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From guozh...@apache.org
Subject [kafka-site] branch asf-site updated: KAFKA-7768: Use absolute paths for javadoc (#178)
Date Tue, 08 Jan 2019 00:46:05 GMT
This is an automated email from the ASF dual-hosted git repository.

guozhang pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/kafka-site.git


The following commit(s) were added to refs/heads/asf-site by this push:
     new b480383  KAFKA-7768: Use absolute paths for javadoc (#178)
b480383 is described below

commit b480383139bac2f139fef2ae87c6dd153cf7ecf4
Author: John Roesler <vvcephei@users.noreply.github.com>
AuthorDate: Mon Jan 7 18:46:01 2019 -0600

    KAFKA-7768: Use absolute paths for javadoc (#178)
    
    Reviewers: Guozhang Wang <wangguoz@gmail.com>
---
 21/streams/developer-guide/app-reset-tool.html     |   2 +-
 21/streams/developer-guide/config-streams.html     |  30 +++---
 21/streams/developer-guide/dsl-api.html            | 112 ++++++++++-----------
 .../developer-guide/interactive-queries.html       |   6 +-
 21/streams/developer-guide/processor-api.html      |   6 +-
 5 files changed, 78 insertions(+), 78 deletions(-)

diff --git a/21/streams/developer-guide/app-reset-tool.html b/21/streams/developer-guide/app-reset-tool.html
index 10cfffb..f42235a 100644
--- a/21/streams/developer-guide/app-reset-tool.html
+++ b/21/streams/developer-guide/app-reset-tool.html
@@ -141,7 +141,7 @@
                 use either of these methods:</p>
             <ul class="simple">
                 <li>The API method <code class="docutils literal"><span class="pre">KafkaStreams#cleanUp()</span></code> in your application code.</li>
-                <li>Manually delete the corresponding local state directory (default location: <code class="docutils literal"><span class="pre">/tmp/kafka-streams/&lt;application.id&gt;</span></code>). For more information, see <a href="../../../{{version}}/javadoc/org/apache/kafka/streams/StreamsConfig.html#STATE_DIR_CONFIG">Streams</a> javadocs.</li>
+                <li>Manually delete the corresponding local state directory (default location: <code class="docutils literal"><span class="pre">/tmp/kafka-streams/&lt;application.id&gt;</span></code>). For more information, see <a href="/{{version}}/javadoc/org/apache/kafka/streams/StreamsConfig.html#STATE_DIR_CONFIG">Streams</a> javadocs.</li>
             </ul>
 </div>
 </div>
diff --git a/21/streams/developer-guide/config-streams.html b/21/streams/developer-guide/config-streams.html
index 9472b4f..918399d 100644
--- a/21/streams/developer-guide/config-streams.html
+++ b/21/streams/developer-guide/config-streams.html
@@ -54,7 +54,7 @@
     </ol>
     <div class="section" id="configuration-parameter-reference">
       <span id="streams-developer-guide-required-configs"></span><h2>Configuration parameter reference<a class="headerlink" href="#configuration-parameter-reference" title="Permalink to this headline"></a></h2>
-      <p>This section contains the most common Streams configuration parameters. For a full reference, see the <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/StreamsConfig.html">Streams</a> Javadocs.</p>
+      <p>This section contains the most common Streams configuration parameters. For a full reference, see the <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/StreamsConfig.html">Streams</a> Javadocs.</p>
       <div class="contents local topic" id="contents">
         <ul class="simple">
           <li><a class="reference internal" href="#required-configuration-parameters" id="id3">Required configuration parameters</a><ul>
@@ -149,7 +149,7 @@
       </div>
       <div class="section" id="optional-configuration-parameters">
         <span id="streams-developer-guide-optional-configs"></span><h3><a class="toc-backref" href="#id6">Optional configuration parameters</a><a class="headerlink" href="#optional-configuration-parameters" title="Permalink to this headline"></a></h3>
-        <p>Here are the optional <a href="../../../{{version}}/javadoc/org/apache/kafka/streams/StreamsConfig.html">Streams</a> javadocs, sorted by level of importance:</p>
+        <p>Here are the optional <a href="/{{version}}/javadoc/org/apache/kafka/streams/StreamsConfig.html">Streams</a> javadocs, sorted by level of importance:</p>
         <blockquote>
           <div><ul class="simple">
             <li>High: These parameters can have a significant impact on performance. Take care when deciding the values of these parameters.</li>
@@ -305,11 +305,11 @@
               <code>FAIL</code> will signal that Streams should shut down and <code>CONTINUE</code> will signal that Streams should ignore the issue
               and continue processing. The following library built-in exception handlers are available:</p>
               <ul class="simple">
-                <li><a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/errors/LogAndContinueExceptionHandler.html">LogAndContinueExceptionHandler</a>:
+                <li><a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/errors/LogAndContinueExceptionHandler.html">LogAndContinueExceptionHandler</a>:
                   This handler logs the deserialization exception and then signals the processing pipeline to continue processing more records.
                   This log-and-skip strategy allows Kafka Streams to make progress instead of failing if there are records that fail
                   to deserialize.</li>
-                <li><a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/errors/LogAndFailExceptionHandler.html">LogAndFailExceptionHandler</a>.
+                <li><a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/errors/LogAndFailExceptionHandler.html">LogAndFailExceptionHandler</a>.
                   This handler logs the deserialization exception and then signals the processing pipeline to stop processing more records.</li>
               </ul>
 
@@ -354,7 +354,7 @@
           <span id="streams-developer-guide-peh"></span><h4><a class="toc-backref" href="#id24">default.production.exception.handler</a><a class="headerlink" href="#default-production-exception-handler" title="Permalink to this headline"></a></h4>
           <blockquote>
             <div><p>The default production exception handler allows you to manage exceptions triggered when trying to interact with a broker
-              such as attempting to produce a record that is too large. By default, Kafka provides and uses the <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/errors/DefaultProductionExceptionHandler.html">DefaultProductionExceptionHandler</a>
+              such as attempting to produce a record that is too large. By default, Kafka provides and uses the <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/errors/DefaultProductionExceptionHandler.html">DefaultProductionExceptionHandler</a>
               that always fails when these exceptions occur.</p>
 
             <p>Each exception handler can return a <code>FAIL</code> or <code>CONTINUE</code> depending on the record and the exception thrown. Returning <code>FAIL</code> will signal that Streams should shut down and <code>CONTINUE</code> will signal that Streams
@@ -439,7 +439,7 @@
           <span id="streams-developer-guide-partition-grouper"></span><h4><a class="toc-backref" href="#id12">partition.grouper</a><a class="headerlink" href="#partition-grouper" title="Permalink to this headline"></a></h4>
           <blockquote>
             <div>A partition grouper creates a list of stream tasks from the partitions of source topics, where each created task is assigned with a group of source topic partitions.
-              The default implementation provided by Kafka Streams is <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/processor/DefaultPartitionGrouper.html">DefaultPartitionGrouper</a>.
+              The default implementation provided by Kafka Streams is <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/processor/DefaultPartitionGrouper.html">DefaultPartitionGrouper</a>.
