Repository: kafka
Updated Branches:
  refs/heads/trunk 93b940016 -> ae9532c6b


MINOR: Fixed broken links in the documentation

Author: Vahid Hashemian <vahidhashem...@us.ibm.com>

Reviewers: Jason Gustafson <ja...@confluent.io>

Closes #2010 from vahidhashemian/doc/fix_hyperlinks


Project: http://git-wip-us.apache.org/repos/asf/kafka/repo
Commit: http://git-wip-us.apache.org/repos/asf/kafka/commit/ae9532c6
Tree: http://git-wip-us.apache.org/repos/asf/kafka/tree/ae9532c6
Diff: http://git-wip-us.apache.org/repos/asf/kafka/diff/ae9532c6

Branch: refs/heads/trunk
Commit: ae9532c6b3befe2b18d336004bb0976e9d27d08e
Parents: 93b9400
Author: Vahid Hashemian <vahidhashem...@us.ibm.com>
Authored: Tue Oct 11 20:25:35 2016 -0700
Committer: Jason Gustafson <ja...@confluent.io>
Committed: Tue Oct 11 20:25:35 2016 -0700

----------------------------------------------------------------------
 docs/api.html    | 8 ++++----
 docs/design.html | 8 ++++++--
 docs/ops.html    | 4 +++-
 3 files changed, 13 insertions(+), 7 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/kafka/blob/ae9532c6/docs/api.html
----------------------------------------------------------------------
diff --git a/docs/api.html b/docs/api.html
index 686b265..366814a 100644
--- a/docs/api.html
+++ b/docs/api.html
@@ -20,7 +20,7 @@ Kafka includes four core apis:
   <li>The <a href="#producerapi">Producer</a> API allows applications to send 
streams of data to topics in the Kafka cluster.
   <li>The <a href="#consumerapi">Consumer</a> API allows applications to read 
streams of data from topics in the Kafka cluster.
   <li>The <a href="#streamsapi">Streams</a> API allows transforming streams of 
data from input topics to output topics.
-  <li>The <a href="#producerapi">Connect</a> API allows implementing 
connectors that continually pull from some source system or application into 
Kafka or push from Kafka into some sink system or application.
+  <li>The <a href="#connectapi">Connect</a> API allows implementing connectors 
that continually pull from some source system or application into Kafka or push 
from Kafka into some sink system or application.
 </ol>
 
 Kafka exposes all its functionality over a language independent protocol which 
has clients available in many programming languages. However only the Java 
clients are maintained as part of the main Kafka project, the others are 
available as independent open source projects. A list of non-Java clients is 
available <a 
href="https://cwiki.apache.org/confluence/display/KAFKA/Clients";>here</a>.
@@ -58,7 +58,7 @@ To use the consumer, you can use the following maven 
dependency:
        &lt;/dependency&gt;
 </pre>
 
-<h3><a id="streamsapi" href="#streamsapi">Streams API</a></h3>
+<h3><a id="streamsapi" href="#streamsapi">2.3 Streams API</a></h3>
 
 The <a href="#streamsapi">Streams</a> API allows transforming streams of data 
from input topics to output topics.
 <p>
@@ -77,7 +77,7 @@ To use Kafka Streams you can use the following maven 
dependency:
        &lt;/dependency&gt;
 </pre>
 
-<h3><a id="connectapi" href="#connectapi">Connect API</a></h3>
+<h3><a id="connectapi" href="#connectapi">2.4 Connect API</a></h3>
 
 The Connect API allows implementing connectors that continually pull from some 
source data system into Kafka or push from Kafka into some sink data system.
 <p>
@@ -86,7 +86,7 @@ Many users of Connect won't need to use this API directly, 
though, they can use
 Those who want to implement custom connectors can see the <a 
href="/0100/javadoc/index.html?org/apache/kafka/connect" title="Kafka 0.10.0 
Javadoc">javadoc</a>.
 <p>
 
-<h3><a id="legacyapis" href="#streamsapi">Legacy APIs</a></h3>
+<h3><a id="legacyapis" href="#streamsapi">2.5 Legacy APIs</a></h3>
 
