This is an automated email from the ASF dual-hosted git repository.
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in repository https://gitbox.apache.org/repos/asf/flink-web.git
The following commit(s) were added to refs/heads/asf-site by this push:
new c1ebeef [FLINK-11563] Translate "Getting Help" page into Chinese
c1ebeef is described below
commit c1ebeef585d15cc583d6340dce6df3d5d3393e44
Author: SunnyD <[email protected]>
AuthorDate: Wed Feb 27 14:08:04 2019 +0800
[FLINK-11563] Translate "Getting Help" page into Chinese
This closes #168
---
content/gettinghelp.html | 2 +-
content/zh/gettinghelp.html | 155 ++++++++++++++++++++------------------------
gettinghelp.md | 2 +-
gettinghelp.zh.md | 136 +++++++++++++++++---------------------
4 files changed, 130 insertions(+), 165 deletions(-)
diff --git a/content/gettinghelp.html b/content/gettinghelp.html
index ef8c1f6..7d567f4 100644
--- a/content/gettinghelp.html
+++ b/content/gettinghelp.html
@@ -221,7 +221,7 @@ Because of that, all functions that you pass to the API
must be serializable, as
<a
href="http://docs.oracle.com/javase/8/docs/api/java/io/Serializable.html";>java.io.Serializable</a>.</p>
<p>If your function is an anonymous inner class, consider the following:
- - make the function a standalone class, or a static inner class
+ - make the function a standalone class, or a static inner class.
- use a Java 8 lambda function.</p>
<p>Is your function is already a static class, check the fields that you
assign when you create
diff --git a/content/zh/gettinghelp.html b/content/zh/gettinghelp.html
index 25c1bb3..16420fe 100644
--- a/content/zh/gettinghelp.html
+++ b/content/zh/gettinghelp.html
@@ -152,157 +152,140 @@
<div class="page-toc">
<ul id="markdown-toc">
- <li><a href="#having-a-question" id="markdown-toc-having-a-question">Having
a Question?</a> <ul>
- <li><a href="#user-mailing-list"
id="markdown-toc-user-mailing-list">User Mailing List</a></li>
+ <li><a href="#section" id="markdown-toc-section">有问题吗?</a> <ul>
+ <li><a href="#section-1" id="markdown-toc-section-1">用户邮件列表</a></li>
<li><a href="#stack-overflow" id="markdown-toc-stack-overflow">Stack
Overflow</a></li>
</ul>
</li>
- <li><a href="#found-a-bug" id="markdown-toc-found-a-bug">Found a
Bug?</a></li>
- <li><a href="#got-an-error-message"
id="markdown-toc-got-an-error-message">Got an Error Message?</a> <ul>
- <li><a href="#i-have-a-notserializableexception"
id="markdown-toc-i-have-a-notserializableexception">I have a
NotSerializableException.</a></li>
- <li><a
href="#using-the-scala-api-i-get-an-error-about-implicit-values-and-evidence-parameters"
id="markdown-toc-using-the-scala-api-i-get-an-error-about-implicit-values-and-evidence-parameters">Using
the Scala API, I get an error about implicit values and evidence
parameters.</a></li>
- <li><a href="#i-see-a-classcastexception-x-cannot-be-cast-to-x"
id="markdown-toc-i-see-a-classcastexception-x-cannot-be-cast-to-x">I see a
ClassCastException: X cannot be cast to X.</a></li>
- <li><a href="#i-have-an-abstractmethoderror-or-nosuchfielderror"
id="markdown-toc-i-have-an-abstractmethoderror-or-nosuchfielderror">I have an
AbstractMethodError or NoSuchFieldError.</a></li>
- <li><a
href="#my-datastream-application-produces-no-output-even-though-events-are-going-in"
id="markdown-toc-my-datastream-application-produces-no-output-even-though-events-are-going-in">My
DataStream application produces no output, even though events are going
in.</a></li>
- <li><a
href="#i-see-an-exception-reporting-insufficient-number-of-network-buffers"
id="markdown-toc-i-see-an-exception-reporting-insufficient-number-of-network-buffers">I
see an exception reporting “Insufficient number of network buffers”.</a></li>
- <li><a
href="#my-job-fails-with-various-exceptions-from-the-hdfshadoop-code-what-can-i-do"
id="markdown-toc-my-job-fails-with-various-exceptions-from-the-hdfshadoop-code-what-can-i-do">My