               It assigns each task with one partition for each of the source topic partitions. The generated number of tasks equals the largest
               number of partitions among the input topics. Usually an application does not need to customize the partition grouper.</div></blockquote>
         </div>
@@ -479,10 +479,10 @@
         <div class="section" id="timestamp-extractor">
           <span id="streams-developer-guide-timestamp-extractor"></span><h4><a class="toc-backref" href="#id15">timestamp.extractor</a><a class="headerlink" href="#timestamp-extractor" title="Permalink to this headline"></a></h4>
           <blockquote>
-            <div><p>A timestamp extractor pulls a timestamp from an instance of <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/clients/consumer/ConsumerRecord.html">ConsumerRecord</a>.
+            <div><p>A timestamp extractor pulls a timestamp from an instance of <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/clients/consumer/ConsumerRecord.html">ConsumerRecord</a>.
               Timestamps are used to control the progress of streams.</p>
               <p>The default extractor is
-                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/processor/FailOnInvalidTimestamp.html">FailOnInvalidTimestamp</a>.
+                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/processor/FailOnInvalidTimestamp.html">FailOnInvalidTimestamp</a>.
                 This extractor retrieves built-in timestamps that are automatically embedded into Kafka messages by the Kafka producer
                 client since
                 <a class="reference external" href="https://cwiki.apache.org/confluence/display/KAFKA/KIP-32+-+Add+timestamps+to+Kafka+message">Kafka version 0.10</a>.
@@ -504,19 +504,19 @@
               <p>If you have data with invalid timestamps and want to process it, then there are two alternative extractors available.
                 Both work on built-in timestamps, but handle invalid timestamps differently.</p>
               <ul class="simple">
-                <li><a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/processor/LogAndSkipOnInvalidTimestamp.html">LogAndSkipOnInvalidTimestamp</a>:
+                <li><a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/processor/LogAndSkipOnInvalidTimestamp.html">LogAndSkipOnInvalidTimestamp</a>:
                   This extractor logs a warn message and returns the invalid timestamp to Kafka Streams, which will not process but
                   silently drop the record.
                   This log-and-skip strategy allows Kafka Streams to make progress instead of failing if there are records with an
                   invalid built-in timestamp in your input data.</li>
-                <li><a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/processor/UsePreviousTimeOnInvalidTimestamp.html">UsePreviousTimeOnInvalidTimestamp</a>.
+                <li><a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/processor/UsePreviousTimeOnInvalidTimestamp.html">UsePreviousTimeOnInvalidTimestamp</a>.
                   This extractor returns the record&#8217;s built-in timestamp if it is valid (i.e. not negative).  If the record does not
                   have a valid built-in timestamps, the extractor returns the previously extracted valid timestamp from a record of the
                   same topic partition as the current record as a timestamp estimation.  In case that no timestamp can be estimated, it
                   throws an exception.</li>
               </ul>
               <p>Another built-in extractor is
-                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/processor/WallclockTimestampExtractor.html">WallclockTimestampExtractor</a>.
+                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/processor/WallclockTimestampExtractor.html">WallclockTimestampExtractor</a>.
                 This extractor does not actually &#8220;extract&#8221; a timestamp from the consumed record but rather returns the current time in
                 milliseconds from the system clock (think: <code class="docutils literal"><span class="pre">System.currentTimeMillis()</span></code>), which effectively means Streams will operate
                 on the basis of the so-called <strong>processing-time</strong> of events.</p>
@@ -568,10 +568,10 @@
       </div>
       <div class="section" id="kafka-consumers-and-producer-configuration-parameters">
         <h3><a class="toc-backref" href="#id16">Kafka consumers, producer and admin client configuration parameters</a><a class="headerlink" href="#kafka-consumers-and-producer-configuration-parameters" title="Permalink to this headline"></a></h3>
-        <p>You can specify parameters for the Kafka <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/clients/consumer/package-summary.html">consumers</a>, <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/clients/producer/package-summary.html">producers</a>,
-            and <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/kafka/clients/admin/package-summary.html">admin client</a> that are used internally.
+        <p>You can specify parameters for the Kafka <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/clients/consumer/package-summary.html">consumers</a>, <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/clients/producer/package-summary.html">producers</a>,
+            and <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/kafka/clients/admin/package-summary.html">admin client</a> that are used internally.
             The consumer, producer and admin client settings are defined by specifying parameters in a <code class="docutils literal"><span class="pre">StreamsConfig</span></code> instance.</p>
-        <p>In this example, the Kafka <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/clients/consumer/ConsumerConfig.html#SESSION_TIMEOUT_MS_CONFIG">consumer session timeout</a> is configured to be 60000 milliseconds in the Streams settings:</p>
+        <p>In this example, the Kafka <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/clients/consumer/ConsumerConfig.html#SESSION_TIMEOUT_MS_CONFIG">consumer session timeout</a> is configured to be 60000 milliseconds in the Streams settings:</p>
         <div class="highlight-java"><div class="highlight"><pre><span></span><span class="n">Properties</span> <span class="n">streamsSettings</span> <span class="o">=</span> <span class="k">new</span> <span class="n">Properties</span><span class="o">();</span>
 <span class="c1">// Example of a &quot;normal&quot; setting for Kafka Streams</span>
 <span class="n">streamsSettings</span><span class="o">.</span><span class="na">put</span><span class="o">(</span><span class="n">StreamsConfig</span><span class="o">.</span><span class="na">BOOTSTRAP_SERVERS_CONFIG</span><span class="o">,</span> <span class="s">&quot;kafka-broker-01:9092&quot;</span><span class="o">);</span>
@@ -680,7 +680,7 @@
           <span id="streams-developer-guide-rocksdb-config"></span><h4><a class="toc-backref" href="#id20">rocksdb.config.setter</a><a class="headerlink" href="#rocksdb-config-setter" title="Permalink to this headline"></a></h4>
           <blockquote>
             <div><p>The RocksDB configuration. Kafka Streams uses RocksDB as the default storage engine for persistent stores. To change the default
-              configuration for RocksDB, implement <code class="docutils literal"><span class="pre">RocksDBConfigSetter</span></code> and provide your custom class via <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/state/RocksDBConfigSetter.html">rocksdb.config.setter</a>.</p>
+              configuration for RocksDB, implement <code class="docutils literal"><span class="pre">RocksDBConfigSetter</span></code> and provide your custom class via <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/state/RocksDBConfigSetter.html">rocksdb.config.setter</a>.</p>
               <p>Here is an example that adjusts the memory size consumed by RocksDB.</p>
               <div class="highlight-java"><div class="highlight"><pre><span></span>    <span class="kd">public</span> <span class="kd">static</span> <span class="kd">class</span> <span class="nc">CustomRocksDBConfig</span> <span class="kd">implements</span> <span class="n">RocksDBConfigSetter</span> <span class="o">{</span>
 
diff --git a/21/streams/developer-guide/dsl-api.html b/21/streams/developer-guide/dsl-api.html
index b96df73..cf3f21b 100644
--- a/21/streams/developer-guide/dsl-api.html
+++ b/21/streams/developer-guide/dsl-api.html
@@ -104,7 +104,7 @@
             </ol>
             <p>After the application is run, the defined processor topologies are continuously executed (i.e., the processing plan is put into
                 action). A step-by-step guide for writing a stream processing application using the DSL is provided below.</p>
-            <p>For a complete list of available API functionality, see also the <a href="../../../{{version}}/javadoc/org/apache/kafka/streams/package-summary.html">Streams</a> API docs.</p>
+            <p>For a complete list of available API functionality, see also the <a href="/{{version}}/javadoc/org/apache/kafka/streams/package-summary.html">Streams</a> API docs.</p>
         </div>
 
         <div class="section" id="dsl-core-constructs-overview">
@@ -236,7 +236,7 @@
                     <td><p class="first">Creates a <a class="reference internal" href="#streams_concepts_kstream"><span class="std std-ref">KStream</span></a> from the specified Kafka input topics and interprets the data
                         as a <a class="reference internal" href="#streams_concepts_kstream"><span class="std std-ref">record stream</span></a>.
