LarryDpk
发布于 2020-08-02 / 1775 阅读
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Spring Cloud Data Flow用Shell来操作,方便建立CICD

1 前言

之前我们用两篇文章讲解了Spring Cloud Data Flow,例子都是用UI操作的,但我们在Linux系统上经常是无法提供界面来操作,集成在Jenkins上也无法使用UI。好在官方提供了Data Flow Shell工具,可以在命令行模式下进行操作,非常方便。

相关文章可参考:

Spring Cloud Data Flow初体验,以Local模式运行

把Spring Cloud Data Flow部署在Kubernetes上,再跑个任务试试

Spring Cloud Data Flow Server提供了可操作的REST API,所以这个Shell工具的本质还是通过调用REST API来交互的。

2 常用操作

2.1 启动

首先要确保我们已经安装有Java环境和下载了可执行的jar包:spring-cloud-dataflow-shell-2.5.3.RELEASE.jar

然后启动如下:

$ java -jar spring-cloud-dataflow-shell-2.5.3.RELEASE.jar

默认是连接了http://localhost:9393Server,可以通过--dataflow.uri=地址来指定。如果需要认证信息,需要加上--dataflow.username=用户 --dataflow.password=密码

比如我们连接之前安装在Kubernetes上的Server如下:

$ java -jar spring-cloud-dataflow-shell-2.5.3.RELEASE.jar --dataflow.uri=http://localhost:30093

2.2 Application操作

介绍一下Application相关操作:

列出所有目前注册的app

dataflow:>app list
╔═══╤══════╤═════════╤════╤════════════════════╗
║app│source│processor│sink│        task        ║
╠═══╪══════╪═════════╪════╪════════════════════╣
║   │      │         │    │composed-task-runner║
║   │      │         │    │timestamp-batch     ║
║   │      │         │    │timestamp           ║
╚═══╧══════╧═════════╧════╧════════════════════╝

查看某个app的信息:

dataflow:>app info --type task timestamp
Information about task application 'timestamp':
Version: '2.1.1.RELEASE':
Default application version: 'true':
Resource URI: docker:springcloudtask/timestamp-task:2.1.1.RELEASE
╔══════════════════════════════╤══════════════════════════════╤══════════════════════════════╤══════════════════════════════╗
║         Option Name          │         Description          │           Default            │             Type             ║
╠══════════════════════════════╪══════════════════════════════╪══════════════════════════════╪══════════════════════════════╣
║timestamp.format              │The timestamp format,         │yyyy-MM-dd HH:mm:ss.SSS       │java.lang.String              ║
║                              │"yyyy-MM-dd HH:mm:ss.SSS" by  │                              │                              ║
║                              │default.                      │                              │                              ║
╚══════════════════════════════╧══════════════════════════════╧══════════════════════════════╧══════════════════════════════╝

清除app注册信息:

dataflow:>app unregister --type task timestamp
Successfully unregistered application 'timestamp' with type 'task'.
dataflow:>app list
╔═══╤══════╤═════════╤════╤════════════════════╗
║app│source│processor│sink│        task        ║
╠═══╪══════╪═════════╪════╪════════════════════╣
║   │      │         │    │composed-task-runner║
║   │      │         │    │timestamp-batch     ║
╚═══╧══════╧═════════╧════╧════════════════════╝

清除所有app注册信息:

dataflow:>app all unregister
Successfully unregistered applications.
dataflow:>app list 
No registered apps.
You can register new apps with the 'app register' and 'app import' commands.

注册一个app

dataflow:>app register --name timestamp-pkslow --type task --uri docker:springcloudtask/timestamp-task:2.1.1.RELEASE
Successfully registered application 'task:timestamp-pkslow'
dataflow:>app list
╔═══╤══════╤═════════╤════╤════════════════╗
║app│source│processor│sink│      task      ║
╠═══╪══════╪═════════╪════╪════════════════╣
║   │      │         │    │timestamp-pkslow║
╚═══╧══════╧═════════╧════╧════════════════╝