job fails with various exceptions from the HDFS/Hadoop code. What can I
do?</a></li>
+ <li><a href="#bug" id="markdown-toc-bug">发现 Bug?</a></li>
+ <li><a href="#section-2" id="markdown-toc-section-2">收到错误信息?</a> <ul>
+ <li><a href="#notserializableexception-"
id="markdown-toc-notserializableexception-">我有一个 NotSerializableException
异常。</a></li>
+ <li><a href="#scala-api" id="markdown-toc-scala-api">使用 Scala
API，我收到有关隐式值和证据参数的错误。</a></li>
+ <li><a href="#classcastexception-x-cannot-be-cast-to-x"
id="markdown-toc-classcastexception-x-cannot-be-cast-to-x">我看到一个
ClassCastException: X cannot be cast to X.</a></li>
+ <li><a href="#abstractmethoderror--nosuchfielderror-"
id="markdown-toc-abstractmethoderror--nosuchfielderror-">我有一个
AbstractMethodError 或 NoSuchFieldError 错误。</a></li>
+ <li><a href="#datastream-" id="markdown-toc-datastream-">尽管事件正在持续发送，我的
DataStream 程序还是没有输出。</a></li>
+ <li><a href="#insufficient-number-of-network-buffers-"
id="markdown-toc-insufficient-number-of-network-buffers-">我看到了一个 “Insufficient
number of network buffers” 的异常报告。</a></li>
+ <li><a href="#job--hdfshadoop-" id="markdown-toc-job--hdfshadoop-">我的
Job 因为 HDFS/Hadoop 代码的各种异常失败了，我该怎么办？</a></li>
</ul>
</li>
</ul>
</div>
-<h2 id="having-a-question">Having a Question?</h2>
+<h2 id="section">有问题吗?</h2>
-<p>The Apache Flink community answers many user questions every day. You can
search for answers and advice in the archives or reach out to the community for
help and guidance.</p>
+<p>Apache Flink 社区每天都会回答许多用户的问题。你可以从历史存档中搜索答案和建议，也可以联系社区寻求帮助和指导。</p>
-<h3 id="user-mailing-list">User Mailing List</h3>
+<h3 id="section-1">用户邮件列表</h3>
-<p>Many Flink users, contributors, and committers are subscribed to Flink’s
user mailing list. The user mailing list is a very good place to ask for
help.</p>
+<p>许多 Flink 用户、贡献者和提交者都订阅了 Flink 的用户邮件列表。用户邮件列表是一个寻求帮助的好地方。</p>
-<p>Before posting to the mailing list, you can search the mailing list
archives for email threads that discuss issues related to yours on the
following websites.</p>
+<p>在发送邮件到邮件列表之前，你可以搜索以下网站的邮件列表存档，从中找到你关注问题的相关讨论。</p>
<ul>
- <li><a
href="https://lists.apache.org/[email protected]";>Apache Pony
Mail Archive</a></li>
- <li><a
href="http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/";>Nabble
Archive</a></li>
+ <li><a
href="https://lists.apache.org/[email protected]";>Apache Pony
邮件存档</a></li>
+ <li><a
href="http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/";>Nabble
存档</a></li>
</ul>
-<p>If you’d like to post to the mailing list, you need to</p>
+<p>如果你想发送到邮件列表，你需要：</p>
<ol>
- <li>subscribe to the mailing list by sending an email to
<code>[email protected]</code>,</li>
- <li>confirm the subscription by replying to the confirmation email, and</li>
- <li>send your email to <code>[email protected]</code>.</li>
+ <li>发送电子邮件至 <code>[email protected]</code> 来订阅邮件列表</li>
+ <li>通过回复确认邮件来确认订阅</li>
+ <li>发送你的电子邮件到 <code>[email protected]</code></li>
</ol>
-<p>Please note that you won’t receive a respose to your mail if you are not
subscribed.</p>
+<p>请注意，如果你没有订阅邮件列表，你将不会收到邮件的回复。</p>
<h3 id="stack-overflow">Stack Overflow</h3>
-<p>Many members of the Flink community are active on <a
href="https://stackoverflow.com";>Stack Overflow</a>. You can search for
questions and answers or post your questions using the <a
href="https://stackoverflow.com/questions/tagged/apache-flink";>[apache-flink]</a>
tag.</p>
+<p>Flink 社区的许多成员都活跃在 <a href="https://stackoverflow.com";>Stack
Overflow</a>。你可以在这里搜索问题和答案，或者使用 <a
href="https://stackoverflow.com/questions/tagged/apache-flink";>[apache-flink]</a>
标签来发布你的问题。</p>
-<h2 id="found-a-bug">Found a Bug?</h2>
+<h2 id="bug">发现 Bug?</h2>
-<p>If you observe an unexpected behavior that might be caused by a bug, you
can search for reported bugs or file a bug report in <a
href="https://issues.apache.org/jira/issues/?jql=project %3D FLINK">Flink’s
JIRA</a>.</p>
+<p>如果你发现一个意外行为可能是由 Bug 导致的，你可以在 <a
href="https://issues.apache.org/jira/issues/?jql=project %3D FLINK">Flink’s