                         A <code class="docutils literal"><span class="pre">KStream</span></code> represents a <em>partitioned</em> record stream.
-                        <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#stream(java.lang.String)">(details)</a></p>
+                        <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#stream(java.lang.String)">(details)</a></p>
                         <p>In the case of a KStream, the local KStream instance of every application instance will
                             be populated with data from only <strong>a subset</strong> of the partitions of the input topic.  Collectively, across
                             all application instances, all input topic partitions are read and processed.</p>
@@ -270,7 +270,7 @@
                     <td><p class="first">Reads the specified Kafka input topic into a <a class="reference internal" href="#streams_concepts_ktable"><span class="std std-ref">KTable</span></a>.  The topic is
                         interpreted as a changelog stream, where records with the same key are interpreted as UPSERT aka INSERT/UPDATE
                         (when the record value is not <code class="docutils literal"><span class="pre">null</span></code>) or as DELETE (when the value is <code class="docutils literal"><span class="pre">null</span></code>) for that key.
-                        <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#table-java.lang.String(java.lang.String)">(details)</a></p>
+                        <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#table-java.lang.String(java.lang.String)">(details)</a></p>
                         <p>In the case of a KTable, the local KTable instance of every application instance will
                             be populated with data from only <strong>a subset</strong> of the partitions of the input topic.  Collectively, across
                             all application instances, all input topic partitions are read and processed.</p>
@@ -295,7 +295,7 @@
                     <td><p class="first">Reads the specified Kafka input topic into a <a class="reference internal" href="#streams_concepts_globalktable"><span class="std std-ref">GlobalKTable</span></a>.  The topic is
                         interpreted as a changelog stream, where records with the same key are interpreted as UPSERT aka INSERT/UPDATE
                         (when the record value is not <code class="docutils literal"><span class="pre">null</span></code>) or as DELETE (when the value is <code class="docutils literal"><span class="pre">null</span></code>) for that key.
-                        <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#globalTable-java.lang.String(java.lang.String)">(details)</a></p>
+                        <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#globalTable-java.lang.String(java.lang.String)">(details)</a></p>
                         <p>In the case of a GlobalKTable, the local GlobalKTable instance of every application instance will
                             be populated with data from <strong>all</strong> the partitions of the input topic.</p>
                         <p>You must provide a name for the table (more precisely, for the internal
@@ -366,7 +366,7 @@
                         </ul>
                     </td>
                         <td><p class="first">Branch (or split) a <code class="docutils literal"><span class="pre">KStream</span></code> based on the supplied predicates into one or more <code class="docutils literal"><span class="pre">KStream</span></code> instances.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#branch-org.apache.kafka.streams.kstream.Predicate...-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#branch-org.apache.kafka.streams.kstream.Predicate...-">details</a>)</p>
                             <p>Predicates are evaluated in order.  A record is placed to one and only one output stream on the first match:
                                 if the n-th predicate evaluates to true, the record is placed to n-th stream.  If no predicate matches, the
                                 the record is dropped.</p>
@@ -394,8 +394,8 @@
                         </ul>
                     </td>
                         <td><p class="first">Evaluates a boolean function for each element and retains those for which the function returns true.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#filter-org.apache.kafka.streams.kstream.Predicate-">KStream details</a>,
-                            <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#filter-org.apache.kafka.streams.kstream.Predicate-">KTable details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#filter-org.apache.kafka.streams.kstream.Predicate-">KStream details</a>,
+                            <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#filter-org.apache.kafka.streams.kstream.Predicate-">KTable details</a>)</p>
                             <div class="last highlight-java"><div class="highlight"><pre><span></span><span class="n">KStream</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Long</span><span class="o">&gt;</span> <span class="n">stream</span> <span class="o">=</span> <span class="o">...;</span>
 
 <span class="c1">// A filter that selects (keeps) only positive numbers</span>
@@ -421,8 +421,8 @@
                         </ul>
                     </td>
                         <td><p class="first">Evaluates a boolean function for each element and drops those for which the function returns true.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#filterNot-org.apache.kafka.streams.kstream.Predicate-">KStream details</a>,
-                            <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#filterNot-org.apache.kafka.streams.kstream.Predicate-">KTable details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#filterNot-org.apache.kafka.streams.kstream.Predicate-">KStream details</a>,
+                            <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#filterNot-org.apache.kafka.streams.kstream.Predicate-">KTable details</a>)</p>
                             <div class="last highlight-java"><div class="highlight"><pre><span></span><span class="n">KStream</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Long</span><span class="o">&gt;</span> <span class="n">stream</span> <span class="o">=</span> <span class="o">...;</span>
 
 <span class="c1">// An inverse filter that discards any negative numbers or zero</span>
@@ -448,7 +448,7 @@
                     </td>
                         <td><p class="first">Takes one record and produces zero, one, or more records.  You can modify the record keys and values, including
                             their types.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMap-org.apache.kafka.streams.kstream.KeyValueMapper-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMap-org.apache.kafka.streams.kstream.KeyValueMapper-">details</a>)</p>
                             <p><strong>Marks the stream for data re-partitioning:</strong>
                                 Applying a grouping or a join after <code class="docutils literal"><span class="pre">flatMap</span></code> will result in re-partitioning of the records.
                                 If possible use <code class="docutils literal"><span class="pre">flatMapValues</span></code> instead, which will not cause data re-partitioning.</p>
@@ -477,7 +477,7 @@
                     </td>
                         <td><p class="first">Takes one record and produces zero, one, or more records, while retaining the key of the original record.
                             You can modify the record values and the value type.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMapValues-org.apache.kafka.streams.kstream.ValueMapper-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMapValues-org.apache.kafka.streams.kstream.ValueMapper-">details</a>)</p>
                             <p><code class="docutils literal"><span class="pre">flatMapValues</span></code> is preferable to <code class="docutils literal"><span class="pre">flatMap</span></code> because it will not cause data re-partitioning.  However, you
                                 cannot modify the key or key type like <code class="docutils literal"><span class="pre">flatMap</span></code> does.</p>
                             <div class="last highlight-java"><div class="highlight"><pre><span></span><span class="c1">// Split a sentence into words.</span>
@@ -497,7 +497,7 @@
                         </ul>
                     </td>
                         <td><p class="first"><strong>Terminal operation.</strong>  Performs a stateless action on each record.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#foreach-org.apache.kafka.streams.kstream.ForeachAction-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#foreach-org.apache.kafka.streams.kstream.ForeachAction-">details</a>)</p>
                             <p>You would use <code class="docutils literal"><span class="pre">foreach</span></code> to cause <em>side effects</em> based on the input data (similar to <code class="docutils literal"><span class="pre">peek</span></code>) and then <em>stop</em>
                                 <em>further processing</em> of the input data (unlike <code class="docutils literal"><span class="pre">peek</span></code>, which is not a terminal operation).</p>
                             <p><strong>Note on processing guarantees:</strong> Any side effects of an action (such as writing to external systems) are not
@@ -526,7 +526,7 @@
                         </ul>
                     </td>
                         <td><p class="first">Groups the records by the existing key.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupByKey--">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupByKey--">details</a>)</p>
                             <p>Grouping is a prerequisite for <a class="reference internal" href="#streams-developer-guide-dsl-aggregating"><span class="std std-ref">aggregating a stream or a table</span></a>
                                 and ensures that data is properly partitioned (&#8220;keyed&#8221;) for subsequent operations.</p>
                             <p><strong>When to set explicit SerDes:</strong>
@@ -571,8 +571,8 @@
                         <td><p class="first">Groups the records by a <em>new</em> key, which may be of a different key type.
