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Posted to commits@kafka.apache.org by gu...@apache.org on 2018/05/16 20:23:24 UTC
[kafka] branch trunk updated: MINOR: fix broken links in streams
doc (#5025)
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 d4204e8 MINOR: fix broken links in streams doc (#5025)
d4204e8 is described below
commit d4204e8b1456c46d4a343e219855cbe1ea20aa4a
Author: Guozhang Wang <wa...@gmail.com>
AuthorDate: Wed May 16 13:23:20 2018 -0700
MINOR: fix broken links in streams doc (#5025)
Reviewers: Guozhang Wang <wa...@gmail.com>
---
docs/streams/developer-guide/config-streams.html | 4 ++--
docs/streams/developer-guide/dsl-api.html | 8 ++++----
docs/streams/developer-guide/interactive-queries.html | 2 +-
docs/streams/developer-guide/running-app.html | 6 +++---
docs/streams/developer-guide/write-streams.html | 2 +-
5 files changed, 11 insertions(+), 11 deletions(-)
diff --git a/docs/streams/developer-guide/config-streams.html b/docs/streams/developer-guide/config-streams.html
index e3cae22..a03b53d 100644
--- a/docs/streams/developer-guide/config-streams.html
+++ b/docs/streams/developer-guide/config-streams.html
@@ -373,13 +373,13 @@
Standby replicas are used to minimize the latency of task failover. A task that was previously running on a failed instance is
preferred to restart on an instance that has standby replicas so that the local state store restoration process from its
changelog can be minimized. Details about how Kafka Streams makes use of the standby replicas to minimize the cost of
- resuming tasks on failover can be found in the <a class="reference internal" href="../architecture.html#streams-architecture-state"><span class="std std-ref">State</span></a> section.</div></blockquote>
+ resuming tasks on failover can be found in the <a class="reference internal" href="../architecture.html#streams_architecture_state"><span class="std std-ref">State</span></a> section.</div></blockquote>
</div>
<div class="section" id="num-stream-threads">
<h4><a class="toc-backref" href="#id11">num.stream.threads</a><a class="headerlink" href="#num-stream-threads" title="Permalink to this headline"></a></h4>
<blockquote>
<div>This specifies the number of stream threads in an instance of the Kafka Streams application. The stream processing code runs in these thread.
- For more information about Kafka Streams threading model, see <a class="reference internal" href="../architecture.html#streams-architecture-threads"><span class="std std-ref">Threading Model</span></a>.</div></blockquote>
+ For more information about Kafka Streams threading model, see <a class="reference internal" href="../architecture.html#streams_architecture_threads"><span class="std std-ref">Threading Model</span></a>.</div></blockquote>
</div>
<div class="section" id="partition-grouper">
<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>
diff --git a/docs/streams/developer-guide/dsl-api.html b/docs/streams/developer-guide/dsl-api.html
index d1e527e..3895522 100644
--- a/docs/streams/developer-guide/dsl-api.html
+++ b/docs/streams/developer-guide/dsl-api.html
@@ -165,7 +165,7 @@
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>
<p>You must provide a name for the table (more precisely, for the internal
- <a class="reference internal" href="../architecture.html#streams-architecture-state"><span class="std std-ref">state store</span></a> that backs the table). This is required for
+ <a class="reference internal" href="../architecture.html#streams_architecture_state"><span class="std std-ref">state store</span></a> that backs the table). This is required for
supporting <a class="reference internal" href="interactive-queries.html#streams-developer-guide-interactive-queries"><span class="std std-ref">interactive queries</span></a> against the table. When a
name is not provided the table will not queryable and an internal name will be provided for the state store.</p>
<p>If you do not specify SerDes explicitly, the default SerDes from the
@@ -189,7 +189,7 @@
<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
- <a class="reference internal" href="../architecture.html#streams-architecture-state"><span class="std std-ref">state store</span></a> that backs the table). This is required for
+ <a class="reference internal" href="../architecture.html#streams_architecture_state"><span class="std std-ref">state store</span></a> that backs the table). This is required for
supporting <a class="reference internal" href="interactive-queries.html#streams-developer-guide-interactive-queries"><span class="std std-ref">interactive queries</span></a> against the table. When a
name is not provided the table will not queryable and an internal name will be provided for the state store.</p>