JIRA</a> 中搜索已经上报的 Bug 或者发布该 Bug。</p>
-<p>If you are unsure whether the unexpected behavior happend due to a bug or
not, please post a question to the <a href="#user-mailing-list">user mailing
list</a>.</p>
+<p>如果你不确定意外行为的发生是否由 Bug 引起的，请发送问题到 <a href="#user-mailing-list">用户邮件列表</a>。</p>
-<h2 id="got-an-error-message">Got an Error Message?</h2>
+<h2 id="section-2">收到错误信息?</h2>
-<p>Identifying the cause for an error message can be challenging. In the
following, we list the most common error messages and explain how to handle
them.</p>
+<p>找到导致错误的原因通常是比较困难的。在下文中，我们列出了最常见的错误消息并解释了如何处理它们。</p>
-<h3 id="i-have-a-notserializableexception">I have a
NotSerializableException.</h3>
+<h3 id="notserializableexception-">我有一个 NotSerializableException 异常。</h3>
-<p>Flink uses Java serialization to distribute copies of the application logic
(the functions and operations you implement,
-as well as the program configuration, etc.) to the parallel worker processes.
-Because of that, all functions that you pass to the API must be serializable,
as defined by
-<a
href="http://docs.oracle.com/javase/8/docs/api/java/io/Serializable.html";>java.io.Serializable</a>.</p>
+<p>Flink 使用 Java 序列化来分发应用程序逻辑（你实现的函数和操作，以及程序配置等）的副本到并行的工作进程。
+因此，传递给 API 的所有函数都必须是可序列化的，见
+<a
href="http://docs.oracle.com/javase/8/docs/api/java/io/Serializable.html";>java.io.Serializable</a>
定义。</p>
-<p>If your function is an anonymous inner class, consider the following:
- - make the function a standalone class, or a static inner class
- - use a Java 8 lambda function.</p>
+<p>如果你使用的函数是匿名内部类，请考虑以下事项：
+ - 为函数构建独立的类或静态内部类。
+ - 使用 Java 8 lambda 函数。</p>
-<p>Is your function is already a static class, check the fields that you
assign when you create
-an instance of the class. One of the fields most likely holds a
non-serializable type.
- - In Java, use a <code>RichFunction</code> and initialize the problematic
fields in the <code>open()</code> method.
- - In Scala, you can often simply use “lazy val” to defer initialization
until the distributed execution happens. This may come at a minor performance
cost. You can naturally also use a <code>RichFunction</code> in Scala.</p>
+<p>如果函数已经是静态类，则在创建该类的实例时会检查该类的字段。其中很可能包含不可序列化类型的字段。
+ - 在 Java 中，使用 <code>RichFunction</code> 并且在 <code>open()</code> 方法中初始化有问题的字段。
+ - 在 Scala 中，你通常可以简单地使用 “lazy val” 声明来推迟初始化，直到分布式执行发生。这可能是一个较小的性能成本。你当然也可以在
Scala 中使用 <code>RichFunction</code>。</p>
-<h3
id="using-the-scala-api-i-get-an-error-about-implicit-values-and-evidence-parameters">Using
the Scala API, I get an error about implicit values and evidence
parameters.</h3>
+<h3 id="scala-api">使用 Scala API，我收到有关隐式值和证据参数的错误。</h3>
-<p>This error means that the implicit value for the type information could not
be provided.
-Make sure that you have an <code>import
org.apache.flink.streaming.api.scala._</code> (DataStream API) or an
-<code>import org.apache.flink.api.scala._</code> (DataSet API) statement in
your code.</p>
+<p>此错误意味着无法提供类型信息的隐式值。确保在你的代码中存在 <code>import
org.apache.flink.streaming.api.scala._</code> (DataStream API) 或
+<code>import org.apache.flink.api.scala._</code> (DataSet API) 语句。</p>
-<p>If you are using Flink operations inside functions or classes that take
-generic parameters, then a TypeInformation must be available for that
parameter.
-This can be achieved by using a context bound:</p>
+<p>如果在接受泛型参数的函数或类中使用 Flink 操作，则必须为参数提供 TypeInformation 类型参数。
+这可以通过使用上下文绑定来实现：</p>
<div class="highlight"><pre><code class="language-scala"><span
class="k">def</span> <span class="n">myFunction</span><span
class="o">[</span><span class="kt">T:</span> <span
class="kt">TypeInformation</span><span class="o">](</span><span
class="n">input</span><span class="k">:</span> <span
class="kt">DataSet</span><span class="o">[</span><span class="kt">T</span><span
class="o">])</span><span class="k">:</span> <span
class="kt">DataSet</span><span class="o">[</span><span class="kt">Seq</ [...]