                             When grouping a table, you may also specify a new value and value type.
                             <code class="docutils literal"><span class="pre">groupBy</span></code> is a shorthand for <code class="docutils literal"><span class="pre">selectKey(...).groupByKey()</span></code>.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-">KStream details</a>,
-                            <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-">KTable details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-">KStream details</a>,
+                            <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-">KTable details</a>)</p>
                             <p>Grouping is a prerequisite for <a class="reference internal" href="#streams-developer-guide-dsl-aggregating"><span class="std std-ref">aggregating a stream or a table</span></a>
                                 and ensures that data is properly partitioned (&#8220;keyed&#8221;) for subsequent operations.</p>
                             <p><strong>When to set explicit SerDes:</strong>
@@ -648,7 +648,7 @@
                         </ul>
                     </td>
                         <td><p class="first">Takes one record and produces one record.  You can modify the record key and value, including their types.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#map-org.apache.kafka.streams.kstream.KeyValueMapper-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#map-org.apache.kafka.streams.kstream.KeyValueMapper-">details</a>)</p>
                             <p><strong>Marks the stream for data re-partitioning:</strong>
                                 Applying a grouping or a join after <code class="docutils literal"><span class="pre">map</span></code> will result in re-partitioning of the records.
                                 If possible use <code class="docutils literal"><span class="pre">mapValues</span></code> instead, which will not cause data re-partitioning.</p>
@@ -680,8 +680,8 @@
                     </td>
                         <td><p class="first">Takes one record and produces one record, while retaining the key of the original record.
                             You can modify the record value and the value type.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-">KStream details</a>,
-                            <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-">KTable details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-">KStream details</a>,
+                            <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-">KTable details</a>)</p>
                             <p><code class="docutils literal"><span class="pre">mapValues</span></code> is preferable to <code class="docutils literal"><span class="pre">map</span></code> because it will not cause data re-partitioning.  However, it does not
                                 allow you to modify the key or key type like <code class="docutils literal"><span class="pre">map</span></code> does.</p>
                             <div class="last highlight-java"><div class="highlight"><pre><span></span><span class="n">KStream</span><span class="o">&lt;</span><span class="kt">byte</span><span class="o">[],</span> <span class="n">String</span><span class="o">&gt;</span> <span class="n">stream</span> <span class="o">=</span> <span class="o">...;</span>
@@ -708,7 +708,7 @@
                     </td>
                         <td><p class="first">Merges records of two streams into one larger stream.
                             (<a class="reference external"
-                            href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#merge-org.apache.kafka.streams.kstream.KStream-">details</a>)
+                            href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#merge-org.apache.kafka.streams.kstream.KStream-">details</a>)
                             <p>There is no ordering guarantee between records
                             from different streams in the merged stream. Relative order is preserved within each input stream though (ie, records within the same input stream are processed in order)</p>
                             <div class="last highlight-java">
@@ -730,7 +730,7 @@
                         </ul>
                     </td>
                         <td><p class="first">Performs a stateless action on each record, and returns an unchanged stream.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#peek-org.apache.kafka.streams.kstream.ForeachAction-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#peek-org.apache.kafka.streams.kstream.ForeachAction-">details</a>)</p>
                             <p>You would use <code class="docutils literal"><span class="pre">peek</span></code> to cause <em>side effects</em> based on the input data (similar to <code class="docutils literal"><span class="pre">foreach</span></code>) and <em>continue</em>
                                 <em>processing</em> the input data (unlike <code class="docutils literal"><span class="pre">foreach</span></code>, which is a terminal operation).  <code class="docutils literal"><span class="pre">peek</span></code> returns the input
                                 stream as-is;  if you need to modify the input stream, use <code class="docutils literal"><span class="pre">map</span></code> or <code class="docutils literal"><span class="pre">mapValues</span></code> instead.</p>
@@ -762,7 +762,7 @@
                     </td>
                         <td><p class="first"><strong>Terminal operation.</strong>  Prints the records to <code class="docutils literal"><span class="pre">System.out</span></code>.  See Javadocs for serde and <code class="docutils literal"><span class="pre">toString()</span></code>
                             caveats.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#print--">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#print--">details</a>)</p>
                             <p>Calling <code class="docutils literal"><span class="pre">print()</span></code> is the same as calling <code class="docutils literal"><span class="pre">foreach((key,</span> <span class="pre">value)</span> <span class="pre">-&gt;</span> <span class="pre">System.out.println(key</span> <span class="pre">+</span> <span class="pre">&quot;,</span> <span class="pre">&quot;</span> <span class="pre">+</span> <span class="pre">value))</span></code></p>
                             <p><code class="docutils literal"><span class="pre">print</span></code> is mainly for debugging/testing purposes, and it will try to flush on each record print. Hence it <strong>should not</strong> be used for production usage if performance requirements are concerned.</p>
                             <div class="last highlight-java"><div class="highlight"><pre><span></span><span class="n">KStream</span><span class="o">&lt;</span><span class="kt">byte</span><span class="o">[],</span> <span class="n">String</span><span class="o">&gt;</span> <span class="n">stream</span> <span class="o">=</span> <span class="o">...;</span>
@@ -781,7 +781,7 @@
                         </ul>
                     </td>
                         <td><p class="first">Assigns a new key &#8211; possibly of a new key type &#8211; to each record.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#selectKey-org.apache.kafka.streams.kstream.KeyValueMapper-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#selectKey-org.apache.kafka.streams.kstream.KeyValueMapper-">details</a>)</p>
                             <p>Calling <code class="docutils literal"><span class="pre">selectKey(mapper)</span></code> is the same as calling <code class="docutils literal"><span class="pre">map((key,</span> <span class="pre">value)</span> <span class="pre">-&gt;</span> <span class="pre">mapper(key,</span> <span class="pre">value),</span> <span class="pre">value)</span></code>.</p>
                             <p><strong>Marks the stream for data re-partitioning:</strong>
                                 Applying a grouping or a join after <code class="docutils literal"><span class="pre">selectKey</span></code> will result in re-partitioning of the records.</p>
@@ -809,7 +809,7 @@
                         </ul>
                     </td>
                         <td><p class="first">Get the changelog stream of this table.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#toStream--">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#toStream--">details</a>)</p>
                             <div class="last highlight-java"><div class="highlight"><pre><span></span><span class="n">KTable</span><span class="o">&lt;</span><span class="kt">byte</span><span class="o">[],</span> <span class="n">String</span><span class="o">&gt;</span> <span class="n">table</span> <span class="o">=</span> <span class="o">...;</span>
 
 <span class="c1">// Also, a variant of `toStream` exists that allows you</span>
@@ -913,8 +913,8 @@
                             <td><p class="first"><strong>Rolling aggregation.</strong> Aggregates the values of (non-windowed) records by the grouped key.
