From 3a20ba305517ace78ea5f54554bd3b333f0b7d3d Mon Sep 17 00:00:00 2001 From: Paul Cavallaro Date: Sun, 3 Apr 2016 18:14:53 -0700 Subject: [PATCH] MINOR: Fix small typo in design section Sentence was missing "as", minor grammar clean up. Author: Paul Cavallaro Reviewers: Ewen Cheslack-Postava Closes #1151 from paulcavallaro/docs-fix --- docs/design.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/design.html b/docs/design.html index ad40431eeb1..a97a0adecc0 100644 --- a/docs/design.html +++ b/docs/design.html @@ -300,7 +300,7 @@ Log compaction is a mechanism to give finer-grained per-record retention, rather

This retention policy can be set per-topic, so a single cluster can have some topics where retention is enforced by size or time and other topics where retention is enforced by compaction.

-This functionality is inspired by one of LinkedIn's oldest and most successful pieces of infrastructure—a database changelog caching service called Databus. Unlike most log-structured storage systems Kafka is built for subscription and organizes data for fast linear reads and writes. Unlike Databus, Kafka acts a source-of-truth store so it is useful even in situations where the upstream data source would not otherwise be replayable. +This functionality is inspired by one of LinkedIn's oldest and most successful pieces of infrastructure—a database changelog caching service called Databus. Unlike most log-structured storage systems Kafka is built for subscription and organizes data for fast linear reads and writes. Unlike Databus, Kafka acts as a source-of-truth store so it is useful even in situations where the upstream data source would not otherwise be replayable.

Log Compaction Basics