<span class="n">input</span><span class="o">.</span><span
class="n">reduceGroup</span><span class="o">(</span> <span class="n">i</span>
<span class="k">=></span> <span class="n">i</span><span
class="o">.</span><span class="n">toSeq</span> <span class="o">)</span>
<span class="o">}</span></code></pre></div>
-<p>See <a
href="https://ci.apache.org/projects/flink/flink-docs-master/dev/types_serialization.html";>Type
Extraction and Serialization</a> for
-an in-depth discussion of how Flink handles types.</p>
+<p>请参阅 <a
href="https://ci.apache.org/projects/flink/flink-docs-master/dev/types_serialization.html";>类型提取和序列化</a>
深入讨论 Flink 如何处理类型。</p>
-<h3 id="i-see-a-classcastexception-x-cannot-be-cast-to-x">I see a
ClassCastException: X cannot be cast to X.</h3>
+<h3 id="classcastexception-x-cannot-be-cast-to-x">我看到一个 ClassCastException: X
cannot be cast to X.</h3>
-<p>When you see an exception in the style <code>com.foo.X</code> cannot be
cast to <code>com.foo.X</code> (or cannot be assigned to
<code>com.foo.X</code>), it means that
-multiple versions of the class <code>com.foo.X</code> have been loaded by
different class loaders, and types of that class are attempted to be assigned
to each other.</p>
+<p>当你看到 <code>com.foo.X</code> cannot be cast to <code>com.foo.X</code> ( 或者
cannot be assigned to <code>com.foo.X</code>) 样式的异常时，这意味着
<code>com.foo.X</code> 类的多个版本已经由不同的类加载器加载，并且尝试相互赋值。</p>
-<p>The reason for that can be:</p>
+<p>原因可能是:</p>
<ul>
<li>
- <p>Class duplication through <code>child-first</code> classloading. That
is an intended mechanism to allow users to use different versions of the same
-dependencies that Flink uses. However, if different copies of these classes
move between Flink’s core and the user application code, such an exception
-can occur. To verify that this is the reason, try setting
<code>classloader.resolve-order: parent-first</code> in the configuration.
-If that makes the error disappear, please write to the mailing list to check
if that may be a bug.</p>
+ <p>通过 <code>child-first</code>
的类加载方式实现类复制。这是一种预期的机制，该机制允许用户使用相同依赖的不同版本。然而，如果这些类的不同副本在 Flink
的核心代码和用户应用程序代码之间移动，则可能发生这种异常。为了验证这个原因，请尝试在配置中设置
<code>classloader.resolve-order：parent-first</code>。如果这可以使错误消失，请写信到邮件列表以检查是否可能是
Bug。</p>
</li>
<li>
- <p>Caching of classes from different execution attempts, for example by
utilities like Guava’s Interners, or Avro’s Schema cache.
-Try to not use interners, or reduce the scope of the interner/cache to make
sure a new cache is created whenever a new task
-execution is started.</p>
+ <p>从不同的执行中尝试缓存类，例如使用像 Guava 的 Interners 或 Avro 的 Schema 等通用工具进行缓存操作。尝试不使用
Interners，或减少 interner/cache 的使用范围，以确保每当新任务开始执行时都会创建新的缓存。</p>
</li>
</ul>
-<h3 id="i-have-an-abstractmethoderror-or-nosuchfielderror">I have an
AbstractMethodError or NoSuchFieldError.</h3>
+<h3 id="abstractmethoderror--nosuchfielderror-">我有一个 AbstractMethodError 或
NoSuchFieldError 错误。</h3>
-<p>Such errors typically indicate a mix-up in some dependency version. That
means a different version of a dependency (a library)
-is loaded during the execution compared to the version that code was compiled
against.</p>
+<p>此类错误通常表示混淆了某些依赖的版本。这意味着在执行期间加载了不同版本的依赖项（库），而不是编译代码的版本。</p>
-<p>From Flink 1.4.0 on, dependencies in your application JAR file may have
different versions compared to dependencies used
-by Flink’s core, or other dependencies in the classpath (for example from
Hadoop). That requires <code>child-first</code> classloading
-to be activated, which is the default.</p>
+<p>从 Flink 1.4.0 开始，在默认激活 <code>child-first</code> 类加载方式的情况下，相比 Flink core
所使用的依赖或类路径中的其他依赖（例如来自 Hadoop ）而言，应用程序 JAR 文件中的依赖更可能带有不同的版本。</p>
-<p>If you see these problems in Flink 1.4+, one of the following may be true:
- - You have a dependency version conflict within your application code. Make
sure all your dependency versions are consistent.