                                 Aggregating is a generalization of <code class="docutils literal"><span class="pre">reduce</span></code> and allows, for example, the aggregate value to have a different
                                 type than the input values.
-                                (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html">KGroupedStream details</a>,
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html">KGroupedTable details</a>)</p>
+                                (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html">KGroupedStream details</a>,
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html">KGroupedTable details</a>)</p>
                                 <p>When aggregating a <em>grouped stream</em>, you must provide an initializer (e.g., <code class="docutils literal"><span class="pre">aggValue</span> <span class="pre">=</span> <span class="pre">0</span></code>) and an &#8220;adder&#8221;
                                     aggregator (e.g., <code class="docutils literal"><span class="pre">aggValue</span> <span class="pre">+</span> <span class="pre">curValue</span></code>).  When aggregating a <em>grouped table</em>, you must provide a
                                     &#8220;subtractor&#8221; aggregator (think: <code class="docutils literal"><span class="pre">aggValue</span> <span class="pre">-</span> <span class="pre">oldValue</span></code>).</p>
@@ -1016,8 +1016,8 @@
                                 Aggregates the values of records, <a class="reference internal" href="#streams-developer-guide-dsl-windowing"><span class="std std-ref">per window</span></a>, by the grouped key.
                                 Aggregating is a generalization of <code class="docutils literal"><span class="pre">reduce</span></code> and allows, for example, the aggregate value to have a different
                                 type than the input values.
-                                (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html">TimeWindowedKStream details</a>,
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html">SessionWindowedKStream details</a>)</p>
+                                (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html">TimeWindowedKStream details</a>,
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html">SessionWindowedKStream details</a>)</p>
                                 <p>You must provide an initializer (e.g.,  <code class="docutils literal"><span class="pre">aggValue</span> <span class="pre">=</span> <span class="pre">0</span></code>), &#8220;adder&#8221; aggregator (e.g.,  <code class="docutils literal"><span class="pre">aggValue</span> <span class="pre">+</span> <span class="pre">curValue</span></code>),
                                     and a window.  When windowing based on sessions, you must additionally provide a &#8220;session merger&#8221; aggregator
                                     (e.g.,  <code class="docutils literal"><span class="pre">mergedAggValue</span> <span class="pre">=</span> <span class="pre">leftAggValue</span> <span class="pre">+</span> <span class="pre">rightAggValue</span></code>).</p>
@@ -1111,8 +1111,8 @@
                             </ul>
                         </td>
                             <td><p class="first"><strong>Rolling aggregation.</strong> Counts the number of records by the grouped key.
-                                (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html">KGroupedStream details</a>,
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html">KGroupedTable details</a>)</p>
+                                (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html">KGroupedStream details</a>,
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html">KGroupedTable details</a>)</p>
                                 <p>Several variants of <code class="docutils literal"><span class="pre">count</span></code> exist, see Javadocs for details.</p>
                                 <div class="highlight-java"><div class="highlight"><pre><span></span><span class="n">KGroupedStream</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Long</span><span class="o">&gt;</span> <span class="n">groupedStream</span> <span class="o">=</span> <span class="o">...;</span>
 <span class="n">KGroupedTable</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Long</span><span class="o">&gt;</span> <span class="n">groupedTable</span> <span class="o">=</span> <span class="o">...;</span>
@@ -1142,8 +1142,8 @@
                         </td>
                             <td><p class="first"><strong>Windowed aggregation.</strong>
                                 Counts the number of records, <a class="reference internal" href="#streams-developer-guide-dsl-windowing"><span class="std std-ref">per window</span></a>, by the grouped key.
-                                (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html">TimeWindowedKStream details</a>,
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html">SessionWindowedKStream details</a>)</p>
+                                (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html">TimeWindowedKStream details</a>,
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html">SessionWindowedKStream details</a>)</p>
                                 <p>The windowed <code class="docutils literal"><span class="pre">count</span></code> turns a <code class="docutils literal"><span class="pre">TimeWindowedKStream&lt;K,</span> <span class="pre">V&gt;</span></code> or <code class="docutils literal"><span class="pre">SessionWindowedKStream&lt;K,</span> <span class="pre">V&gt;</span></code>
                                     into a windowed <code class="docutils literal"><span class="pre">KTable&lt;Windowed&lt;K&gt;,</span> <span class="pre">V&gt;</span></code>.</p>
                                 <p>Several variants of <code class="docutils literal"><span class="pre">count</span></code> exist, see Javadocs for details.</p>
@@ -1176,8 +1176,8 @@
                             <td><p class="first"><strong>Rolling aggregation.</strong> Combines the values of (non-windowed) records by the grouped key.
                                 The current record value is combined with the last reduced value, and a new reduced value is returned.
                                 The result value type cannot be changed, unlike <code class="docutils literal"><span class="pre">aggregate</span></code>.
-                                (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html">KGroupedStream details</a>,
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html">KGroupedTable details</a>)</p>
+                                (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html">KGroupedStream details</a>,
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html">KGroupedTable details</a>)</p>
                                 <p>When reducing a <em>grouped stream</em>, you must provide an &#8220;adder&#8221; reducer (e.g.,  <code class="docutils literal"><span class="pre">aggValue</span> <span class="pre">+</span> <span class="pre">curValue</span></code>).
                                     When reducing a <em>grouped table</em>, you must additionally provide a &#8220;subtractor&#8221; reducer (e.g.,
                                     <code class="docutils literal"><span class="pre">aggValue</span> <span class="pre">-</span> <span class="pre">oldValue</span></code>).</p>
@@ -1260,8 +1260,8 @@
                                 The current record value is combined with the last reduced value, and a new reduced value is returned.
                                 Records with <code class="docutils literal"><span class="pre">null</span></code> key or value are ignored.
                                 The result value type cannot be changed, unlike <code class="docutils literal"><span class="pre">aggregate</span></code>.
-                                (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html">TimeWindowedKStream details</a>,
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html">SessionWindowedKStream details</a>)</p>
+                                (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html">TimeWindowedKStream details</a>,
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html">SessionWindowedKStream details</a>)</p>
                                 <p>The windowed <code class="docutils literal"><span class="pre">reduce</span></code> turns a turns a <code class="docutils literal"><span class="pre">TimeWindowedKStream&lt;K,</span> <span class="pre">V&gt;</span></code> or a <code class="docutils literal"><span class="pre">SessionWindowedKStream&lt;K,</span> <span class="pre">V&gt;</span></code>
                                     into a windowed <code class="docutils literal"><span class="pre">KTable&lt;Windowed&lt;K&gt;,</span> <span class="pre">V&gt;</span></code>.</p>
                                 <p>Several variants of <code class="docutils literal"><span class="pre">reduce</span></code> exist, see Javadocs for details.</p>
@@ -1760,7 +1760,7 @@
                             </td>
                                 <td><p class="first">Performs an INNER JOIN of this stream with another stream.
