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From jkr...@apache.org
Subject svn commit: r1498621 - in /kafka/site: diagrams/consumer-groups.graffle images/consumer-groups.png introduction.html styles.css
Date Mon, 01 Jul 2013 18:57:46 GMT
Author: jkreps
Date: Mon Jul  1 18:57:45 2013
New Revision: 1498621

URL: http://svn.apache.org/r1498621
Log:
Add diagram to intro.


Added:
    kafka/site/diagrams/consumer-groups.graffle
    kafka/site/images/consumer-groups.png   (with props)
Modified:
    kafka/site/introduction.html
    kafka/site/styles.css

Added: kafka/site/diagrams/consumer-groups.graffle
URL: http://svn.apache.org/viewvc/kafka/site/diagrams/consumer-groups.graffle?rev=1498621&view=auto
==============================================================================
--- kafka/site/diagrams/consumer-groups.graffle (added)
+++ kafka/site/diagrams/consumer-groups.graffle Mon Jul  1 18:57:45 2013
@@ -0,0 +1,1255 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
+<plist version="1.0">
+<dict>
+	<key>ActiveLayerIndex</key>
+	<integer>0</integer>
+	<key>ApplicationVersion</key>
+	<array>
+		<string>com.omnigroup.OmniGrafflePro.MacAppStore</string>
+		<string>139.16</string>
+	</array>
+	<key>AutoAdjust</key>
+	<true/>
+	<key>BackgroundGraphic</key>
+	<dict>
+		<key>Bounds</key>
+		<string>{{0, 0}, {576, 733}}</string>
+		<key>Class</key>
+		<string>SolidGraphic</string>
+		<key>FontInfo</key>
+		<dict>
+			<key>Font</key>
+			<string>Helvetica</string>
+			<key>Size</key>
+			<real>13</real>
+		</dict>
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+		<integer>2</integer>
+		<key>Style</key>
+		<dict>
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+			</dict>
+		</dict>
+	</dict>
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+	<key>CanvasOrigin</key>
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+	<key>ColumnSpacing</key>
+	<real>36</real>
+	<key>CreationDate</key>
+	<string>2013-07-01 18:13:29 +0000</string>
+	<key>Creator</key>
+	<string>Jay Kreps</string>
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Added: kafka/site/images/consumer-groups.png
URL: http://svn.apache.org/viewvc/kafka/site/images/consumer-groups.png?rev=1498621&view=auto
==============================================================================
Binary file - no diff available.

Propchange: kafka/site/images/consumer-groups.png
------------------------------------------------------------------------------
    svn:mime-type = application/octet-stream

Modified: kafka/site/introduction.html
URL: http://svn.apache.org/viewvc/kafka/site/introduction.html?rev=1498621&r1=1498620&r2=1498621&view=diff
==============================================================================
--- kafka/site/introduction.html (original)
+++ kafka/site/introduction.html Mon Jul  1 18:57:45 2013
@@ -2,19 +2,19 @@
 
 <h1>Introduction to Kafka</h1>
 
-Kafka is a distributed, partitioned, replicated commit log as a service. It provides the functionality of a messaging system, but with a unique design.
+Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
 <p>
 What does all that mean?
 <p>
 First let's review some basic messaging terminology:
 <ul>
-	<li>Kafka maintains feeds of data in categories called <i>topics</i>.
-	<li><i>Producers</i> publish data to a Kafka topic.
-	<li><i>Consumers</i> subscribe to topics and receive the feed of data published to these topics.
+	<li>Kafka maintains feeds of messages in categories called <i>topics</i>.
+	<li><i>Producers</i> publish messages to a Kafka topic.
+	<li><i>Consumers</i> subscribe to topics and receive the feed of messages published to these topics.
 	<li>Kafka is run as a cluster of one or more servers each of which is called a <i>broker</i>.
 </ul>
 
-A a high level, producers send messages over the network to the Kafka cluster which in turn serves them up to consumers like this:
+At a high level, producers send messages over the network to the Kafka cluster which in turn serves them up to consumers like this:
 <div style="text-align: center; width: 100%">
   <img src="images/producer_consumer.png">
 </div>
@@ -28,9 +28,9 @@ A topic is the category or feed name. Fo
 </div>
 Each partition is an ordered, immutable sequence of messages that is continually appended to&mdash;a commit log. The messages in the partitions are each assigned a sequential id number called the <i>offset</i> that uniquely identifies each message within the partition.
 <p>
-The Kafka cluster maintains these partitioned logs for a configurable period of time, usually days. During this time any number of consumers can consume this data (and they can consume it any number of times).
+The Kafka cluster retains all published messages&mdash;whether or not they have been consumed&mdash;for a configurable period of time. For example if the retention is set for two days, then for the two days after a message is published it is available for consumption, after which it will be discarded to free up space. This approach to data retention allows more flexibility for consumers: unlike most systems Kafka does not retain a separate copy of the data for each consumer, and consumers can reprocess data if they need to.
 <p>
-The position in the log is controlled by the message offset of the last read message. This offset is controlled by the consumer: normally a consumer will read sequentially but the consumer can choose to move its position back to an older offset if it needs to reprocess data.
+In fact the only metadata retained on a per-consumer basis is the position of the consumer in in the log, called the "offset". This offset is controlled by the consumer: normally a consumer will read sequentially advance its offset in the same way, but the consumer can reset its position if need be.
 <p>
 The partitions in the log serve several purposes. First, they allow the log to scale beyond a size that will fit on a single server. Each individual partition must fit on the servers that host it, but a topic may have many partitions so it can handle an arbitrary amount of data. Second they act as the unit of parallelism&mdash;more on that in a bit. 
 