- - You are conflicting with a library that Flink cannot support via
<code>child-first</code> classloading. Currently these are the
- Scala standard library classes, as well as Flink’s own classes, logging
APIs, and any Hadoop core classes.</p>
+<p>如果你在 Flink 1.4 以上的版本中看到这些问题，则可能是属于以下某种情况：
+ - 你的程序代码中存在依赖项版本冲突，确保所有依赖项版本都一致。
+ - 你与一个 Flink 不能支持 <code>child-first</code> 类加载的库发生了冲突。目前会产生这种情况的有 Scala
标准库类、Flink 自己的类、日志 API 和所有的 Hadoop 核心类。</p>
-<h3
id="my-datastream-application-produces-no-output-even-though-events-are-going-in">My
DataStream application produces no output, even though events are going
in.</h3>
+<h3 id="datastream-">尽管事件正在持续发送，我的 DataStream 程序还是没有输出。</h3>
-<p>If your DataStream application uses <em>Event Time</em>, check that your
watermarks get updated. If no watermarks are produced,
-event time windows might never trigger, and the application would produce no
results.</p>
+<p>如果你的 DataStream 程序使用了 <em>事件时间</em>，那么请检查你的 Watermark 是否已经更新。如果没有产生
Watermark，
+事件时间窗口可能永远不会触发，程序将不会产生任何结果。</p>
-<p>You can check in Flink’s web UI (watermarks section) whether watermarks are
making progress.</p>
+<p>你可以在 Flink 的 Web UI（Watermark 部分）中查看 Watermark 是否正在更新。</p>
-<h3 id="i-see-an-exception-reporting-insufficient-number-of-network-buffers">I
see an exception reporting “Insufficient number of network buffers”.</h3>
+<h3 id="insufficient-number-of-network-buffers-">我看到了一个 “Insufficient number
of network buffers” 的异常报告。</h3>
-<p>If you run Flink with a very high parallelism, you may need to increase the
number of network buffers.</p>
+<p>如果你用非常高的并行度运行 Flink 程序，则可能需要增加网络缓冲区的大小。</p>
-<p>By default, Flink takes 10% of the JVM heap size for network buffers, with
a minimum of 64MB and a maximum of 1GB.
-You can adjust all these values via
<code>taskmanager.network.memory.fraction</code>,
<code>taskmanager.network.memory.min</code>, and
-<code>taskmanager.network.memory.max</code>.</p>
+<p>默认情况下，Flink 占用 JVM 堆的 10% 作为网络缓冲区的大小，最小为64MB，最大为1GB。
+你可以通过 <code>taskmanager.network.memory.fraction</code>、
<code>taskmanager.network.memory.min</code>和
+<code>taskmanager.network.memory.max</code> 参数调整这些值。</p>
-<p>Please refer to the <a
href="https://ci.apache.org/projects/flink/flink-docs-master/ops/config.html#configuring-the-network-buffers";>Configuration
Reference</a> for details.</p>
+<p>详情请参考 <a
href="https://ci.apache.org/projects/flink/flink-docs-master/ops/config.html#configuring-the-network-buffers";>配置参考</a>。</p>
-<h3
id="my-job-fails-with-various-exceptions-from-the-hdfshadoop-code-what-can-i-do">My
job fails with various exceptions from the HDFS/Hadoop code. What can I
do?</h3>
+<h3 id="job--hdfshadoop-">我的 Job 因为 HDFS/Hadoop 代码的各种异常失败了，我该怎么办？</h3>
-<p>The most common cause for that is that the Hadoop version in Flink’s
classpath is different than the
-Hadoop version of the cluster you want to connect to (HDFS / YARN).</p>
+<p>最常见的原因是 Flink 的类路径中的 Hadoop 版本与你要访问的 Hadoop 集群（HDFS / YARN）版本不同。</p>
-<p>The easiest way to fix that is to pick a Hadoop-free Flink version and
simply export the Hadoop path and
-classpath from the cluster.</p>
+<p>解决这个问题的最简单方法是选择一个不含 Hadoop 的 Flink 版本，并通过 export 的方式设置 Hadoop 路径和类路径即可。</p>
</div>
diff --git a/gettinghelp.md b/gettinghelp.md
index 3cf2303..c763b94 100644
--- a/gettinghelp.md
+++ b/gettinghelp.md
@@ -49,7 +49,7 @@ Because of that, all functions that you pass to the API must
be serializable, as
[java.io.Serializable](http://docs.oracle.com/javase/8/docs/api/java/io/Serializable.html).