                                     Even though this operation is windowed, the joined stream will be of type <code class="docutils literal"><span class="pre">KStream&lt;K,</span> <span class="pre">...&gt;</span></code> rather than <code class="docutils literal"><span class="pre">KStream&lt;Windowed&lt;K&gt;,</span> <span class="pre">...&gt;</span></code>.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <p><strong>Causes data re-partitioning of a stream if and only if the stream was marked for re-partitioning (if both are marked, both are re-partitioned).</strong></p>
                                     <p>Several variants of <code class="docutils literal"><span class="pre">join</span></code> exists, see the Javadocs for details.</p>
@@ -1819,7 +1819,7 @@
                             </td>
                                 <td><p class="first">Performs a LEFT JOIN of this stream with another stream.
                                     Even though this operation is windowed, the joined stream will be of type <code class="docutils literal"><span class="pre">KStream&lt;K,</span> <span class="pre">...&gt;</span></code> rather than <code class="docutils literal"><span class="pre">KStream&lt;Windowed&lt;K&gt;,</span> <span class="pre">...&gt;</span></code>.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <p><strong>Causes data re-partitioning of a stream if and only if the stream was marked for re-partitioning (if both are marked, both are re-partitioned).</strong></p>
                                     <p>Several variants of <code class="docutils literal"><span class="pre">leftJoin</span></code> exists, see the Javadocs for details.</p>
@@ -1881,7 +1881,7 @@
                             </td>
                                 <td><p class="first">Performs an OUTER JOIN of this stream with another stream.
                                     Even though this operation is windowed, the joined stream will be of type <code class="docutils literal"><span class="pre">KStream&lt;K,</span> <span class="pre">...&gt;</span></code> rather than <code class="docutils literal"><span class="pre">KStream&lt;Windowed&lt;K&gt;,</span> <span class="pre">...&gt;</span></code>.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#outerJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#outerJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <p><strong>Causes data re-partitioning of a stream if and only if the stream was marked for re-partitioning (if both are marked, both are re-partitioned).</strong></p>
                                     <p>Several variants of <code class="docutils literal"><span class="pre">outerJoin</span></code> exists, see the Javadocs for details.</p>
@@ -1942,7 +1942,7 @@
                             The semantics of the various stream-stream join variants are explained below.
                             To improve the readability of the table, assume that (1) all records have the same key (and thus the key in the table is omitted), (2) all records belong to a single join window, and (3) all records are processed in timestamp order.
                             The columns INNER JOIN, LEFT JOIN, and OUTER JOIN denote what is passed as arguments to the user-supplied
-                            <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html">ValueJoiner</a> for the <code class="docutils literal"><span class="pre">join</span></code>, <code class="docutils literal"><span class="pre">leftJoin</span></code>, and
+                            <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html">ValueJoiner</a> for the <code class="docutils literal"><span class="pre">join</span></code>, <code class="docutils literal"><span class="pre">leftJoin</span></code>, and
                             <code class="docutils literal"><span class="pre">outerJoin</span></code> methods, respectively, whenever a new input record is received on either side of the join.  An empty table
                             cell denotes that the <code class="docutils literal"><span class="pre">ValueJoiner</span></code> is not called at all.</p>
                         <table border="1" class="docutils">
@@ -2100,7 +2100,7 @@
                             </td>
                                 <td><p class="first">Performs an INNER JOIN of this table with another table.
                                     The result is an ever-updating KTable that represents the &#8220;current&#8221; result of the join.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <div class="highlight-java"><div class="highlight"><pre><span></span><span class="n">KTable</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Long</span><span class="o">&gt;</span> <span class="n">left</span> <span class="o">=</span> <span class="o">...;</span>
 <span class="n">KTable</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Double</span><span class="o">&gt;</span> <span class="n">right</span> <span class="o">=</span> <span class="o">...;</span>
@@ -2146,7 +2146,7 @@
                                 </ul>
                             </td>
                                 <td><p class="first">Performs a LEFT JOIN of this table with another table.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <div class="highlight-java"><div class="highlight"><pre><span></span><span class="n">KTable</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Long</span><span class="o">&gt;</span> <span class="n">left</span> <span class="o">=</span> <span class="o">...;</span>
 <span class="n">KTable</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Double</span><span class="o">&gt;</span> <span class="n">right</span> <span class="o">=</span> <span class="o">...;</span>
@@ -2195,7 +2195,7 @@
                                 </ul>
                             </td>
                                 <td><p class="first">Performs an OUTER JOIN of this table with another table.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#outerJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KTable.html#outerJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <div class="highlight-java"><div class="highlight"><pre><span></span><span class="n">KTable</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Long</span><span class="o">&gt;</span> <span class="n">left</span> <span class="o">=</span> <span class="o">...;</span>
 <span class="n">KTable</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Double</span><span class="o">&gt;</span> <span class="n">right</span> <span class="o">=</span> <span class="o">...;</span>
@@ -2244,7 +2244,7 @@
                             The semantics of the various table-table join variants are explained below.
                             To improve the readability of the table, you can assume that (1) all records have the same key (and thus the key in the table is omitted) and that (2) all records are processed in timestamp order.
                             The columns INNER JOIN, LEFT JOIN, and OUTER JOIN denote what is passed as arguments to the user-supplied
-                            <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html">ValueJoiner</a> for the <code class="docutils literal"><span class="pre">join</span></code>, <code class="docutils literal"><span class="pre">leftJoin</span></code>, and
+                            <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html">ValueJoiner</a> for the <code class="docutils literal"><span class="pre">join</span></code>, <code class="docutils literal"><span class="pre">leftJoin</span></code>, and
                             <code class="docutils literal"><span class="pre">outerJoin</span></code> methods, respectively, whenever a new input record is received on either side of the join.  An empty table
                             cell denotes that the <code class="docutils literal"><span class="pre">ValueJoiner</span></code> is not called at all.</p>
                         <table border="1" class="docutils">
@@ -2408,7 +2408,7 @@
                                 </ul>
                             </td>
                                 <td><p class="first">Performs an INNER JOIN of this stream with the table, effectively doing a table lookup.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <p><strong>Causes data re-partitioning of the stream if and only if the stream was marked for re-partitioning.</strong></p>
                                     <p>Several variants of <code class="docutils literal"><span class="pre">join</span></code> exists, see the Javadocs for details.</p>
@@ -2461,7 +2461,7 @@
                                 </ul>
                             </td>
                                 <td><p class="first">Performs a LEFT JOIN of this stream with the table, effectively doing a table lookup.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
                                     <p><strong>Data must be co-partitioned</strong>: The input data for both sides must be <a class="reference internal" href="#streams-developer-guide-dsl-joins-co-partitioning"><span class="std std-ref">co-partitioned</span></a>.</p>
                                     <p><strong>Causes data re-partitioning of the stream if and only if the stream was marked for re-partitioning.</strong></p>
                                     <p>Several variants of <code class="docutils literal"><span class="pre">leftJoin</span></code> exists, see the Javadocs for details.</p>
@@ -2517,7 +2517,7 @@
                             To improve the readability of the table we assume that (1) all records have the same key (and thus we omit the key in
                             the table) and that (2) all records are processed in timestamp order.
