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README.md

@@ -1,9 +1,12 @@
 # Fred的知识库
 
-共计 9 篇文章
+共计 12 篇文章
 
 ## 2024
 
+- 05-11 [一文搞懂Kerberos](https://ipfred.github.io/lang/docker/20240511160713/ "2024-05-11 16:07:13")
+- 05-10 [docker使用常用命令](https://ipfred.github.io/lang/docker/20240510103849/ "2024-05-10 10:38:49")
+- 04-28 [Vim使用技巧大全](https://ipfred.github.io/posts/20240428183407/ "2024-04-28 18:34:07")
 - 04-26 [Java核心基础](https://ipfred.github.io/lang/java/20240426133928/ "2024-04-26 13:39:28")
 - 04-26 [Java开发工具和前言](https://ipfred.github.io/lang/java/20240426111354/ "2024-04-26 11:13:54")
 - 04-24 [hive常见的命令](https://ipfred.github.io/bigdata/hive/20240424162208/ "2024-04-24 16:22:08")

archives/index.html

@@ -13,7 +13,7 @@
 <meta name="description" content="Fred&#39;s Note：探索、分享、记录自己在工作生活学习到一些东西。" /><meta name="keywords" content='Fred, Python知识库, 大数据知识库, Hugo Blog' />
   <meta itemprop="name" content="Fred的知识库">
   <meta itemprop="description" content="Fred&#39;s Note：探索、分享、记录自己在工作生活学习到一些东西。">
-  <meta itemprop="dateModified" content="2024-04-30T09:00:38+08:00">
+  <meta itemprop="dateModified" content="2024-05-13T14:47:00+08:00">
   <meta itemprop="image" content="https://ipfred.github.io/images/apple-devices-preview.webp"><meta property="og:url" content="https://ipfred.github.io/archives/">
   <meta property="og:site_name" content="Fred的知识库">
   <meta property="og:title" content="Fred的知识库">
@@ -219,8 +219,17 @@
   <div class="search-dropdown mobile">
     <div id="search-dropdown-mobile"></div>
   </div><main class="container"><div class="page archive">
-    <div class="header"><h1 class="single-title animate__animated animate__pulse animate__faster"><i class="fa-solid fa-box-archive fa-fw me-1" aria-hidden="true"></i>归档 <sup>9</sup>
-      </h1><p class="single-subtitle total-word-count" title='总计约 13623 字'><i class="fa-regular fa-keyboard fa-fw" aria-hidden="true"></i> 总计约 13.62K 字</p></div><h2 class="group-title"><i class="fa-regular fa-calendar fa-fw me-1" aria-hidden="true"></i>2024</h2><article class="archive-item">
+    <div class="header"><h1 class="single-title animate__animated animate__pulse animate__faster"><i class="fa-solid fa-box-archive fa-fw me-1" aria-hidden="true"></i>归档 <sup>12</sup>
+      </h1><p class="single-subtitle total-word-count" title='总计约 18472 字'><i class="fa-regular fa-keyboard fa-fw" aria-hidden="true"></i> 总计约 18.47K 字</p></div><h2 class="group-title"><i class="fa-regular fa-calendar fa-fw me-1" aria-hidden="true"></i>2024</h2><article class="archive-item">
+            <a href="/lang/docker/20240511160713/" class="archive-item-link">一文搞懂Kerberos</a>
+            <span class="archive-item-date" title='2024-05-11 16:07:13'>05-11</span>
+          </article><article class="archive-item">
+            <a href="/lang/docker/20240510103849/" class="archive-item-link">docker使用常用命令</a>
+            <span class="archive-item-date" title='2024-05-10 10:38:49'>05-10</span>
+          </article><article class="archive-item">
+            <a href="/posts/20240428183407/" class="archive-item-link">Vim使用技巧大全</a>
+            <span class="archive-item-date" title='2024-04-28 18:34:07'>04-28</span>
+          </article><article class="archive-item">
             <a href="/lang/java/20240426133928/" class="archive-item-link">Java核心基础</a>
             <span class="archive-item-date" title='2024-04-26 13:39:28'>04-26</span>
           </article><article class="archive-item">

