[dolphinscheduler-website] branch asf-site updated: Automated deployment: 436f7d94a2101bb590cdf77c28451a39a99d6bb5

[github-bot]

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

github-bot pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/dolphinscheduler-website.git


The following commit(s) were added to refs/heads/asf-site by this push:
     new 70fc124  Automated deployment: 436f7d94a2101bb590cdf77c28451a39a99d6bb5
70fc124 is described below

commit 70fc1241b816d48e0e8af6ad2578724489a7edc7
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Fri Oct 8 16:26:40 2021 +0000

    Automated deployment: 436f7d94a2101bb590cdf77c28451a39a99d6bb5
---
 en-us/blog/DAG.html | 53 ++++++++++++++++++++++++++++++++++++++++++++++++-----
 en-us/blog/DAG.json |  2 +-
 zh-cn/blog/DAG.html | 53 ++++++++++++++++++++++++++++++++++++++++++++++++-----
 zh-cn/blog/DAG.json |  2 +-
 4 files changed, 98 insertions(+), 12 deletions(-)

diff --git a/en-us/blog/DAG.html b/en-us/blog/DAG.html
index 5109d82..ff64791 100644
--- a/en-us/blog/DAG.html
+++ b/en-us/blog/DAG.html
@@ -44,11 +44,54 @@
 </ol>
 <p><strong>For example, the following DAG graph :</strong></p>
 <p><img 
src="https://github.com/apache/dolphinscheduler-website/blob/master/img/DAG/DAG02.png?raw=true";
 alt="DAG02"></p>
-<p>In degree of node 1: 0, out degree: 2</p>
-<p>In degree of node 2: 1, out degree: 2</p>
-<p>In degree of node 3: 2, out degree: 1</p>
-<p>In degree of node 4: 2, out degree: 2</p>
-<p>In degree of node 5: 2, out degree: 0</p>
+<table>
+<thead>
+<tr>
+<th>Node</th>
+<th>in degree</th>
+<th>out degree</th>
+<th>count of in degree</th>
+<th>count of out degree</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>Node 1</td>
+<td>0</td>
+<td>Node 2,Node 4</td>
+<td>0</td>
+<td>2</td>
+</tr>
+<tr>
+<td>Node 2</td>
+<td>Node 1</td>
+<td>Node 3,Node 4</td>
+<td>1</td>
+<td>2</td>
+</tr>
+<tr>
+<td>Node 3</td>
+<td>Node 2,Node 4</td>
+<td>Node 5</td>
+<td>2</td>
+<td>1</td>
+</tr>
+<tr>
+<td>Node 4</td>
+<td>Node 1,Node 2</td>
+<td>Node 3,Node 5</td>
+<td>2</td>
+<td>2</td>
+</tr>
+<tr>
+<td>Node 5</td>
+<td>Node 3,Node 4</td>
+<td>0</td>
+<td>2</td>
+<td>0</td>
+</tr>
+</tbody>
+</table>
 <p><strong>Its topological sorting process is:</strong></p>
 <p><img 
src="https://github.com/apache/dolphinscheduler-website/blob/master/img/DAG/DAG03.png?raw=true";
 alt="DAG03"></p>
 <p>Therefore, the result of topological sorting is: {1,2,4,3,5}.</p>
diff --git a/en-us/blog/DAG.json b/en-us/blog/DAG.json
index 2b87e21..c990fc3 100644
--- a/en-us/blog/DAG.json
+++ b/en-us/blog/DAG.json
@@ -1,6 +1,6 @@
 {
   "filename": "DAG.md",
-  "__html": "<h2>Big Data Workflow Task Scheduling - Directed Acyclic Graph 
(DAG) for Topological Sorting</h2>\n<h3>Reviewing the basics：</h3>\n<h4>Graph 
traversal：</h4>\n<p>A graph traversal is a visit to all the vertices in a graph 
once and only once, starting from a vertex in the graph and following some 
search method along the edges of the graph.</p>\n<p>Note : the tree is a 
special kind of graph, so tree traversal can actually be seen as a special kind 
of graph traversal.</p>\n<h4>T [...]