<div class="highlight-java"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">org.apache.kafka.common.serialization.Serdes</span><span class="o">;</span>
@@ -690,12 +690,12 @@
</div>
<div class="section" id="stateful-transformations">
<span id="streams-developer-guide-dsl-transformations-stateful"></span><h3><a class="toc-backref" href="#id11">Stateful transformations</a><a class="headerlink" href="#stateful-transformations" title="Permalink to this headline"></a></h3>
- <p id="streams-developer-guide-dsl-transformations-stateful-overview">Stateful transformations depend on state for processing inputs and producing outputs and require a <a class="reference internal" href="../architecture.html#streams-architecture-state"><span class="std std-ref">state store</span></a> associated with the stream processor. For example, in aggregating operations, a windowing state store is used to collect the latest aggregation results per
+ <p id="streams-developer-guide-dsl-transformations-stateful-overview">Stateful transformations depend on state for processing inputs and producing outputs and require a <a class="reference internal" href="../architecture.html#streams_architecture_state"><span class="std std-ref">state store</span></a> associated with the stream processor. For example, in aggregating operations, a windowing state store is used to collect the latest aggregation results per
window. In join operations, a windowing state store is used to collect all of the records received so far within the
defined window boundary.</p>
<p>Note, that state stores are fault-tolerant.
In case of failure, Kafka Streams guarantees to fully restore all state stores prior to resuming the processing.
- See <a class="reference internal" href="../architecture.html#streams-architecture-fault-tolerance"><span class="std std-ref">Fault Tolerance</span></a> for further information.</p>
+ See <a class="reference internal" href="../architecture.html#streams_architecture_recovery"><span class="std std-ref">Fault Tolerance</span></a> for further information.</p>
<p>Available stateful transformations in the DSL include:</p>
<ul class="simple">
<li><a class="reference internal" href="#streams-developer-guide-dsl-aggregating"><span class="std std-ref">Aggregating</span></a></li>
diff --git a/docs/streams/developer-guide/interactive-queries.html b/docs/streams/developer-guide/interactive-queries.html
index 4675d8a..9b64ddb 100644
--- a/docs/streams/developer-guide/interactive-queries.html
+++ b/docs/streams/developer-guide/interactive-queries.html
@@ -52,7 +52,7 @@
<li><a class="reference internal" href="#demo-applications" id="id11">Demo applications</a></li>
</ul>
</div>
- <p>The full state of your application is typically <a class="reference internal" href="../architecture.html#streams-architecture-state"><span class="std std-ref">split across many distributed instances of your application</span></a>, and across many state stores that are managed locally by these application instances.</p>
+ <p>The full state of your application is typically <a class="reference internal" href="../architecture.html#streams_architecture_state"><span class="std std-ref">split across many distributed instances of your application</span></a>, and across many state stores that are managed locally by these application instances.</p>
<div class="figure align-center">
<img class="centered" src="/{{version}}/images/streams-interactive-queries-03.png">
</div>
diff --git a/docs/streams/developer-guide/running-app.html b/docs/streams/developer-guide/running-app.html
index bd1a77e..f83210d 100644
--- a/docs/streams/developer-guide/running-app.html
+++ b/docs/streams/developer-guide/running-app.html
@@ -77,7 +77,7 @@ $ java -cp path-to-app-fatjar.jar com.example.MyStreamsApp
<a class="reference internal" href="../code-examples.html#streams-code-examples"><span class="std std-ref">Streams code examples</span></a>.</p>
<p>When you start your application you are launching a Kafka Streams instance of your application. You can run multiple
instances of your application. A common scenario is that there are multiple instances of your application running in
- parallel. For more information, see <a class="reference internal" href="../architecture.html#streams-architecture-parallelism-model"><span class="std std-ref">Parallelism Model</span></a>.</p>
+ parallel. For more information, see <a class="reference internal" href="../architecture.html#streams_architecture_tasks"><span class="std std-ref">Parallelism Model</span></a>.</p>
<p>When the application instance starts running, the defined processor topology will be initialized as one or more stream tasks.