                             The columns INNER JOIN and LEFT JOIN denote what is passed as arguments to the user-supplied
-                            <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html">ValueJoiner</a> for the <code class="docutils literal"><span class="pre">join</span></code> and <code class="docutils literal"><span class="pre">leftJoin</span></code>
+                            <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html">ValueJoiner</a> for the <code class="docutils literal"><span class="pre">join</span></code> and <code class="docutils literal"><span class="pre">leftJoin</span></code>
                             methods, respectively, whenever a new input record is received on either side of the join.  An empty table
                             cell denotes that the <code class="docutils literal"><span class="pre">ValueJoiner</span></code> is not called at all.</p>
                         <table border="1" class="docutils">
@@ -2679,7 +2679,7 @@
                                 </ul>
                             </td>
                                 <td><p class="first">Performs an INNER JOIN of this stream with the global table, effectively doing a table lookup.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
                                     <p>The <code class="docutils literal"><span class="pre">GlobalKTable</span></code> is fully bootstrapped upon (re)start of a <code class="docutils literal"><span class="pre">KafkaStreams</span></code> instance, which means the table is fully populated with all the data in the underlying topic that is
                                         available at the time of the startup.  The actual data processing begins only once the bootstrapping has completed.</p>
                                     <p><strong>Causes data re-partitioning of the stream if and only if the stream was marked for re-partitioning.</strong></p>
@@ -2733,7 +2733,7 @@
                                 </ul>
                             </td>
                                 <td><p class="first">Performs a LEFT JOIN of this stream with the global table, effectively doing a table lookup.
-                                    <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
+                                    <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-">(details)</a></p>
                                     <p>The <code class="docutils literal"><span class="pre">GlobalKTable</span></code> is fully bootstrapped upon (re)start of a <code class="docutils literal"><span class="pre">KafkaStreams</span></code> instance, which means the table is fully populated with all the data in the underlying topic that is
                                         available at the time of the startup.  The actual data processing begins only once the bootstrapping has completed.</p>
                                     <p><strong>Causes data re-partitioning of the stream if and only if the stream was marked for re-partitioning.</strong></p>
@@ -3076,11 +3076,11 @@ grouped
                     </td>
                         <td><p class="first"><strong>Terminal operation.</strong>  Applies a <code class="docutils literal"><span class="pre">Processor</span></code> to each record.
                             <code class="docutils literal"><span class="pre">process()</span></code> allows you to leverage the <a class="reference internal" href="processor-api.html#streams-developer-guide-processor-api"><span class="std std-ref">Processor API</span></a> from the DSL.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#process-org.apache.kafka.streams.processor.ProcessorSupplier-java.lang.String...-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#process-org.apache.kafka.streams.processor.ProcessorSupplier-java.lang.String...-">details</a>)</p>
                             <p>This is essentially equivalent to adding the <code class="docutils literal"><span class="pre">Processor</span></code> via <code class="docutils literal"><span class="pre">Topology#addProcessor()</span></code> to your
                                 <a class="reference internal" href="../core-concepts.html#streams_topology"><span class="std std-ref">processor topology</span></a>.</p>
                             <p class="last">An example is available in the
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#process-org.apache.kafka.streams.processor.ProcessorSupplier-java.lang.String...-">javadocs</a>.</p>
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#process-org.apache.kafka.streams.processor.ProcessorSupplier-java.lang.String...-">javadocs</a>.</p>
                         </td>
                     </tr>
                     <tr class="row-odd"><td><p class="first"><strong>Transform</strong></p>
@@ -3090,7 +3090,7 @@ grouped
                     </td>
                         <td><p class="first">Applies a <code class="docutils literal"><span class="pre">Transformer</span></code> to each record.
                             <code class="docutils literal"><span class="pre">transform()</span></code> allows you to leverage the <a class="reference internal" href="processor-api.html#streams-developer-guide-processor-api"><span class="std std-ref">Processor API</span></a> from the DSL.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transform-org.apache.kafka.streams.kstream.TransformerSupplier-java.lang.String...-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transform-org.apache.kafka.streams.kstream.TransformerSupplier-java.lang.String...-">details</a>)</p>
                             <p>Each input record is transformed into zero, one, or more output records (similar to the stateless <code class="docutils literal"><span class="pre">flatMap</span></code>).
                                 The <code class="docutils literal"><span class="pre">Transformer</span></code> must return <code class="docutils literal"><span class="pre">null</span></code> for zero output.
                                 You can modify the record&#8217;s key and value, including their types.</p>
@@ -3100,7 +3100,7 @@ grouped
                             <p><code class="docutils literal"><span class="pre">transform</span></code> is essentially equivalent to adding the <code class="docutils literal"><span class="pre">Transformer</span></code> via <code class="docutils literal"><span class="pre">Topology#addProcessor()</span></code> to your
                                 <a class="reference internal" href="../core-concepts.html#streams_topology"><span class="std std-ref">processor topology</span></a>.</p>
                             <p class="last">An example is available in the
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transform-org.apache.kafka.streams.kstream.TransformerSupplier-java.lang.String...-">javadocs</a>.
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transform-org.apache.kafka.streams.kstream.TransformerSupplier-java.lang.String...-">javadocs</a>.
                                </p>
                         </td>
                     </tr>
@@ -3112,14 +3112,14 @@ grouped
                     </td>
                         <td><p class="first">Applies a <code class="docutils literal"><span class="pre">ValueTransformer</span></code> to each record, while retaining the key of the original record.
                             <code class="docutils literal"><span class="pre">transformValues()</span></code> allows you to leverage the <a class="reference internal" href="processor-api.html#streams-developer-guide-processor-api"><span class="std std-ref">Processor API</span></a> from the DSL.
-                            (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transformValues-org.apache.kafka.streams.kstream.ValueTransformerSupplier-java.lang.String...-">details</a>)</p>
+                            (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transformValues-org.apache.kafka.streams.kstream.ValueTransformerSupplier-java.lang.String...-">details</a>)</p>
                             <p>Each input record is transformed into exactly one output record (zero output records or multiple output records are not possible).
                                 The <code class="docutils literal"><span class="pre">ValueTransformer</span></code> may return <code class="docutils literal"><span class="pre">null</span></code> as the new value for a record.</p>
                             <p><code class="docutils literal"><span class="pre">transformValues</span></code> is preferable to <code class="docutils literal"><span class="pre">transform</span></code> because it will not cause data re-partitioning.</p>
                             <p><code class="docutils literal"><span class="pre">transformValues</span></code> is essentially equivalent to adding the <code class="docutils literal"><span class="pre">ValueTransformer</span></code> via <code class="docutils literal"><span class="pre">Topology#addProcessor()</span></code> to your
                                 <a class="reference internal" href="../core-concepts.html#streams_topology"><span class="std std-ref">processor topology</span></a>.</p>
                             <p class="last">An example is available in the
-                                <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transformValues-org.apache.kafka.streams.kstream.ValueTransformerSupplier-java.lang.String...-">javadocs</a>.</p>
+                                <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#transformValues-org.apache.kafka.streams.kstream.ValueTransformerSupplier-java.lang.String...-">javadocs</a>.</p>
                         </td>
                     </tr>
                     </tbody>
@@ -3269,7 +3269,7 @@ groupedTable
                     </ul>
                 </td>
                     <td><p class="first"><strong>Terminal operation.</strong>  Write the records to Kafka topic(s).
