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Posted to commits@kafka.apache.org by gu...@apache.org on 2018/01/29 18:10:24 UTC

[kafka] branch trunk updated: MINOR: Fix some streams web doc nits (#4411)

This is an automated email from the ASF dual-hosted git repository.

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


The following commit(s) were added to refs/heads/trunk by this push:
     new 6ea53d2  MINOR: Fix some streams web doc nits (#4411)
6ea53d2 is described below

commit 6ea53d22e25e948b26c8f2c436f242edb0748df2
Author: Joel Hamill <11...@users.noreply.github.com>
AuthorDate: Mon Jan 29 10:08:48 2018 -0800

    MINOR: Fix some streams web doc nits (#4411)
    
    Reviewers: Derrick Or <de...@gmail.com>, Guozhang Wang <wa...@gmail.com>
---
 docs/streams/developer-guide/dsl-api.html             | 17 ++++++++---------
 docs/streams/developer-guide/interactive-queries.html |  4 ++--
 docs/streams/developer-guide/processor-api.html       |  2 +-
 3 files changed, 11 insertions(+), 12 deletions(-)

diff --git a/docs/streams/developer-guide/dsl-api.html b/docs/streams/developer-guide/dsl-api.html
index 399d3fc..ba03e2e 100644
--- a/docs/streams/developer-guide/dsl-api.html
+++ b/docs/streams/developer-guide/dsl-api.html
@@ -418,7 +418,7 @@
                                 <strong>must do</strong> if the key and/or value types of the resulting <code class="docutils literal"><span class="pre">KGroupedStream</span></code> do not match the configured default
                                 SerDes.</p>
                             <div class="admonition note">
-                                <p class="first admonition-title">Note</p>
+                                <p><b>Note</b></p>
                                 <p class="last"><strong>Grouping vs. Windowing:</strong>
                                     A related operation is <a class="reference internal" href="#streams-developer-guide-dsl-windowing"><span class="std std-ref">windowing</span></a>, which lets you control how to
                                     &#8220;sub-group&#8221; the grouped records <em>of the same key</em> into so-called <em>windows</em> for stateful operations such as
@@ -464,7 +464,7 @@
                                 <strong>do</strong> if the key and/or value types of the resulting <code class="docutils literal"><span class="pre">KGroupedStream</span></code> or <code class="docutils literal"><span class="pre">KGroupedTable</span></code> do not match the
                                 configured default SerDes.</p>
                             <div class="admonition note">
-                                <p class="first admonition-title">Note</p>
+                                <p><b>Note</b></p>
                                 <p class="last"><strong>Grouping vs. Windowing:</strong>
                                     A related operation is <a class="reference internal" href="#streams-developer-guide-dsl-windowing"><span class="std std-ref">windowing</span></a>, which lets you control how to
                                     &#8220;sub-group&#8221; the grouped records <em>of the same key</em> into so-called <em>windows</em> for stateful operations such as
@@ -1204,7 +1204,7 @@
 </pre></div>
                     </div>
                     <div class="admonition note">
-                        <p class="first admonition-title">Note</p>
+                        <p><b>Note</b></p>
                         <p class="last"><strong>Impact of record caches</strong>:
                             For illustration purposes, the column &#8220;KTable <code class="docutils literal"><span class="pre">aggregated</span></code>&#8221; below shows the table&#8217;s state changes over time in a
                             very granular way.  In practice, you would observe state changes in such a granular way only when
@@ -1334,7 +1334,7 @@
 </pre></div>
                     </div>
                     <div class="admonition note">
-                        <p class="first admonition-title">Note</p>
+                        <p><b>Note</b></p>
                         <p class="last"><strong>Impact of record caches</strong>:
                             For illustration purposes, the column &#8220;KTable <code class="docutils literal"><span class="pre">aggregated</span></code>&#8221; below shows the table&#8217;s state changes over time in a
                             very granular way.  In practice, you would observe state changes in such a granular way only when
@@ -1531,7 +1531,6 @@
                             <td>Not Supported</td>
                             <td>Not Supported</td>
                             <td>Not Supported</td>
-                            <td>N/A</td>
                         </tr>
                         </tbody>
                     </table>
@@ -1569,7 +1568,7 @@
                             each <code class="docutils literal"><span class="pre">KafkaStreams</span></code> instance, i.e. each instance has a full copy of the changelog stream.  Further, a
                             <code class="docutils literal"><span class="pre">KeyValueMapper</span></code> allows for non-key based joins from the <code class="docutils literal"><span class="pre">KStream</span></code> to the <code class="docutils literal"><span class="pre">GlobalKTable</span></code>.</p>
                         <div class="admonition note">
-                            <p class="first admonition-title">Note</p>
+                            <p><b>Note</b></p>
                             <p class="last"><strong>Kafka Streams partly verifies the co-partitioning requirement:</strong>
                                 During the partition assignment step, i.e. at runtime, Kafka Streams verifies whether the number of partitions for
