本节主要内容
- Spark运行方式
- Spark运行原理解析
本节内容及部分图片来自：
http://blog.csdn.net/book_mmicky/article/details/25714419
http://blog.csdn.net/yirenboy/article/details/47441465
这两篇文件对Spark的运行架构原理进行了比较深入的讲解，写得非常好，建议大家认真看一下，在此向作者致敬！
1. Spark运行方式
用户编写完Spark应用程序之后，需要将应用程序提交到集群中运行，提交时使用脚本spark-submit进行，spark-submit可以带多种参数，参数选项可以通过下列命令查看
<code class="hljs ruby has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">root<span class="hljs-variable" style="color: rgb(102, 0, 102); box-sizing: border-box;">@sparkmaster</span><span class="hljs-symbol" style="color: rgb(0, 102, 102); box-sizing: border-box;">:/hadoopLearning/spark-</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span>.<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">0</span>-bin-hadoop2.<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">4</span>/bin<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;"># ./spark-submit --help</span></code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li></ul>
可以看到，spark-submit提交参数如下：
<code class="hljs haml has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">./bin/spark-submit \ -<span class="ruby" style="box-sizing: border-box;">-<span class="hljs-class" style="box-sizing: border-box;"><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">class</span> <span class="hljs-inheritance" style="box-sizing: border-box;"><<span class="hljs-parent" style="box-sizing: border-box;">main</span></span>-<span class="hljs-title" style="box-sizing: border-box; color: rgb(102, 0, 102);">class</span>></span></span> -<span class="ruby" style="box-sizing: border-box;">-master <master-url> \</span> -<span class="ruby" style="box-sizing: border-box;">-deploy-mode <deploy-mode> \</span> -<span class="ruby" style="box-sizing: border-box;">-conf <key>=<value> \</span> ... # other options <application-jar> \ [application-arguments]</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li></ul>
下面介绍几种常用Spark应用程序提交方式：
（1）本地运行方式 –master local
<code class="hljs vhdl has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">//<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--master local，本地运行方式。读取文件可以采用本地文件系统也可采用HDFS，这里给出的例子是采用本地文件系统</span>//从本地文件系统读取文件<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">file</span>:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/README.md//生成的结果也保存到本地文件系统：<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">file</span>:/SparkWordCountResultroot@sparkmaster:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/bin# ./spark-submit <span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--master local </span><span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--class SparkWordCount --executor-memory 1g </span>/root/IdeaProjects/SparkWordCount/<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">out</span>/artifacts/SparkWordCount_jar/SparkWordCount.jar <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">file</span>:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/README.md <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">file</span>:/SparkWordCountResult</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li></ul>
（2）Standalone运行方式 –master spark://sparkmaster:7077
采用Spark自带的资源管理器进行集群资源管理
<code class="hljs livecodeserver has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">//standalone运行，指定<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--master spark://sparkmaster:7077</span><span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">//采用本地文件系统，也可采用HDFS</span><span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">//没有指定deploy-mode，默认为client deploy mode</span>root@sparkmaster:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/bin<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;"># </span>./spark-submit <span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--master spark://sparkmaster:7077 </span><span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--class SparkWordCount --executor-memory 1g </span>/root/IdeaProjects/SparkWordCount/out/artifacts/SparkWordCount_jar/SparkWordCount.jar <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">file</span>:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/README.md <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">file</span>:/SparkWordCountResult2</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li></ul>
图片来源：http://blog.csdn.net/book_mmicky/article/details/25714419，
在执行过程中，可以通过http://192.168.1.103:4040查看任务状态,192.168.1.103为sparkmaster IP地址：
也可以指定为cluster deploy mode，例如：
<code class="hljs haml has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">root@sparkmaster:/hadoopLearning/spark-1.5.0-bin-hadoop2.4/bin# ./spark-submit -<span class="ruby" style="box-sizing: border-box;">-master <span class="hljs-symbol" style="color: rgb(0, 102, 102); box-sizing: border-box;">spark:</span>/<span class="hljs-regexp" style="color: rgb(0, 136, 0); box-sizing: border-box;">/sparkmaster:7077 </span></span>-<span class="ruby" style="box-sizing: border-box;">-deploy-mode cluster</span>-<span class="ruby" style="box-sizing: border-box;">-supervise --<span class="hljs-class" style="box-sizing: border-box;"><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">class</span> <span class="hljs-title" style="box-sizing: border-box; color: rgb(102, 0, 102);">SparkWordCount</span> --<span class="hljs-title" style="box-sizing: border-box; color: rgb(102, 0, 102);">executor</span>-<span class="hljs-title" style="box-sizing: border-box; color: rgb(102, 0, 102);">memory</span> 1<span class="hljs-title" style="box-sizing: border-box; color: rgb(102, 0, 102);">g</span> </span></span><span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">/root/IdeaProjects/SparkWordCount/out/artifacts/SparkWordCount_jar/SparkWordCount.jar </span> file:/hadoopLearning/spark-1.5.0-bin-hadoop2.4/README.md file:/SparkWordCountResult3</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li></ul>