If your function is an anonymous inner class, consider the following:
- - make the function a standalone class, or a static inner class
+ - make the function a standalone class, or a static inner class.
- use a Java 8 lambda function.
Is your function is already a static class, check the fields that you assign
when you create
diff --git a/gettinghelp.zh.md b/gettinghelp.zh.md
index d24fabd..81b1a24 100644
--- a/gettinghelp.zh.md
+++ b/gettinghelp.zh.md
@@ -6,66 +6,62 @@ title: "获取帮助"
{% toc %}
-## Having a Question?
+## 有问题吗?
-The Apache Flink community answers many user questions every day. You can
search for answers and advice in the archives or reach out to the community for
help and guidance.
+Apache Flink 社区每天都会回答许多用户的问题。你可以从历史存档中搜索答案和建议，也可以联系社区寻求帮助和指导。
-### User Mailing List
+### 用户邮件列表
-Many Flink users, contributors, and committers are subscribed to Flink's user
mailing list. The user mailing list is a very good place to ask for help.
+许多 Flink 用户、贡献者和提交者都订阅了 Flink 的用户邮件列表。用户邮件列表是一个寻求帮助的好地方。
-Before posting to the mailing list, you can search the mailing list archives
for email threads that discuss issues related to yours on the following
websites.
+在发送邮件到邮件列表之前，你可以搜索以下网站的邮件列表存档，从中找到你关注问题的相关讨论。
-- [Apache Pony Mail
Archive](https://lists.apache.org/[email protected])
-- [Nabble
Archive](http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/)
+- [Apache Pony 邮件存档](https://lists.apache.org/[email protected])
+- [Nabble
存档](http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/)
-If you'd like to post to the mailing list, you need to
+如果你想发送到邮件列表，你需要：
-1. subscribe to the mailing list by sending an email to
`[email protected]`,
-2. confirm the subscription by replying to the confirmation email, and
-3. send your email to `[email protected]`.
+1. 发送电子邮件至 `[email protected]` 来订阅邮件列表
+2. 通过回复确认邮件来确认订阅
+3. 发送你的电子邮件到 `[email protected]`
-Please note that you won't receive a respose to your mail if you are not
subscribed.
+请注意，如果你没有订阅邮件列表，你将不会收到邮件的回复。
### Stack Overflow
-Many members of the Flink community are active on [Stack
Overflow](https://stackoverflow.com). You can search for questions and answers
or post your questions using the
[\[apache-flink\]](https://stackoverflow.com/questions/tagged/apache-flink)
tag.
+Flink 社区的许多成员都活跃在 [Stack
Overflow](https://stackoverflow.com)。你可以在这里搜索问题和答案，或者使用
[\[apache-flink\]](https://stackoverflow.com/questions/tagged/apache-flink)
标签来发布你的问题。
-## Found a Bug?
+## 发现 Bug?
-If you observe an unexpected behavior that might be caused by a bug, you can
search for reported bugs or file a bug report in [Flink's
JIRA](https://issues.apache.org/jira/issues/?jql=project %3D FLINK).
+如果你发现一个意外行为可能是由 Bug 导致的，你可以在 [Flink's
JIRA](https://issues.apache.org/jira/issues/?jql=project %3D FLINK) 中搜索已经上报的
Bug 或者发布该 Bug。
-If you are unsure whether the unexpected behavior happend due to a bug or not,
please post a question to the [user mailing list](#user-mailing-list).
+如果你不确定意外行为的发生是否由 Bug 引起的，请发送问题到 [用户邮件列表](#user-mailing-list)。
-## Got an Error Message?
+## 收到错误信息?
-Identifying the cause for an error message can be challenging. In the
following, we list the most common error messages and explain how to handle
them.
+找到导致错误的原因通常是比较困难的。在下文中，我们列出了最常见的错误消息并解释了如何处理它们。
-### I have a NotSerializableException.
+### 我有一个 NotSerializableException 异常。
-Flink uses Java serialization to distribute copies of the application logic
(the functions and operations you implement,
-as well as the program configuration, etc.) to the parallel worker processes.
-Because of that, all functions that you pass to the API must be serializable,
as defined by
-[java.io.Serializable](http://docs.oracle.com/javase/8/docs/api/java/io/Serializable.html).