                                 both sides of a join are the same.  If they are not, a <code class="docutils literal"><span class="pre">TopologyBuilderException</span></code> (runtime exception) is being
@@ -2691,7 +2690,7 @@
                         <a class="reference internal" href="#streams-developer-guide-dsl-aggregating"><span class="std std-ref">aggregations</span></a> or <a class="reference internal" href="#streams-developer-guide-dsl-joins"><span class="std std-ref">joins</span></a> into
                         so-called windows.  Windows are tracked per record key.</p>
                     <div class="admonition note">
-                        <p class="first admonition-title">Note</p>
+                        <p><b>Note</b></p>
                         <p class="last">A related operation is <a class="reference internal" href="#streams-developer-guide-dsl-transformations-stateless"><span class="std std-ref">grouping</span></a>, which groups all
                             records that have the same key to ensure that data is properly partitioned (&#8220;keyed&#8221;) for subsequent operations.
                             Once grouped, windowing allows you to further sub-group the records of a key.</p>
@@ -2776,7 +2775,7 @@ become t=300,000).</span></p>
                             hopping window with a size 5 minutes and an advance interval of 1 minute.  Since hopping windows can overlap &#8211; and in
                             general they do &#8211; a data record may belong to more than one such windows.</p>
                         <div class="admonition note">
-                            <p class="first admonition-title">Note</p>
+                            <p><b>Note</b></p>
                             <p class="last"><strong>Hopping windows vs. sliding windows:</strong>
                                 Hopping windows are sometimes called &#8220;sliding windows&#8221; in other stream processing tools.  Kafka Streams follows the
                                 terminology in academic literature, where the semantics of sliding windows are different to those of hopping windows.</p>
@@ -3146,7 +3145,7 @@ t=5 (blue), which lead to a merge of sessions and an extension of a session, res
                 </tbody>
             </table>
             <div class="admonition note">
-                <p class="first admonition-title">Note</p>
+                <p><b>Note</b></p>
                 <p class="last"><strong>When you want to write to systems other than Kafka:</strong>
                     Besides writing the data back to Kafka, you can also apply a
                     <a class="reference internal" href="#streams-developer-guide-dsl-process"><span class="std std-ref">custom processor</span></a> as a stream sink at the end of the processing to, for
diff --git a/docs/streams/developer-guide/interactive-queries.html b/docs/streams/developer-guide/interactive-queries.html
index b55655e..0a37d56 100644
--- a/docs/streams/developer-guide/interactive-queries.html
+++ b/docs/streams/developer-guide/interactive-queries.html
@@ -120,7 +120,7 @@
             </ul>
             <p>You can also <a class="reference internal" href="#streams-developer-guide-interactive-queries-custom-stores"><span class="std std-ref">implement your own QueryableStoreType</span></a> as described in section <a class="reference internal" href="#streams-developer-guide-interactive-queries-custom-stores"><span class="std std-ref">Querying local custom state stores</span></a>.</p>
             <div class="admonition note">
-                <p class="first admonition-title">Note</p>
+                <p><b>Note</b></p>
                 <p class="last">Kafka Streams materializes one state store per stream partition. This means your application will potentially manage
                     many underlying state stores.  The API enables you to query all of the underlying stores without having to know which
                     partition the data is in.</p>
@@ -227,7 +227,7 @@
             <div class="section" id="querying-local-custom-state-stores">
                 <span id="streams-developer-guide-interactive-queries-custom-stores"></span><h3><a class="toc-backref" href="#id6">Querying local custom state stores</a><a class="headerlink" href="#querying-local-custom-state-stores" title="Permalink to this headline"></a></h3>
                 <div class="admonition note">
-                    <p class="first admonition-title">Note</p>
+                    <p><b>Note</b></p>
                     <p class="last">Only the <a class="reference internal" href="processor-api.html#streams-developer-guide-processor-api"><span class="std std-ref">Processor API</span></a> supports custom state stores.</p>
                 </div>
                 <p>Before querying the custom state stores you must implement these interfaces:</p>
diff --git a/docs/streams/developer-guide/processor-api.html b/docs/streams/developer-guide/processor-api.html
index 5ed569a..b92e85b 100644
--- a/docs/streams/developer-guide/processor-api.html
+++ b/docs/streams/developer-guide/processor-api.html
@@ -148,7 +148,7 @@
 </pre></div>
             </div>
             <div class="admonition note">
-                <p class="first admonition-title">Note</p>
+                <p><b>Note</b></p>
                 <p class="last"><strong>Stateful processing with state stores:</strong>
                     The <code class="docutils literal"><span class="pre">WordCountProcessor</span></code> defined above can access the currently received record in its <code class="docutils literal"><span class="pre">process()</span></code> method, and it can
                     leverage <a class="reference internal" href="#streams-developer-guide-state-store"><span class="std std-ref">state stores</span></a> to maintain processing states to, for example, remember recently

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