批量导入app,可以从一个URL或一个properties文件导入:

dataflow:>app import https://dataflow.spring.io/task-docker-latest
Successfully registered 3 applications from [task.composed-task-runner, task.timestamp.metadata, task.composed-task-runner.metadata, task.timestamp-batch.metadata, task.timestamp-batch, task.timestamp]
dataflow:>app list
╔═══╤══════╤═════════╤════╤════════════════════╗
║app│source│processor│sink│        task        ║
╠═══╪══════╪═════════╪════╪════════════════════╣
║   │      │         │    │timestamp-pkslow    ║
║   │      │         │    │composed-task-runner║
║   │      │         │    │timestamp-batch     ║
║   │      │         │    │timestamp           ║
╚═══╧══════╧═════════╧════╧════════════════════╝

需要注意的是,在注册或导入app时,如果重复的话,默认是无法导入的,不会覆盖。如果想要覆盖,可以加参数--force

dataflow:>app register --name timestamp-pkslow --type task --uri docker:springcloudtask/timestamp-task:2.1.1.RELEASE
Command failed org.springframework.cloud.dataflow.rest.client.DataFlowClientException: The 'task:timestamp-pkslow' application is already registered as docker:springcloudtask/timestamp-task:2.1.1.RELEASE
The 'task:timestamp-pkslow' application is already registered as docker:springcloudtask/timestamp-task:2.1.1.RELEASE

dataflow:>app register --name timestamp-pkslow --type task --uri docker:springcloudtask/timestamp-task:2.1.1.RELEASE --force
Successfully registered application 'task:timestamp-pkslow'

2.3 Task操作

列出task

dataflow:>task list
╔════════════════╤════════════════════════════════╤═══════════╤═══════════╗
║   Task Name    │        Task Definition         │description│Task Status║
╠════════════════╪════════════════════════════════╪═══════════╪═══════════╣
║timestamp-pkslow│timestamp                       │           │COMPLETE   ║
║timestamp-two   │<t1: timestamp || t2: timestamp>│           │ERROR      ║
║timestamp-two-t1│timestamp                       │           │COMPLETE   ║
║timestamp-two-t2│timestamp                       │           │COMPLETE   ║
╚════════════════╧════════════════════════════════╧═══════════╧═══════════╝

删除一个task,这里我们删除的是一个组合task,所以会把子task也一并删除了:

dataflow:>task destroy timestamp-two
Destroyed task 'timestamp-two'
dataflow:>task list
╔════════════════╤═══════════════╤═══════════╤═══════════╗
║   Task Name    │Task Definition│description│Task Status║
╠════════════════╪═══════════════╪═══════════╪═══════════╣
║timestamp-pkslow│timestamp      │           │COMPLETE   ║
╚════════════════╧═══════════════╧═══════════╧═══════════╝

删除所有task,会有风险提示:

dataflow:>task all destroy 
Really destroy all tasks? [y, n]: y
All tasks destroyed

dataflow:>task list
╔═════════╤═══════════════╤═══════════╤═══════════╗
║Task Name│Task Definition│description│Task Status║
╚═════════╧═══════════════╧═══════════╧═══════════╝

创建一个task

dataflow:>task create timestamp-pkslow-t1 --definition "timestamp --format=\"yyyy\"" --description "pkslow timestamp task"
Created new task 'timestamp-pkslow-t1'
dataflow:>task list
╔═══════════════════╤═══════════════════════╤═════════════════════╤═══════════╗
║     Task Name     │    Task Definition    │     description     │Task Status║
╠═══════════════════╪═══════════════════════╪═════════════════════╪═══════════╣
║timestamp-pkslow-t1│timestamp --format=yyyy│pkslow timestamp task│UNKNOWN    ║
╚═══════════════════╧═══════════════════════╧═════════════════════╧═══════════╝

启动一个task并查看状态,启动时需要记录执行ID,然后通过执行ID来查询状态:

