-class support for streams and tables. - Kafka's Streams API provides such functionality through its core abstractions for - streams <streams_concepts_kstream> and - tables <streams_concepts_ktable>, which we will talk about in a minute. - Now, an interesting observation is that there is actually a close relationship between streams and tables, - the so-called stream-table duality. - And Kafka exploits this duality in many ways: for example, to make your applications + Kafka's Streams API provides such functionality through its core abstractions for + streams + <streams_concepts_kstreams> + and tables + <streams_concepts_kstreams>, + which we will talk about in a minute. Now, an interesting observation is that there is actually a close relationship between streams and tables, + the so-called stream-table duality. And Kafka exploits this duality in many ways: for example, to make your applications + elastic elastic <streams_developer-guide_execution-scaling>, - to support fault-tolerant stateful processing <streams_developer-guide_state-store_fault-tolerance>, - or to run interactive queries <streams_concepts_interactive-queries> + to support fault-tolerant stateful processing + <streams_developer-guide_state-store_fault-tolerance>, + or to run interactive queries + <streams_concepts_interactive-queries> against your application's latest processing results. And, beyond its internal usage, the Kafka Streams API also allows developers to exploit this duality in their own applications.

- Before we discuss concepts such as aggregations <streams_concepts_aggregations> + Before we discuss concepts such as aggregations + <streams_concepts_aggregations>, in Kafka Streams we must first introduce tables in more detail, and talk about the aforementioned stream-table duality. Essentially, this duality means that a stream can be viewed as a table, and a table can be viewed as a stream.

From 736337d9a2542b13b1e8926999fa2afeb15c4755 Mon Sep 17 00:00:00 2001 From: Victoria Bialas Date: Wed, 24 Apr 2019 11:40:59 -0700 Subject: [PATCH 2/2] Bill's review comments, removed placeholder link targets Signed-off-by: Victoria Bialas --- docs/streams/core-concepts.html | 42 ++++++++++++++------------------- 1 file changed, 18 insertions(+), 24 deletions(-) diff --git a/docs/streams/core-concepts.html b/docs/streams/core-concepts.html index eb5db3d21f96e..474cac9bb0215 100644 --- a/docs/streams/core-concepts.html +++ b/docs/streams/core-concepts.html @@ -159,30 +159,24 @@

Duality of

- Any stream processing technology must therefore provide first-class support for streams and tables. - Kafka's Streams API provides such functionality through its core abstractions for - streams - <streams_concepts_kstreams> - and tables - <streams_concepts_kstreams>, - which we will talk about in a minute. Now, an interesting observation is that there is actually a close relationship between streams and tables, - the so-called stream-table duality. And Kafka exploits this duality in many ways: for example, to make your applications - elastic - elastic <streams_developer-guide_execution-scaling>, - to support fault-tolerant stateful processing - <streams_developer-guide_state-store_fault-tolerance>, - or to run interactive queries - <streams_concepts_interactive-queries> - against your application's latest processing results. And, beyond its internal usage, the Kafka Streams API - also allows developers to exploit this duality in their own applications. -

- -

- Before we discuss concepts such as aggregations - <streams_concepts_aggregations>, - in Kafka Streams we must first introduce tables in more detail, and talk about the aforementioned stream-table duality. - Essentially, this duality means that a stream can be viewed as a table, and a table can be viewed as a stream. -

+ Any stream processing technology must therefore provide first-class support for streams and tables. + Kafka's Streams API provides such functionality through its core abstractions for + streams + and tables, + which we will talk about in a minute. Now, an interesting observation is that there is actually a close relationship between streams and tables, + the so-called stream-table duality. And Kafka exploits this duality in many ways: for example, to make your applications + elastic, + to support fault-tolerant stateful processing, + or to run interactive queries + against your application's latest processing results. And, beyond its internal usage, the Kafka Streams API + also allows developers to exploit this duality in their own applications. +

+ +

+ Before we discuss concepts such as aggregations + in Kafka Streams, we must first introduce tables in more detail, and talk about the aforementioned stream-table duality. + Essentially, this duality means that a stream can be viewed as a table, and a table can be viewed as a stream. +

States