-                        (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#to(java.lang.String)">KStream details</a>)</p>
+                        (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#to(java.lang.String)">KStream details</a>)</p>
                         <p>When to provide serdes explicitly:</p>
                         <ul class="simple">
                             <li>If you do not specify SerDes explicitly, the default SerDes from the
@@ -3318,7 +3318,7 @@ groupedTable
                 </td>
                     <td><p class="first">Write the records to a Kafka topic and create a new stream/table from that topic.
                         Essentially a shorthand for <code class="docutils literal"><span class="pre">KStream#to()</span></code> followed by <code class="docutils literal"><span class="pre">StreamsBuilder#stream()</span></code>, same for tables.
-                        (<a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#through(java.lang.String)">KStream details</a>)</p>
+                        (<a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/kstream/KStream.html#through(java.lang.String)">KStream details</a>)</p>
                         <p>When to provide SerDes explicitly:</p>
                         <ul class="simple">
                             <li>If you do not specify SerDes explicitly, the default SerDes from the
diff --git a/21/streams/developer-guide/interactive-queries.html b/21/streams/developer-guide/interactive-queries.html
index 8d6177a..8d8143f 100644
--- a/21/streams/developer-guide/interactive-queries.html
+++ b/21/streams/developer-guide/interactive-queries.html
@@ -371,7 +371,7 @@ interactive queries</span></p>
                 <p>To enable remote state store discovery in a distributed Kafka Streams application, you must set the <a class="reference internal" href="config-streams.html#streams-developer-guide-required-configs"><span class="std std-ref">configuration property</span></a> in the config properties.
                     The <code class="docutils literal"><span class="pre">application.server</span></code> property defines a unique <code class="docutils literal"><span class="pre">host:port</span></code> pair that points to the RPC endpoint of the respective instance of a Kafka Streams application.
                     The value of this configuration property will vary across the instances of your application.
-                    When this property is set, Kafka Streams will keep track of the RPC endpoint information for every instance of an application, its state stores, and assigned stream partitions through instances of <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html">StreamsMetadata</a>.</p>
+                    When this property is set, Kafka Streams will keep track of the RPC endpoint information for every instance of an application, its state stores, and assigned stream partitions through instances of <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html">StreamsMetadata</a>.</p>
                 <div class="admonition tip">
                     <p><b>Tip</b></p>
                     <p class="last">Consider leveraging the exposed RPC endpoints of your application for further functionality, such as
@@ -416,7 +416,7 @@ interactive queries</span></p>
             </div>
             <div class="section" id="discovering-and-accessing-application-instances-and-their-local-state-stores">
                 <span id="streams-developer-guide-interactive-queries-discover-app-instances-and-stores"></span><h3><a class="toc-backref" href="#id10">Discovering and accessing application instances and their local state stores</a><a class="headerlink" href="#discovering-and-accessing-application-instances-and-their-local-state-stores" title="Permalink to this headline"></a></h3>
-                <p>The following methods return <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html">StreamsMetadata</a> objects, which provide meta-information about application instances such as their RPC endpoint and locally available state stores.</p>
+                <p>The following methods return <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html">StreamsMetadata</a> objects, which provide meta-information about application instances such as their RPC endpoint and locally available state stores.</p>
                 <ul class="simple">
                     <li><code class="docutils literal"><span class="pre">KafkaStreams#allMetadata()</span></code>: find all instances of this application</li>
                     <li><code class="docutils literal"><span class="pre">KafkaStreams#allMetadataForStore(String</span> <span class="pre">storeName)</span></code>: find those applications instances that manage local instances of the state store &#8220;storeName&#8221;</li>
@@ -425,7 +425,7 @@ interactive queries</span></p>
                 </ul>
                 <div class="admonition attention">
                     <p class="first admonition-title">Attention</p>
-                    <p class="last">If <code class="docutils literal"><span class="pre">application.server</span></code> is not configured for an application instance, then the above methods will not find any <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html">StreamsMetadata</a> for it.</p>
+                    <p class="last">If <code class="docutils literal"><span class="pre">application.server</span></code> is not configured for an application instance, then the above methods will not find any <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html">StreamsMetadata</a> for it.</p>
                 </div>
                 <p>For example, we can now find the <code class="docutils literal"><span class="pre">StreamsMetadata</span></code> for the state store named &#8220;word-count&#8221; that we defined in the
                     code example shown in the previous section:</p>
diff --git a/21/streams/developer-guide/processor-api.html b/21/streams/developer-guide/processor-api.html
index 1e7d673..119c85a 100644
--- a/21/streams/developer-guide/processor-api.html
+++ b/21/streams/developer-guide/processor-api.html
@@ -66,7 +66,7 @@
                     You can combine the convenience of the DSL with the power and flexibility of the Processor API as described in the
                     section <a class="reference internal" href="dsl-api.html#streams-developer-guide-dsl-process"><span class="std std-ref">Applying processors and transformers (Processor API integration)</span></a>.</p>
             </div>
-            <p>For a complete list of available API functionality, see the <a href="../../../{{version}}/javadoc/org/apache/kafka/streams/package-summary.html">Streams</a> API docs.</p>
+            <p>For a complete list of available API functionality, see the <a href="/{{version}}/javadoc/org/apache/kafka/streams/package-summary.html">Streams</a> API docs.</p>
         </div>
         <div class="section" id="defining-a-stream-processor">
             <span id="streams-developer-guide-stream-processor"></span><h2><a class="toc-backref" href="#id2">Defining a Stream Processor</a><a class="headerlink" href="#defining-a-stream-processor" title="Permalink to this headline"></a></h2>
@@ -227,7 +227,7 @@
                                 space.</li>
                             <li>RocksDB settings can be fine-tuned, see
                                 <a class="reference internal" href="config-streams.html#streams-developer-guide-rocksdb-config"><span class="std std-ref">RocksDB configuration</span></a>.</li>
-                            <li>Available <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/state/Stores.PersistentKeyValueFactory.html">store variants</a>:
+                            <li>Available <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/state/Stores.PersistentKeyValueFactory.html">store variants</a>:
                                 time window key-value store, session window key-value store.</li>
                         </ul>
                             <div class="highlight-java"><div class="highlight"><pre><span></span><span class="c1">// Creating a persistent key-value store:</span>
@@ -349,7 +349,7 @@
                     as <code class="docutils literal"><span class="pre">KeyValueStore</span></code>.</p>
                 <p>Note that your customized <code class="docutils literal"><span class="pre">org.apache.kafka.streams.processor.StateStore</span></code> implementation also needs to provide the logic on how to restore the state
                     via the <code class="docutils literal"><span class="pre">org.apache.kafka.streams.processor.StateRestoreCallback</span></code> or <code class="docutils literal"><span class="pre">org.apache.kafka.streams.processor.BatchingStateRestoreCallback</span></code> interface.
-                    Details on how to instantiate these interfaces can be found in the <a class="reference external" href="../../../{{version}}/javadoc/org/apache/kafka/streams/processor/StateStore.html">javadocs</a>.</p>
+                    Details on how to instantiate these interfaces can be found in the <a class="reference external" href="/{{version}}/javadoc/org/apache/kafka/streams/processor/StateStore.html">javadocs</a>.</p>
                 <p>You also need to provide a &#8220;builder&#8221; for the store by implementing the
                     <code class="docutils literal"><span class="pre">org.apache.kafka.streams.state.StoreBuilder</span></code> interface, which Kafka Streams uses to create instances of
                     your store.</p>


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