baidu_urls.txt

@@ -1,3 +1,6 @@
+https://ipfred.github.io/lang/docker/20240511160713/
+https://ipfred.github.io/lang/docker/20240510103849/
+https://ipfred.github.io/posts/20240428183407/
 https://ipfred.github.io/lang/java/20240426133928/
 https://ipfred.github.io/lang/java/20240426111354/
 https://ipfred.github.io/web/

bigdata/hadoop/a9bc224/index.html

@@ -394,7 +394,7 @@ <h2 id="hdfs文件读取过程" class="heading-element">
         </noscript></div></article>
 
   <aside class="toc" id="toc-auto" aria-label="目录"><h2 class="toc-title">目录&nbsp;<i class="toc-icon fa-solid fa-angle-down fa-fw" aria-hidden="true"></i></h2>
-      <div class="toc-content" id="toc-content-auto"></div></aside></main><footer class="footer">
+      <div class="toc-content always-active" id="toc-content-auto"></div></aside></main><footer class="footer">
     <div class="footer-container"><div class="footer-line powered order-2">由 <a href="https://gohugo.io/" target="_blank" rel="external nofollow noopener noreferrer" title="Hugo 0.125.2"><img class="hugo-icon" src="/images/hugo.min.svg" alt="Hugo logo" /> Hugo</a> 强力驱动 | 主题 - <a href="https://github.com/hugo-fixit/FixIt" target="_blank" rel="external" title="FixIt v0.3.2"><img class="fixit-icon" src="/images/fixit.min.svg" alt="FixIt logo" /> FixIt</a>
         </div><div class="footer-line copyright order-1" itemscope itemtype="http://schema.org/CreativeWork"><i class="fa-regular fa-copyright fa-fw" aria-hidden="true"></i>
             <span itemprop="copyrightYear">2024</span><span class="author" itemprop="copyrightHolder">

bigdata/hadoop/hadoop命令行的使用/index.html

@@ -762,7 +762,7 @@
         </noscript></div></article>
 
   <aside class="toc" id="toc-auto" aria-label="目录"><h2 class="toc-title">目录&nbsp;<i class="toc-icon fa-solid fa-angle-down fa-fw" aria-hidden="true"></i></h2>
-      <div class="toc-content" id="toc-content-auto"></div></aside></main><footer class="footer">
+      <div class="toc-content always-active" id="toc-content-auto"></div></aside></main><footer class="footer">
     <div class="footer-container"><div class="footer-line powered order-2">由 <a href="https://gohugo.io/" target="_blank" rel="external nofollow noopener noreferrer" title="Hugo 0.125.2"><img class="hugo-icon" src="/images/hugo.min.svg" alt="Hugo logo" /> Hugo</a> 强力驱动 | 主题 - <a href="https://github.com/hugo-fixit/FixIt" target="_blank" rel="external" title="FixIt v0.3.2"><img class="fixit-icon" src="/images/fixit.min.svg" alt="FixIt logo" /> FixIt</a>
         </div><div class="footer-line copyright order-1" itemscope itemtype="http://schema.org/CreativeWork"><i class="fa-regular fa-copyright fa-fw" aria-hidden="true"></i>
             <span itemprop="copyrightYear">2024</span><span class="author" itemprop="copyrightHolder">

bigdata/hive/20240424162208/index.html

@@ -543,7 +543,7 @@ <h3 id="hive内部表" class="heading-element">
         </noscript></div></article>
 
