Spark 随记 - 从百草味到三只松鼠

spark 随记

本文最后更新于2021年12月28日，已超过997天没有更新。如果文章内容或图片资源失效，请留言反馈，我会及时处理，谢谢！

这篇随记是笔者粗浅的分析一下spark的源码。
使用的是 https://spark.apache.org/downloads.html 下载的源码，若想省事可直接ctrl+f 直接搜索 org.apache.spark.deploy.SparkSubmit 的 SparkSubmit 这个类。但是不能对源码进行自定义的注释之类的还是比较受限的。所以推荐还是自己下载源码使用 idea 打开。笔者也是自己的下的源码简单分析一下。毕竟每次提交任务时都是看着任务开始那么多的日志也不知道发生了啥~ 哈哈部分图片是摘自网上的。侵删。

1.1 核心组件

1.1.1 Driver

Spark驱动器节点，用于执行Spark任务中的main方法，负责实际代码的执行工作。Driver在Spark作业执行时主要负责：

将用户程序转化为作业（job）；
在Executor之间调度任务(task)；
跟踪Executor的执行情况；
通过UI展示查询运行情况；

1.1.2 Executor

Spark Executor节点是一个JVM进程，负责在 Spark 作业中运行具体任务，任务彼此之间相互独立。Spark 应用启动时，Executor节点被同时启动，并且始终伴随着整个 Spark 应用的生命周期而存在。如果有Executor节点发生了故障或崩溃，Spark 应用也可以继续执行，会将出错节点上的任务调度到其他Executor节点上继续运行。

Executor有两个核心功能：

负责运行组成Spark应用的任务，并将结果返回给驱动器进程；
它们通过自身的块管理器（Block Manager）为用户程序中要求缓存的 RDD 提供内存式存储。RDD 是直接缓存在Executor进程内的，因此任务可以在运行时充分利用缓存数据加速运算。

2. 执行流程

2.1 通用流程

Submit 提交后，在Driver 中执行2条线，一条线申请资源，注册应用程序，启动executor等，另一条线执行相关操作，

1 在资源满足后，懒执行到Action 算子后，

2 触发job，划分stage

3 创建TaskSet

4 将task 分配个指定的Executor

2.2 Yarn 底层执行流程

2.2.1 执行提交应用的命令

    --class com.atguigu.spark.WordCount \

    --master yarn \

    --deploy-mode cluster \

    WordCount.jar \

    /input \

    /output

实际在spark.class 里执行了

2.2.2 底层运行

bin/java org.apache.spark.deploy.SparkSubmit "$@"

总结：

当spark submit 时其实就是执行一个java程序开启进程 SparkSubmit

2.2.3 运行SparkSubmint

-main

//对参数进行封装 mainClass ==>--class脚本内设置的class==>WordCount

*val appArgs = new SparkSubmitArguments(args)

将 --class 也就是将执行的 class 例如：wordcount

封装成SparkSubmitArguments 的属性 mainClass

\>doRunMain()

&runMain(childArgs, childClasspath, sysProps, childMainClass, args.verbose)

//根据字符串类型的类全限定名获取类对象

~ Class.forName(childMainClass)

//根据类对象获取当前类的main方法

~val mainMethod = mainClass.getMethod("main")

//调用指定类的主方法

~mainMethod.invoke(null, childArgs.toArray)

2.2.4 源码分析：

提交脚本：

bin/java org.apache.spark.deploy.SparkSubmit "$@"

//对参数进行封装 mainClass ==>--class脚本内设置的class==>WordCount

*val appArgs = new SparkSubmitArguments(args)

将 --class 也就是将执行的 class 例如：wordcount

*submit(appArgs)

//准备提交环境

//cluster： childMainClass = "org.apache.spark.deploy.yarn.Client"

//client: childMainClass = "com.dongyl.wordcount "

childMainClass 的值根据传入的client ，cluster 改变、根据childMainClass 来获取类对象。

\>val (childArgs, childClasspath, sysProps, childMainClass) = prepareSubmitEnvironment(args)

\>doRunMain()

&runMain(childArgs, childClasspath, sysProps, childMainClass, args.verbose)

//根据字符串类型的类全限定名获取类对象

~ Class.forName(childMainClass)

//根据类对象获取当前类的main方法

~val mainMethod = mainClass.getMethod("main")

//调用指定类的主方法

~mainMethod.invoke(null, childArgs.toArray)

submit(args: SparkSubmitArguments) à
def doRunMain() à
runMain(childArgs, childClasspath, sysProps, childMainClass, args.verbose)à
/**
 * 定义一个加载器
 */
val loader 
// 通过字符串类型的类全限定名反射 获取类对象
mainClass = Utils.classForName(childMainClass)
这个childMainClass 的值 是由传入参数  client 或 cluster 决定的！

2.3 YARN任务流程

2.3.1 Yarn-Client工作流程：

1 启动应用程序

启动应用程序，在SparkContext启动过程中，初始化DAGScheduler调度器，使用反射方法初始化YarnScheduler 和 YarnClientSchedulerBackend。YarnClientSchedulerBackend内部启动DriverEndpoint 和 Client。
Client向Yarn集群的ResourceManager申请启动Application Master。

2 申请资源

ResourceManager收到请求后，在集群中选一个NodeManger，为此应用申请一个Container，并在其中启动Application Master。前面讲过，Client模式中的ApplicationMaster不运行SparkContext，只与SparkContext进行联系进行资源的派分。

SparkContext启动完毕后，与Application Master通信，向Resource Manager注册，根据任务信息申请Container资源。

3 申请taskset

Application Master申请到资源后，与NodeManager通信
在Container中启动YarnClientSchedulerBackend，YarnClientSchedulerBackend向客户端中的SparkContext注册并申请taskset。

4 保持通信

SparkContext和运行中的任务保持通信，获取任务的状态和进度，随时掌握各个任务的运行状况，可以在任务失败时重启任务。

5 关闭

应用程序运行完成后，SparkContext向ResourceManager申请注销并关闭自己。

2.3.2 Yarn-Cluster工作流程：

Yarn-Cluster工作流程如上图所示:

1 提交应用程序

客户端启动Client项YARN集群提交应用程序。

2 初始化SparkContext

ResourceManager收到请求后，再集群中选一个NodeManger，为此应用申请一个Container，并在其中启动Application Master。在Application Master中进行SparkContext的初始化操作

3 AM申请资源，监控任务状态

Application Master向ResourceManager注册，为各个任务申请资源，并监控任务的运行状态直到结束

4 AM拿到资源，申请并注册TaskSet

Application Master申请到资源后，与NodeManager通信，在Container中启动CoarseGrainedExecutorBackend，CoarseGrainedExecutorBackend向客户端中的SparkContext注册并申请taskset。

5 CoarseGrainedExecutorBackend 运行任务并汇报状态

CoarseGrainedExecutorBackend运行任务并向Application Master汇报运行的状态和进度.

6 SparkContext 向RM 申请注销并关闭

应用程序运行完成后，SparkContext向ResourceManager申请注销并关闭。

2.3.3 总结

Spark虽然有多种运行模式，但是其运行架构基本上由三部分组成，

SparkContext
ClusterManager（集群资源管理器）
Executor（任务执行进程）

SparkContext用于负责与ClusterManager通信，进行资源的申请、任务的分配和监控等，负责作业执行的全生命周期管理。
ClusterManager提供了资源的分配和管理，不同模式下角色有所不同。Standalone模式下由Master提供，Yarn模式下由ResourceManager担任。

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尼巴巴闲逛
Android · Google Chrome

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}!}

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