+Flink 使用 Java 序列化来分发应用程序逻辑（你实现的函数和操作，以及程序配置等）的副本到并行的工作进程。
+因此，传递给 API 的所有函数都必须是可序列化的，见
+[java.io.Serializable](http://docs.oracle.com/javase/8/docs/api/java/io/Serializable.html)
定义。
-If your function is an anonymous inner class, consider the following:
- - make the function a standalone class, or a static inner class
- - use a Java 8 lambda function.
+如果你使用的函数是匿名内部类，请考虑以下事项：
+ - 为函数构建独立的类或静态内部类。
+ - 使用 Java 8 lambda 函数。
-Is your function is already a static class, check the fields that you assign
when you create
-an instance of the class. One of the fields most likely holds a
non-serializable type.
- - In Java, use a `RichFunction` and initialize the problematic fields in the
`open()` method.
- - In Scala, you can often simply use “lazy val” to defer initialization
until the distributed execution happens. This may come at a minor performance
cost. You can naturally also use a `RichFunction` in Scala.
+如果函数已经是静态类，则在创建该类的实例时会检查该类的字段。其中很可能包含不可序列化类型的字段。
+ - 在 Java 中，使用 `RichFunction` 并且在 `open()` 方法中初始化有问题的字段。
+ - 在 Scala 中，你通常可以简单地使用 “lazy val” 声明来推迟初始化，直到分布式执行发生。这可能是一个较小的性能成本。你当然也可以在
Scala 中使用 `RichFunction`。
-### Using the Scala API, I get an error about implicit values and evidence
parameters.
+### 使用 Scala API，我收到有关隐式值和证据参数的错误。
-This error means that the implicit value for the type information could not be
provided.
-Make sure that you have an `import org.apache.flink.streaming.api.scala._`
(DataStream API) or an
-`import org.apache.flink.api.scala._` (DataSet API) statement in your code.
+此错误意味着无法提供类型信息的隐式值。确保在你的代码中存在 `import org.apache.flink.streaming.api.scala._`
(DataStream API) 或
+`import org.apache.flink.api.scala._` (DataSet API) 语句。
-If you are using Flink operations inside functions or classes that take
-generic parameters, then a TypeInformation must be available for that
parameter.
-This can be achieved by using a context bound:
+如果在接受泛型参数的函数或类中使用 Flink 操作，则必须为参数提供 TypeInformation 类型参数。
+这可以通过使用上下文绑定来实现：
~~~scala
def myFunction[T: TypeInformation](input: DataSet[T]): DataSet[Seq[T]] = {
@@ -73,61 +69,47 @@ def myFunction[T: TypeInformation](input: DataSet[T]):
DataSet[Seq[T]] = {
}
~~~
-See [Type Extraction and Serialization]({{ site.docs-snapshot
}}/dev/types_serialization.html) for
-an in-depth discussion of how Flink handles types.
+请参阅 [类型提取和序列化]({{ site.docs-snapshot }}/dev/types_serialization.html) 深入讨论
Flink 如何处理类型。
-### I see a ClassCastException: X cannot be cast to X.
+### 我看到一个 ClassCastException: X cannot be cast to X.
-When you see an exception in the style `com.foo.X` cannot be cast to
`com.foo.X` (or cannot be assigned to `com.foo.X`), it means that
-multiple versions of the class `com.foo.X` have been loaded by different class
loaders, and types of that class are attempted to be assigned to each other.
+当你看到 `com.foo.X` cannot be cast to `com.foo.X` ( 或者 cannot be assigned to
`com.foo.X`) 样式的异常时，这意味着 `com.foo.X` 类的多个版本已经由不同的类加载器加载，并且尝试相互赋值。
-The reason for that can be:
+原因可能是:
- - Class duplication through `child-first` classloading. That is an intended
mechanism to allow users to use different versions of the same
- dependencies that Flink uses. However, if different copies of these
classes move between Flink's core and the user application code, such an
exception
- can occur. To verify that this is the reason, try setting
`classloader.resolve-order: parent-first` in the configuration.
- If that makes the error disappear, please write to the mailing list to
check if that may be a bug.
+ - 通过 `child-first` 的类加载方式实现类复制。这是一种预期的机制，该机制允许用户使用相同依赖的不同版本。然而，如果这些类的不同副本在
Flink 的核心代码和用户应用程序代码之间移动，则可能发生这种异常。为了验证这个原因，请尝试在配置中设置
`classloader.resolve-order：parent-first`。如果这可以使错误消失，请写信到邮件列表以检查是否可能是 Bug。
+
+ - 从不同的执行中尝试缓存类，例如使用像 Guava 的 Interners 或 Avro 的 Schema 等通用工具进行缓存操作。尝试不使用
Interners，或减少 interner/cache 的使用范围，以确保每当新任务开始执行时都会创建新的缓存。
- - Caching of classes from different execution attempts, for example by
utilities like Guava’s Interners, or Avro's Schema cache.