   <aside class="toc" id="toc-auto" aria-label="目录"><h2 class="toc-title">目录&nbsp;<i class="toc-icon fa-solid fa-angle-down fa-fw" aria-hidden="true"></i></h2>
-      <div class="toc-content" id="toc-content-auto"></div></aside></main><footer class="footer">
+      <div class="toc-content always-active" id="toc-content-auto"></div></aside></main><footer class="footer">
     <div class="footer-container"><div class="footer-line powered order-2">由 <a href="https://gohugo.io/" target="_blank" rel="external nofollow noopener noreferrer" title="Hugo 0.125.2"><img class="hugo-icon" src="/images/hugo.min.svg" alt="Hugo logo" /> Hugo</a> 强力驱动 | 主题 - <a href="https://github.com/hugo-fixit/FixIt" target="_blank" rel="external" title="FixIt v0.3.2"><img class="fixit-icon" src="/images/fixit.min.svg" alt="FixIt logo" /> FixIt</a>
         </div><div class="footer-line copyright order-1" itemscope itemtype="http://schema.org/CreativeWork"><i class="fa-regular fa-copyright fa-fw" aria-hidden="true"></i>
             <span itemprop="copyrightYear">2024</span><span class="author" itemprop="copyrightHolder">

bigdata/index.html

@@ -208,9 +208,9 @@
     <div id="search-dropdown-mobile"></div>
   </div><main class="container"><div class="page archive">
     <div class="header"><h1 class="single-title animate__animated animate__pulse animate__faster"><i class="fa-solid fa-feather fa-fw me-1" aria-hidden="true"></i>所有大数据 <sup>4</sup>
-      </h1><p class="single-subtitle total-word-count" title='总计约 5055 字'><i class="fa-regular fa-keyboard fa-fw" aria-hidden="true"></i> 总计约 5.05K 字</p></div><h2 class="group-title"><i class="fa-regular fa-calendar-check fa-fw me-1" aria-hidden="true"></i>最近更新</h2><article class="archive-item">
+      </h1><p class="single-subtitle total-word-count" title='总计约 5072 字'><i class="fa-regular fa-keyboard fa-fw" aria-hidden="true"></i> 总计约 5.07K 字</p></div><h2 class="group-title"><i class="fa-regular fa-calendar-check fa-fw me-1" aria-hidden="true"></i>最近更新</h2><article class="archive-item">
           <a href="/bigdata/spark/spark%E5%85%A5%E9%97%A8/" class="archive-item-link">spark简单介绍</a>
-          <span class="archive-item-date" title='2024-04-26 15:07:47'>更新于 04-26</span>
+          <span class="archive-item-date" title='2024-04-30 16:53:13'>更新于 04-30</span>
         </article><article class="archive-item">
           <a href="/bigdata/hadoop/hadoop%E5%91%BD%E4%BB%A4%E8%A1%8C%E7%9A%84%E4%BD%BF%E7%94%A8/" class="archive-item-link">hadoop命令行的使用</a>
           <span class="archive-item-date" title='2024-04-26 09:57:44'>更新于 04-26</span>

bigdata/index.xml

@@ -36,7 +36,7 @@
       <link>https://ipfred.github.io/bigdata/spark/spark%E5%85%A5%E9%97%A8/</link>
       <pubDate>Sat, 20 Apr 2024 20:14:22 +0800</pubDate><author>330446875@qq.com (Fred)</author>
       <guid>https://ipfred.github.io/bigdata/spark/spark%E5%85%A5%E9%97%A8/</guid>
-      <description>Configuration - Spark 2.4.8 配置参数 Apache Spark A Unified engine for large-scale data analytics Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, pandas API on Spark for pandas workloads, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for incremental computation and stream processing. DownloadingGet Spark from the downloads page of the project website. This documentation is for Spark version 3.5.1. Spark uses Hadoop’s client libraries for HDFS and YARN. Downloads are pre-packaged for a handful of popular Hadoop versions. Users can also download a “Hadoop free” binary</description>
+      <description>Configuration - Spark 2.4.8 配置参数 Spark SQL — PySpark官方API手册 Apache Spark A Unified engine for large-scale data analytics Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, pandas API on Spark for pandas workloads, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for incremental computation and stream processing. DownloadingGet Spark from the downloads page of the project website. This documentation is for Spark version 3.5.1. Spark uses Hadoop’s client libraries for HDFS and YARN. Downloads are pre-packaged for a handful of popular Hadoop versions. Users</description>
     </item>
   </channel>
 </rss>