dataflow:>task launch timestamp-pkslow-t1
Launched task 'timestamp-pkslow-t1' with execution id 8
dataflow:>task execution status 8
╔═══════════════╤═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗
║      Key      │                                                                                     Value                                                                                     ║
╠═══════════════╪═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣
║Id             │8                                                                                                                                                                              ║
║Resource URL   │Docker Resource [docker:springcloudtask/timestamp-task:2.1.1.RELEASE]                                                                                                          ║
║Name           │timestamp-pkslow-t1                                                                                                                                                            ║
║CLI Arguments  │[--timestamp.format=yyyy, --spring.datasource.username=******, --spring.datasource.url=******, --spring.datasource.driverClassName=org.mariadb.jdbc.Driver,                    ║
║               │--spring.cloud.task.name=timestamp-pkslow-t1, --spring.datasource.password=******, --spring.cloud.data.flow.platformname=default, --spring.cloud.task.executionid=8]           ║
║App Arguments  │                 timestamp.format = yyyy                                                                                                                                       ║
║               │       spring.datasource.username = ******                                                                                                                                     ║
║               │            spring.datasource.url = ******                                                                                                                                     ║
║               │spring.datasource.driverClassName = org.mariadb.jdbc.Driver                                                                                                                    ║
║               │           spring.cloud.task.name = timestamp-pkslow-t1                                                                                                                        ║
║               │       spring.datasource.password = ******                                                                                                                                     ║
║Deployment     │                                                                                                                                                                               ║
║Properties     │                                                                                                                                                                               ║
║Job Execution  │[]                                                                                                                                                                             ║
║Ids            │                                                                                                                                                                               ║
║Start Time     │Sun Aug 02 01:20:52 CST 2020                                                                                                                                                   ║
║End Time       │Sun Aug 02 01:20:52 CST 2020                                                                                                                                                   ║
║Exit Code      │0                                                                                                                                                                              ║
║Exit Message   │                                                                                                                                                                               ║
║Error Message  │                                                                                                                                                                               ║
║External       │timestamp-pkslow-t1-r27jvm6591                                                                                                                                                 ║
║Execution Id   │                                                                                                                                                                               ║
╚═══════════════╧═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝

查看所有task执行并查看执行日志:

dataflow:>task execution list 
╔═══════════════════╤══╤════════════════════════════╤════════════════════════════╤═════════╗
║     Task Name     │ID│         Start Time         │          End Time          │Exit Code║
╠═══════════════════╪══╪════════════════════════════╪════════════════════════════╪═════════╣
║timestamp-pkslow-t1│8 │Sun Aug 02 01:20:52 CST 2020│Sun Aug 02 01:20:52 CST 2020│0        ║
║timestamp-two-t2   │7 │Sat Aug 01 00:46:34 CST 2020│Sat Aug 01 00:46:35 CST 2020│0        ║
║timestamp-two-t1   │6 │Sat Aug 01 00:46:28 CST 2020│Sat Aug 01 00:46:28 CST 2020│0        ║
║timestamp-two      │5 │Sat Aug 01 00:46:22 CST 2020│Sat Aug 01 00:46:23 CST 2020│1        ║
║timestamp-two      │4 │Sat Aug 01 00:45:45 CST 2020│Sat Aug 01 00:46:37 CST 2020│0        ║
║timestamp-pkslow   │3 │Wed Jul 29 16:57:19 CST 2020│Wed Jul 29 16:57:19 CST 2020│0        ║
║timestamp          │2 │Wed Jul 29 15:41:40 CST 2020│Wed Jul 29 15:41:40 CST 2020│0        ║
║timestamp          │1 │                            │                            │         ║
╚═══════════════════╧══╧════════════════════════════╧════════════════════════════╧═════════╝

dataflow:>task execution log 8
2020-08-01 17:20:48.967  INFO 1 --- [           main] trationDelegate$BeanPostProcessorChecker : Bean 'org.springframework.cloud.autoconfigure.ConfigurationPropertiesRebinderAutoConfiguration' of type [org.springframework.cloud.autoconfigure.ConfigurationPropertiesRebinderAutoConfiguration$$EnhancerBySpringCGLIB$$ccb7e6d0] is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying)

  .   ____          _            __ _ _
 /\\ / ___'_ __ _ _(_)_ __  __ _ \ \ \ \
( ( )\___ | '_ | '_| | '_ \/ _` | \ \ \ \
 \\/  ___)| |_)| | | | | || (_| |  ) ) ) )
  '  |____| .__|_| |_|_| |_\__, | / / / /
 =========|_|==============|___/=/_/_/_/
 :: Spring Boot ::       (v2.1.13.RELEASE)