 <p>
 A more limited legacy producer and consumer api is also included in Kafka. 
These old Scala APIs are deprecated and only still available for compatibility 
purposes. Information on them can be found here <a 
href="/081/documentation.html#producerapi"  title="Kafka 0.8.1 Docs">

http://git-wip-us.apache.org/repos/asf/kafka/blob/ae9532c6/docs/design.html
----------------------------------------------------------------------
diff --git a/docs/design.html b/docs/design.html
index c8c10b4..9e53faf 100644
--- a/docs/design.html
+++ b/docs/design.html
@@ -327,8 +327,12 @@ makes a log more complete, ensuring log consistency during 
leader failure or cha
 <p>
 This majority vote approach has a very nice property: the latency is dependent 
on only the fastest servers. That is, if the replication factor is three, the 
latency is determined by the faster slave not the slower one.
 <p>
-There are a rich variety of algorithms in this family including ZooKeeper's <a 
href="http://www.stanford.edu/class/cs347/reading/zab.pdf";>Zab</a>, <a 
href="https://ramcloud.stanford.edu/wiki/download/attachments/11370504/raft.pdf";>Raft</a>,
-and <a href="http://pmg.csail.mit.edu/papers/vr-revisited.pdf";>Viewstamped 
Replication</a>. The most similar academic publication we are aware of to 
Kafka's actual implementation is <a 
href="http://research.microsoft.com/apps/pubs/default.aspx?id=66814";>PacificA</a>
 from Microsoft.
+There are a rich variety of algorithms in this family including ZooKeeper's
+<a 
href="http://web.archive.org/web/20140602093727/http://www.stanford.edu/class/cs347/reading/zab.pdf";>Zab</a>,
+<a 
href="https://ramcloud.stanford.edu/wiki/download/attachments/11370504/raft.pdf";>Raft</a>,
+and <a href="http://pmg.csail.mit.edu/papers/vr-revisited.pdf";>Viewstamped 
Replication</a>.
+The most similar academic publication we are aware of to Kafka's actual 
implementation is
+<a 
href="http://research.microsoft.com/apps/pubs/default.aspx?id=66814";>PacificA</a>
 from Microsoft.
 <p>
 The downside of majority vote is that it doesn't take many failures to leave 
you with no electable leaders. To tolerate one failure requires three copies of 
the data, and to tolerate two failures requires five copies
 of the data. In our experience having only enough redundancy to tolerate a 
single failure is not enough for a practical system, but doing every write five 
times, with 5x the disk space requirements and 1/5th the

http://git-wip-us.apache.org/repos/asf/kafka/blob/ae9532c6/docs/ops.html
----------------------------------------------------------------------
diff --git a/docs/ops.html b/docs/ops.html
index 236fef1..ed0c153 100644
--- a/docs/ops.html
+++ b/docs/ops.html
@@ -566,7 +566,9 @@ In general you don't need to do any low-level tuning of the 
filesystem, but in t
 
 In Linux, data written to the filesystem is maintained in <a 
href="http://en.wikipedia.org/wiki/Page_cache";>pagecache</a> until it must be 
written out to disk (due to an application-level fsync or the OS's own flush 
policy). The flushing of data is done by a set of background threads called 
pdflush (or in post 2.6.32 kernels "flusher threads").
 <p>
-Pdflush has a configurable policy that controls how much dirty data can be 
maintained in cache and for how long before it must be written back to disk. 
This policy is described <a 
href="http://www.westnet.com/~gsmith/content/linux-pdflush.htm";>here</a>. When 
Pdflush cannot keep up with the rate of data being written it will eventually 
cause the writing process to block incurring latency in the writes to slow down 
the accumulation of data.
+Pdflush has a configurable policy that controls how much dirty data can be 
maintained in cache and for how long before it must be written back to disk.
+This policy is described <a 
href="http://web.archive.org/web/20160518040713/http://www.westnet.com/~gsmith/content/linux-pdflush.htm";>here</a>.
+When Pdflush cannot keep up with the rate of data being written it will 
eventually cause the writing process to block incurring latency in the writes 
to slow down the accumulation of data.
 <p>
 You can see the current state of OS memory usage by doing
 <pre>

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