If the processor topology defines any state stores, these are also constructed during the initialization period. For
more information, see the <a class="reference internal" href="#streams-developer-guide-execution-scaling-state-restoration"><span class="std std-ref">State restoration during workload rebalance</span></a> section).</p>
@@ -87,7 +87,7 @@ $ java -cp path-to-app-fatjar.jar com.example.MyStreamsApp
<p>Kafka Streams makes your stream processing applications elastic and scalable. You can add and remove processing capacity
dynamically during application runtime without any downtime or data loss. This makes your applications
resilient in the face of failures and for allows you to perform maintenance as needed (e.g. rolling upgrades).</p>
- <p>For more information about this elasticity, see the <a class="reference internal" href="../architecture.html#streams-architecture-parallelism-model"><span class="std std-ref">Parallelism Model</span></a> section. Kafka Streams
+ <p>For more information about this elasticity, see the <a class="reference internal" href="../architecture.html#streams_architecture_tasks"><span class="std std-ref">Parallelism Model</span></a> section. Kafka Streams
leverages the Kafka group management functionality, which is built right into the <a class="reference external" href="https://cwiki.apache.org/confluence/display/KAFKA/A+Guide+To+The+Kafka+Protocol">Kafka wire protocol</a>. It is the foundation that enables the
elasticity of Kafka Streams applications: members of a group coordinate and collaborate jointly on the consumption and
processing of data in Kafka. Additionally, Kafka Streams provides stateful processing and allows for fault-tolerant
@@ -128,7 +128,7 @@ $ java -cp path-to-app-fatjar.jar com.example.MyStreamsApp
<li>If no local state store exists, the changelog is replayed from the earliest to the current offset. This reconstructs the local state store to the most recent snapshot.</li>
<li>If a local state store exists, the changelog is replayed from the previously checkpointed offset. The changes are applied and the state is restored to the most recent snapshot. This method takes less time because it is applying a smaller portion of the changelog.</li>
</ul>
- <p>For more information, see <a class="reference internal" href="config-streams.html#streams-developer-guide-standby-replicas"><span class="std std-ref">Standby Replicas</span></a>.</p>
+ <p>For more information, see <a class="reference internal" href="config-streams.html#num-standby-replicas"><span class="std std-ref">Standby Replicas</span></a>.</p>
</div>
<div class="section" id="determining-how-many-application-instances-to-run">
<h3><a class="toc-backref" href="#id8">Determining how many application instances to run</a><a class="headerlink" href="#determining-how-many-application-instances-to-run" title="Permalink to this headline"></a></h3>
diff --git a/docs/streams/developer-guide/write-streams.html b/docs/streams/developer-guide/write-streams.html
index 23ca764..0007b3e 100644
--- a/docs/streams/developer-guide/write-streams.html
+++ b/docs/streams/developer-guide/write-streams.html
@@ -155,7 +155,7 @@
</div>
<p>If there are other instances of this stream processing application running elsewhere (e.g., on another machine), Kafka
Streams transparently re-assigns tasks from the existing instances to the new instance that you just started.
- For more information, see <a class="reference internal" href="../architecture.html#streams-architecture-tasks"><span class="std std-ref">Stream Partitions and Tasks</span></a> and <a class="reference internal" href="../architecture.html#streams-architecture-threads"><span class="std std-ref">Threading Model</span></a>.</p>
+ For more information, see <a class="reference internal" href="../architecture.html#streams_architecture_tasks"><span class="std std-ref">Stream Partitions and Tasks</span></a> and <a class="reference internal" href="../architecture.html#streams-architecture-threads"><span class="std std-ref">Threading Model</span></a>.</p>
<p>To catch any unexpected exceptions, you can set an <code class="docutils literal"><span class="pre">java.lang.Thread.UncaughtExceptionHandler</span></code> before you start the
application. This handler is called whenever a stream thread is terminated by an unexpected exception:</p>
<div class="highlight-java"><div class="highlight"><pre><span></span><span class="c1">// Java 8+, using lambda expressions</span>
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