@@ -38,7 +38,7 @@ The partitions in the log serve several 
 
 The partitions of the log are distributed over the servers in the Kafka cluster with each server handling data and requests for a share of the partitions. Each partition is replicated across a configurable number of servers for fault tolerance.
 <p>
-Each partition has one server which acts as the "leader" and zero or more "followers". The leader handles all read and write requests for the partition while the followers passively replicate the leader. If the leader fails, one of the followers will automatically become the new leader. Each server acts as a leader for some of its partitions and a follower for others so load is well balanced within the cluster.
+Each partition has one server which acts as the "leader" and zero or more servers which act as "followers". The leader handles all read and write requests for the partition while the followers passively replicate the leader. If the leader fails, one of the followers will automatically become the new leader. Each server acts as a leader for some of its partitions and a follower for others so load is well balanced within the cluster.
 
 <h3>Producers</h3>
 
@@ -46,11 +46,17 @@ Producers publish data to the topics of 
 
 <h3>Consumers</h3>
 
-Traditionally messaging has two models: <a href="http://en.wikipedia.org/wiki/Message_queue">queuing</a> and <a href="http://en.wikipedia.org/wiki/Publish%E2%80%93subscribe_pattern">publish-subscribe</a>. In a queue a pool of consumers may read from server and the message goes to one of them; in publish-subscribe the message is broadcast to all consumers. Kafka offers a single consumer abstraction that generalizes both of these&mdash;the <i>consumer group</i>.
+Traditionally messaging has two models: <a href="http://en.wikipedia.org/wiki/Message_queue">queuing</a> and <a href="http://en.wikipedia.org/wiki/Publish%E2%80%93subscribe_pattern">publish-subscribe</a>. In a queue, a pool of consumers may read from a server and each message goes to one of them; in publish-subscribe the message is broadcast to all consumers. Kafka offers a single consumer abstraction that generalizes both of these&mdash;the <i>consumer group</i>.
 <p>
-Consumers label themselves with a consumer group, and each message is delivered to one server within that group. If all the servers have the same consumer group, then this works just like a traditional queue. If all the servers have different consumer groups then this works like publish-subscribe. More commonly, however, we have found that topics have a small number of consumer groups, one for each logical subscriber, and each group may be composed of many consumer instances for scalability and fault tolerance. 
+Consumers label themselves with a consumer group name, and each message published to a topic is delivered to one consumer instance within each subscribing consume group. Consumer instances can be in separate processes or on separate machines. If all the consumer instances have the same consumer group, then this works just like a traditional queue balancing load over the consumers. If all the consumers instances have different consumer groups then this works like publish-subscribe and all messages are broadcast to all consumers. More commonly, however, we have found that topics have a small number of consumer groups, one for each logical subscriber, and each group is composed of many consumer instances for scalability and fault tolerance. 
 <p>
-A traditional queue allows messages to be consumed by any consumer instance. This effectively means the ordering of the messages is lost&mdash;although the messages may be strongly ordered within the queue, they may arrive at the different consumer instances and be processed out of order. By having a notion of parallelism&mdash;the partition&mdash;within the topics Kafka is able to provide both ordering guarantees and load balancing. This is achieved by assigning the partitions in the topic to the consumers in the consumer group so that each partition is consumed by exactly one consumer in the group. By doing this we ensure that the consumer is the only reader of that partition and consumes the data in order. Since there are many partitions this still balances the load over many consumer instances. Note however that there cannot be more consumer instances than partitions.
+
+<div style="float: right; margin: 20px; width: 500px" class="caption">
+  <img src="images/consumer-groups.png"><br>
+  A two server Kafka cluster hosting four partitions (P0-P3) with two consumer groups. Consumer group A has two consumer instances and group B has four.
+</div>
+<p>
+Kafka handles ordering differently from a traditional messaging system too. A traditional queue allows messages to be consumed by any consumer instance. This effectively means the ordering of the messages is lost. That is, although the messages may be strongly ordered within the queue, they will arrive at the different consumer instances and be processed out of order. By having a notion of parallelism&mdash;the partition&mdash;within the topics Kafka is able to provide both ordering guarantees and load balancing. This is achieved by assigning the partitions in the topic to the consumers in the consumer group so that each partition is consumed by exactly one consumer in the group. By doing this we ensure that the consumer is the only reader of that partition and consumes the data in order. Since there are many partitions this still balances the load over many consumer instances. Note however that there cannot be more consumer instances than partitions.
 <p>
 
 <h3>Guarantees</h3>
@@ -62,10 +68,8 @@ Kafka gives the following guarantees
   <li>For a topic with replication factor N, we will tolerate up to N-1 server failures without losing any messages committed to the log.
 </ul>
 
-<h3>Using Kafka</h3>
-
-
+<h3>Getting Started</h3>
 
-For more detailed information on how things work (and why) see our <a href="/08/design.html">design page</a>.
+For more detailed information on how things work and help getting started see our <a href="/08/design.html">design page</a> and overview of <a href="/uses.html">use cases</a>.
 
 <!--#include virtual="includes/footer.html" -->
\ No newline at end of file

Modified: kafka/site/styles.css
URL: http://svn.apache.org/viewvc/kafka/site/styles.css?rev=1498621&r1=1498620&r2=1498621&view=diff
==============================================================================
--- kafka/site/styles.css (original)
+++ kafka/site/styles.css Mon Jul  1 18:57:45 2013
@@ -106,3 +106,7 @@ a {
 	line-height: 200%;
 	color: #2e4a8e;
 }
+.caption {
+	font-size: 11pt; 
+	font-weight: bold
+}
\ No newline at end of file



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