与 clinet deploy mode不同的是 cluster deploy mode中的SparkContext在集群内部创建。
（3）Yarn运行方式
采用Yarn作为底层资源管理器
<code class="hljs avrasm has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">//Yarn Clusterroot@sparkmaster:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/bin<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;"># </span>./spark-submit --master yarn-cluster --class org<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.apache</span><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.spark</span><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.examples</span><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.SparkPi</span> --executor-memory <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>g /root/IdeaProjects/SparkWordCount/<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">out</span>/artifacts/SparkWordCount_jar/SparkWordCount<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.jar</span></code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li></ul>
图片来源：http://blog.csdn.net/yirenboy/article/details/47441465
<code class="hljs avrasm has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">//Yarn Clientroot@sparkmaster:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/bin<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;"># </span>./spark-submit --master yarn-client --class org<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.apache</span><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.spark</span><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.examples</span><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.SparkPi</span> --executor-memory <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>g /root/IdeaProjects/SparkWordCount/<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">out</span>/artifacts/SparkWordCount_jar/SparkWordCount<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.jar</span></code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li></ul>
图片来源：http://blog.csdn.net/yirenboy/article/details/47441465
//Yarn Client运行效果图
2. Spark运行原理解析
（1）窄依赖与宽依赖
在前面讲的Spark编程模型当中，我们对RDD中的常用transformation与action 函数进行了讲解，我们提到RDD经过transformation操作后会生成新的RDD，前一个RDD与tranformation操作后的RDD构成了lineage关系，也即后一个RDD与前一个RDD存在一定的依赖关系，根据tranformation操作后RDD与父RDD中的分区对应关系，可以将依赖分为两种：宽依赖（wide dependency)和窄依赖（narrow dependency)，如下图所示：
图中的实线空心矩形代表一个RDD，实线空心矩形中的带阴影的小矩形表示分区(partition）。从上图中可以看到， map,filter、union等transformation操作后的RDD仅依赖于父RDD的固定分区，它们是窄依赖的；而groupByKey后的RDD的分区与父RDD所有的分区都有依赖关系，此时它们就是宽依赖的。join操作存在两种情况，如果分区仅仅依赖于父RDD的某一分区，则是窄依赖的，否则就是宽依赖。
（2）Spark job运行原理
spark-submit提交Spark应用程序后，其执行流程如下：
1 创建SparkContext对象，然后SparkContext会向Clutser Manager（集群资源管理器），例如Yarn、Standalone、Mesos等申请资源
2 资源管理器在worker node上创建executor并分配资源（CPU、内存等)，后期excutor会定时向资源管理器发送心跳信息
3 SparkContext启动DAGScheduler，将提交的作业(job）转换成若干Stage，各Stage构成DAG（Directed Acyclic Graph有向无环图），各个Stage包含若干相task，这些task的集合被称为TaskSet
4 TaskSet发送给TaskSet Scheduler，TaskSet Scheduler将Task发送给对应的Executor，同时SparkContext将应用程序代码发送到Executor，从而启动任务的执行
5 Executor执行Task，完成后释放相应的资源。
下图给出了DAGScheduler的工作原理：
当RDDG触发相应的action操作（如collect）后，DAGScheduler会根据程序中的transformation类型构造相应的DAG并生成相应的stage，所有窄依赖构成一个stage，而单个宽依赖会生成相应的stage。上图中的黑色矩形表示这些RDD被缓存过，因此上图中的只需要计算stage2、 stage3即可
前面我们提到各Stage由若干个task组成，这些task构建taskset，最终交给Task Scheduler进行调度，最终将task发送到executor上执行，如下图所示 。
（3）spark-Shell jobs调度演示
在spark-master上，启动spark-shell
<code class="hljs livecodeserver has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">root@sparkmaster:/hadoopLearning/spark-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1.5</span><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.0</span>-bin-hadoop2<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">.4</span>/bin<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;"># </span>./spark-<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">shell</span> <span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--master spark://sparkmaster:7077 </span><span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">--executor-memory 1g</span></code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li></ul>
打开浏览器，输入: http://sparkmaster:4040/，并点击executors，可以查看集群中所有的executor，如下图所示
从图中可以看到sparkmaster除了是一个executor之外，它还是一个driver即（standalone clinet模式)
<code class="hljs livecodeserver has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">val rdd1= sc.textFile(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"/README.md"</span>).flatMap(<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">line</span> => <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">line</span>.<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">split</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">" "</span>)).map(<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">word</span> => (<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">word</span>, <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>)).groupByKey().reduceByKey((<span class="hljs-operator" style="box-sizing: border-box;">a</span>,b)=><span class="hljs-operator" style="box-sizing: border-box;">a</span>+b)</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li></ul>
点击stage 1 对应的的map，查看该stage中对应的task信息及在对应的executor上的执行情况：