+  "__html": "<h2>Big Data Workflow Task Scheduling - Directed Acyclic Graph 
(DAG) for Topological Sorting</h2>\n<h3>Reviewing the basics：</h3>\n<h4>Graph 
traversal：</h4>\n<p>A graph traversal is a visit to all the vertices in a graph 
once and only once, starting from a vertex in the graph and following some 
search method along the edges of the graph.</p>\n<p>Note : the tree is a 
special kind of graph, so tree traversal can actually be seen as a special kind 
of graph traversal.</p>\n<h4>T [...]
   "link": "/dist/en-us/blog/DAG.html",
   "meta": {}
 }
\ No newline at end of file
diff --git a/zh-cn/blog/DAG.html b/zh-cn/blog/DAG.html
index 3d68801..c19c606 100644
--- a/zh-cn/blog/DAG.html
+++ b/zh-cn/blog/DAG.html
@@ -57,11 +57,54 @@
 </ol>
 <p><strong>例如下面这个 DAG 图：</strong></p>
 <p><img 
src="https://github.com/apache/dolphinscheduler-website/blob/master/img/DAG/DAG02.png?raw=true";
 alt="DAG02"></p>
-<p>结点1的入度：0，出度：2</p>
-<p>结点2的入度：1，出度：2</p>
-<p>结点3的入度：2，出度：1</p>
-<p>结点4的入度：2，出度：2</p>
-<p>结点5的入度：2，出度：0</p>
+<table>
+<thead>
+<tr>
+<th>结点</th>
+<th>入度结点</th>
+<th>出度结点</th>
+<th>入度结点个数</th>
+<th>出度结点个数</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>结点1</td>
+<td>0</td>
+<td>结点2,结点4</td>
+<td>0个</td>
+<td>2个</td>
+</tr>
+<tr>
+<td>结点2</td>
+<td>结点1</td>
+<td>结点3,结点4</td>
+<td>1个</td>
+<td>2个</td>
+</tr>
+<tr>
+<td>结点3</td>
+<td>结点2,结点4</td>
+<td>结点5</td>
+<td>2个</td>
+<td>1个</td>
+</tr>
+<tr>
+<td>结点4</td>
+<td>结点1,结点2</td>
+<td>结点3,结点5</td>
+<td>2个</td>
+<td>2个</td>
+</tr>
+<tr>
+<td>结点5</td>
+<td>结点3,结点4</td>
+<td>0</td>
+<td>2个</td>
+<td>0个</td>
+</tr>
+</tbody>
+</table>
 <p>它的拓扑排序流程为：<img 
src="https://github.com/apache/dolphinscheduler-website/blob/master/img/DAG/DAG03.png?raw=true";
 alt="DAG03"></p>
 <p>于是，得到拓扑排序后的结果是: {1,2,4,3,5} 。</p>
 <p>如果没有结点 2  —&gt; 结点 4 的这个箭头，那么如下：</p>
diff --git a/zh-cn/blog/DAG.json b/zh-cn/blog/DAG.json
index 8028e11..79d63bc 100644
--- a/zh-cn/blog/DAG.json
+++ b/zh-cn/blog/DAG.json
@@ -1,6 +1,6 @@
 {
   "filename": "DAG.md",
-  "__html": 
"<h2>大数据工作流任务调度--有向无环图(DAG)之拓扑排序</h2>\n<h3>回顾基础知识：</h3>\n<ul>\n<li>图的遍历</li>\n</ul>\n<p>​
    图的遍历是指从图中的某一个顶点出发，按照某种搜索方法沿着图中的边对图中的所有顶点访问一次且仅访问一次。</p>\n<p>​    
<strong>注意树是一种特殊的图，所以树的遍历实际上也可以看作是一种特殊的图的遍历</strong></p>\n<ul>\n<li>\n<p>图的遍历主要有两种算法</p>\n<ul>\n<li>\n<p>广度优先搜索（Breadth
 First Search，BFS）</p>\n<p>基本思想：首先访问起始顶点 v，接着由 v 出发，依次访问 v 的各个未访问过的邻接顶点 w1, w2 
, … ,wi ，然后依次访问  w1, w2 , … , w~i~  
的所有未被访问过的邻接顶点；再从这些访问过的顶点出发，访问它们所有未被访问过的邻接顶点，直至图中所有顶点都被访问过为止。若此时图中尚有顶点未被访问，则
 另选图中一个未曾被访问过的 [...]
+  "__html": 
"<h2>大数据工作流任务调度--有向无环图(DAG)之拓扑排序</h2>\n<h3>回顾基础知识：</h3>\n<ul>\n<li>图的遍历</li>\n</ul>\n<p>​
    图的遍历是指从图中的某一个顶点出发，按照某种搜索方法沿着图中的边对图中的所有顶点访问一次且仅访问一次。</p>\n<p>​    
<strong>注意树是一种特殊的图，所以树的遍历实际上也可以看作是一种特殊的图的遍历</strong></p>\n<ul>\n<li>\n<p>图的遍历主要有两种算法</p>\n<ul>\n<li>\n<p>广度优先搜索（Breadth
 First Search，BFS）</p>\n<p>基本思想：首先访问起始顶点 v，接着由 v 出发，依次访问 v 的各个未访问过的邻接顶点 w1, w2 
, … ,wi ，然后依次访问  w1, w2 , … , w~i~  
的所有未被访问过的邻接顶点；再从这些访问过的顶点出发，访问它们所有未被访问过的邻接顶点，直至图中所有顶点都被访问过为止。若此时图中尚有顶点未被访问，则
 另选图中一个未曾被访问过的 [...]
   "link": "/dist/zh-cn/blog/DAG.html",
   "meta": {}
 }
\ No newline at end of file