2020-08-01 17:20:49.200  INFO 1 --- [           main] c.c.c.ConfigServicePropertySourceLocator : Fetching config from server at : http://localhost:8888
2020-08-01 17:20:49.411  INFO 1 --- [           main] c.c.c.ConfigServicePropertySourceLocator : Connect Timeout Exception on Url - http://localhost:8888. Will be trying the next url if available
2020-08-01 17:20:49.411  WARN 1 --- [           main] c.c.c.ConfigServicePropertySourceLocator : Could not locate PropertySource: I/O error on GET request for "http://localhost:8888/timestamp-task/default": Connection refused (Connection refused); nested exception is java.net.ConnectException: Connection refused (Connection refused)
2020-08-01 17:20:49.415  INFO 1 --- [           main] o.s.c.t.a.t.TimestampTaskApplication     : No active profile set, falling back to default profiles: default
2020-08-01 17:20:50.059  INFO 1 --- [           main] o.s.cloud.context.scope.GenericScope     : BeanFactory id=206f72b7-a955-301c-9338-4db66c6fe95b
2020-08-01 17:20:50.130  INFO 1 --- [           main] trationDelegate$BeanPostProcessorChecker : Bean 'org.springframework.cloud.autoconfigure.ConfigurationPropertiesRebinderAutoConfiguration' of type [org.springframework.cloud.autoconfigure.ConfigurationPropertiesRebinderAutoConfiguration$$EnhancerBySpringCGLIB$$ccb7e6d0] is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying)
2020-08-01 17:20:50.479  INFO 1 --- [           main] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Starting...
2020-08-01 17:20:50.663  INFO 1 --- [           main] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Start completed.
2020-08-01 17:20:51.602  INFO 1 --- [           main] o.s.c.t.a.t.TimestampTaskApplication     : Started TimestampTaskApplication in 3.98 seconds (JVM running for 4.782)
2020-08-01 17:20:51.604  INFO 1 --- [           main] TimestampTaskConfiguration$TimestampTask : 2020
2020-08-01 17:20:51.626  INFO 1 --- [       Thread-5] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Shutdown initiated...
2020-08-01 17:20:51.633  INFO 1 --- [       Thread-5] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Shutdown completed.

2.4 Http请求

可以进行http请求:

dataflow:>http get https://www.pkslow.com

dataflow:>http post --target https://www.pkslow.com --data "data"
> POST (text/plain) https://www.pkslow.com data
> 405 METHOD_NOT_ALLOWED

Error sending data 'data' to 'https://www.pkslow.com'

2.5 读取并执行文件

先准备一个脚本文件,用来放Data Flow Shell命令,文件名为pkslow.shell,内容如下:

version
date
app list

执行与结果如下:

dataflow:>script pkslow.shell
version
2.5.3.RELEASE
date
Sunday, August 2, 2020 1:59:34 AM CST
app list
╔═══╤══════╤═════════╤════╤════════════════════╗
║app│source│processor│sink│        task        ║
╠═══╪══════╪═════════╪════╪════════════════════╣
║   │      │         │    │timestamp-pkslow    ║
║   │      │         │    │composed-task-runner║
║   │      │         │    │timestamp-batch     ║
║   │      │         │    │timestamp           ║
╚═══╧══════╧═════════╧════╧════════════════════╝

Script required 0.045 seconds to execute
dataflow:>

但其实我们在CI/CDpipeline中,并不想先启动一个shell命令行,然后再执行一个脚本。我们想一步到位,直接执行,执行完毕后退出shell命令行。这也是有办法的,可以在启动的时候通过--spring.shell.commandFile指定文件,如果有多个文件则用逗号,分隔。如下所示:

$ java -jar spring-cloud-dataflow-shell-2.5.3.RELEASE.jar --dataflow.uri=http://localhost:30093 --spring.shell.commandFile=pkslow.shell
Successfully targeted http://localhost:30093
2020-08-02T02:03:49+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:311 - 2.5.3.RELEASE
2020-08-02T02:03:49+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:311 - Sunday, August 2, 2020 2:03:49 AM CST
2020-08-02T02:03:49+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:309 - 
╔═══╤══════╤═════════╤════╤════════════════════╗
║app│source│processor│sink│        task        ║
╠═══╪══════╪═════════╪════╪════════════════════╣
║   │      │         │    │timestamp-pkslow    ║
║   │      │         │    │composed-task-runner║
║   │      │         │    │timestamp-batch     ║
║   │      │         │    │timestamp           ║
╚═══╧══════╧═════════╧════╧════════════════════╝
$