- Try to not use interners, or reduce the scope of the interner/cache to
make sure a new cache is created whenever a new task
- execution is started.
+### 我有一个 AbstractMethodError 或 NoSuchFieldError 错误。
-### I have an AbstractMethodError or NoSuchFieldError.
+此类错误通常表示混淆了某些依赖的版本。这意味着在执行期间加载了不同版本的依赖项（库），而不是编译代码的版本。
-Such errors typically indicate a mix-up in some dependency version. That means
a different version of a dependency (a library)
-is loaded during the execution compared to the version that code was compiled
against.
+从 Flink 1.4.0 开始，在默认激活 `child-first` 类加载方式的情况下，相比 Flink core
所使用的依赖或类路径中的其他依赖（例如来自 Hadoop ）而言，应用程序 JAR 文件中的依赖更可能带有不同的版本。
-From Flink 1.4.0 on, dependencies in your application JAR file may have
different versions compared to dependencies used
-by Flink's core, or other dependencies in the classpath (for example from
Hadoop). That requires `child-first` classloading
-to be activated, which is the default.
+如果你在 Flink 1.4 以上的版本中看到这些问题，则可能是属于以下某种情况：
+ - 你的程序代码中存在依赖项版本冲突，确保所有依赖项版本都一致。
+ - 你与一个 Flink 不能支持 `child-first` 类加载的库发生了冲突。目前会产生这种情况的有 Scala 标准库类、Flink
自己的类、日志 API 和所有的 Hadoop 核心类。
-If you see these problems in Flink 1.4+, one of the following may be true:
- - You have a dependency version conflict within your application code. Make
sure all your dependency versions are consistent.
- - You are conflicting with a library that Flink cannot support via
`child-first` classloading. Currently these are the
- Scala standard library classes, as well as Flink's own classes, logging
APIs, and any Hadoop core classes.
+### 尽管事件正在持续发送，我的 DataStream 程序还是没有输出。
+如果你的 DataStream 程序使用了 *事件时间*，那么请检查你的 Watermark 是否已经更新。如果没有产生 Watermark，
+事件时间窗口可能永远不会触发，程序将不会产生任何结果。
-### My DataStream application produces no output, even though events are going
in.
+你可以在 Flink 的 Web UI（Watermark 部分）中查看 Watermark 是否正在更新。
-If your DataStream application uses *Event Time*, check that your watermarks
get updated. If no watermarks are produced,
-event time windows might never trigger, and the application would produce no
results.
+### 我看到了一个 "Insufficient number of network buffers" 的异常报告。
-You can check in Flink's web UI (watermarks section) whether watermarks are
making progress.
+如果你用非常高的并行度运行 Flink 程序，则可能需要增加网络缓冲区的大小。
-### I see an exception reporting "Insufficient number of network buffers".
+默认情况下，Flink 占用 JVM 堆的 10% 作为网络缓冲区的大小，最小为64MB，最大为1GB。
+你可以通过 `taskmanager.network.memory.fraction`、 `taskmanager.network.memory.min`和
+`taskmanager.network.memory.max` 参数调整这些值。
-If you run Flink with a very high parallelism, you may need to increase the
number of network buffers.
+详情请参考 [配置参考]({{ site.docs-snapshot
}}/ops/config.html#configuring-the-network-buffers)。
-By default, Flink takes 10% of the JVM heap size for network buffers, with a
minimum of 64MB and a maximum of 1GB.
-You can adjust all these values via `taskmanager.network.memory.fraction`,
`taskmanager.network.memory.min`, and
-`taskmanager.network.memory.max`.
+### 我的 Job 因为 HDFS/Hadoop 代码的各种异常失败了，我该怎么办？
-Please refer to the [Configuration Reference]({{ site.docs-snapshot
}}/ops/config.html#configuring-the-network-buffers) for details.
+最常见的原因是 Flink 的类路径中的 Hadoop 版本与你要访问的 Hadoop 集群（HDFS / YARN）版本不同。
-### My job fails with various exceptions from the HDFS/Hadoop code. What can I
do?
-
-The most common cause for that is that the Hadoop version in Flink's classpath
is different than the
-Hadoop version of the cluster you want to connect to (HDFS / YARN).
-
-The easiest way to fix that is to pick a Hadoop-free Flink version and simply
export the Hadoop path and
-classpath from the cluster.
+解决这个问题的最简单方法是选择一个不含 Hadoop 的 Flink 版本，并通过 export 的方式设置 Hadoop 路径和类路径即可。