执行完毕后,不会在shell命令行模式里,而是退回linux的终端。这正是我们所需要的。

我们来准备一个注册应用——创建任务——执行任务的脚本试试:

version
date
app register --name pkslow-app-1 --type task --uri docker:springcloudtask/timestamp-task:2.1.1.RELEASE
task create pkslow-task-1 --definition "pkslow-app-1"
task launch pkslow-task-1

执行与结果如下:

$ java -jar spring-cloud-dataflow-shell-2.5.3.RELEASE.jar --dataflow.uri=http://localhost:30093 --spring.shell.commandFile=pkslow.shell
Successfully targeted http://localhost:30093
2020-08-02T02:06:41+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:311 - 2.5.3.RELEASE
2020-08-02T02:06:41+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:311 - Sunday, August 2, 2020 2:06:41 AM CST
2020-08-02T02:06:41+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:311 - Successfully registered application 'task:pkslow-app-1'
2020-08-02T02:06:42+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:311 - Created new task 'pkslow-task-1'
2020-08-02T02:06:51+0800 INFO main o.s.c.d.s.DataflowJLineShellComponent:311 - Launched task 'pkslow-task-1' with execution id 9

这样,我们就可以实现自动化打包与部署运行了。

3 一些使用技巧

强大的shell工具提供了许多命令,其实不用一一记住,可以通过help命令查看所有命令:

dataflow:>help
* ! - Allows execution of operating system (OS) commands
* // - Inline comment markers (start of line only)
* ; - Inline comment markers (start of line only)
* app all unregister - Unregister all applications
* app default - Change the default application version
* app import - Register all applications listed in a properties file
* app info - Get information about an application
* app list - List all registered applications
* app register - Register a new application
* app unregister - Unregister an application
* clear - Clears the console
* cls - Clears the console
* dataflow config info - Show the Dataflow server being used
* dataflow config server - Configure the Spring Cloud Data Flow REST server to use
* date - Displays the local date and time
* exit - Exits the shell
* help - List all commands usage
* http get - Make GET request to http endpoint
* http post - POST data to http endpoint
* job execution display - Display the details of a specific job execution
* job execution list - List created job executions filtered by jobName
* job execution restart - Restart a failed job by jobExecutionId
* job execution step display - Display the details of a specific step execution
* job execution step list - List step executions filtered by jobExecutionId
* job execution step progress - Display the details of a specific step progress
* job instance display - Display the job executions for a specific job instance.
* quit - Exits the shell
* runtime apps - List runtime apps
* script - Parses the specified resource file and executes its commands
* stream all destroy - Destroy all existing streams
* stream all undeploy - Un-deploy all previously deployed stream
* stream create - Create a new stream definition
* stream deploy - Deploy a previously created stream using Skipper
* stream destroy - Destroy an existing stream
* stream history - Get history for the stream deployed using Skipper
* stream info - Show information about a specific stream
* stream list - List created streams
* stream manifest - Get manifest for the stream deployed using Skipper
* stream platform-list - List Skipper platforms
* stream rollback - Rollback a stream using Skipper
* stream scale app instances - Scale app instances in a stream
* stream undeploy - Un-deploy a previously deployed stream
* stream update - Update a previously created stream using Skipper
* stream validate - Verify that apps contained in the stream are valid.
* system properties - Shows the shell's properties
* task all destroy - Destroy all existing tasks
* task create - Create a new task definition
* task destroy - Destroy an existing task
* task execution cleanup - Clean up any platform specific resources linked to a task execution
* task execution current - Display count of currently executin tasks and related information
* task execution list - List created task executions filtered by taskName
* task execution log - Retrieve task execution log
* task execution status - Display the details of a specific task execution
* task execution stop - Stop executing tasks
* task launch - Launch a previously created task
* task list - List created tasks
* task platform-list - List platform accounts for tasks
* task schedule create - Create new task schedule
* task schedule destroy - Delete task schedule
* task schedule list - List task schedules by task definition name
* task validate - Validate apps contained in task definitions
* version - Displays shell version

如果只对特定的一类命令感兴趣,可以通过help xxx的方式获取帮助:

dataflow:>help version
* version - Displays shell version

dataflow:>help app
* app all unregister - Unregister all applications
* app default - Change the default application version
* app import - Register all applications listed in a properties file
* app info - Get information about an application
* app list - List all registered applications
* app register - Register a new application
* app unregister - Unregister an application

shell还支持tab键补全命令。

4 总结

本文的命令比较多,执行结果也贴出来了。这样能加深理解。