Apache Flink 零基础入门(四):客户端操作的 5 种模式

阅读数:5681 2019 年 7 月 11 日 07:00

Apache Flink零基础入门(四):客户端操作的5种模式

我们在 Apache Flink 零基础入门系列文章的前几篇已经为大家介绍了 Flink 开发环境的搭建和应用的部署以及运行,今天这篇文章主要介绍 Flink 的客户端操作。本文以实际操作为主,基于社区的 Flink 1.7.2 版本,使用的操作系统是 Mac 系统,浏览器是 Google Chrome 浏览器。有关开发环境的准备和集群的部署,请参考「开发环境搭建和应用的配置、部署及运行」的内容。

1. 概要

如下图所示,Flink 提供了丰富的客户端操作来提交任务和与任务进行交互,包括 Flink 命令行,Scala Shell,SQL Client,Restful API 和 Web。Flink 首先提供的最重要的是命令行,其次是 SQL Client 用于提交 SQL 任务的运行,还有就是 Scala Shell 提交 Table API 的任务。同时,Flink 也提供了 Restful 服务,用户可以通过 http 方式进行调用。此外,还有 Web 的方式可以提交任务。

Apache Flink零基础入门(四):客户端操作的5种模式

在 Flink 安装目录的 bin 目录下面可以看到有 flink, start-scala-shell.sh sql-client.sh 等文件,这些都是客户端操作的入口。

Apache Flink零基础入门(四):客户端操作的5种模式

2.Flink 客户端操作

2.1 Flink 命令行

Flink 的命令行参数很多,输入 flink - h 能看到完整的说明:

复制代码
➜ flink-1.7.2 bin/flink -h

如果想看某一个命令的参数,比如 Run 命令,输入:

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➜ flink-1.7.2 bin/flink run -h

本文主要讲解常见的一些操作,更详细的文档请参考: Flink 命令行官方文档

2.1.1 Standalone

首先启动一个 Standalone 的集群:

复制代码
➜ flink-1.7.2 bin/start-cluster.sh
Starting cluster.
Starting standalonesession daemon on host zkb-MBP.local.
Starting taskexecutor daemon on host zkb-MBP.local.

打开 http://127.0.0.1:8081 能看到 Web 界面。

Run

运行任务,以 Flink 自带的例子 TopSpeedWindowing 为例:

复制代码
➜ flink-1.7.2 bin/flink run -d examples/streaming/TopSpeedWindowing.jar
Starting execution of program
Executing TopSpeedWindowing example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
Job has been submitted with JobID 5e20cb6b0f357591171dfcca2eea09de

运行起来后默认是 1 个并发:

Apache Flink零基础入门(四):客户端操作的5种模式

点左侧「Task Manager」,然后点「Stdout」能看到输出日志:

Apache Flink零基础入门(四):客户端操作的5种模式

或者查看本地 Log 目录下的 *.out 文件:

Apache Flink零基础入门(四):客户端操作的5种模式

List

查看任务列表:

复制代码
➜ flink-1.7.2 bin/flink list -m 127.0.0.1:8081
Waiting for response...
------------------ Running/Restarting Jobs -------------------
24.03.2019 10:14:06 : 5e20cb6b0f357591171dfcca2eea09de : CarTopSpeedWindowingExample (RUNNING)
--------------------------------------------------------------
No scheduled jobs.
Stop

停止任务。通过 -m 来指定要停止的 JobManager 的主机地址和端口。

复制代码
➜ flink-1.7.2 bin/flink stop -m 127.0.0.1:8081 d67420e52bd051fae2fddbaa79e046bb
Stopping job d67420e52bd051fae2fddbaa79e046bb.
------------------------------------------------------------
The program finished with the following exception:
org.apache.flink.util.FlinkException: Could not stop the job d67420e52bd051fae2fddbaa79e046bb.
at org.apache.flink.client.cli.CliFrontend.lambda$stop$5(CliFrontend.java:554)
at org.apache.flink.client.cli.CliFrontend.runClusterAction(CliFrontend.java:985)
at org.apache.flink.client.cli.CliFrontend.stop(CliFrontend.java:547)
at org.apache.flink.client.cli.CliFrontend.parseParameters(CliFrontend.java:1062)
at org.apache.flink.client.cli.CliFrontend.lambda$main$11(CliFrontend.java:1126)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1836)
at org.apache.flink.runtime.security.HadoopSecurityContext.runSecured(HadoopSecurityContext.java:41)
at org.apache.flink.client.cli.CliFrontend.main(CliFrontend.java:1126)
Caused by: java.util.concurrent.ExecutionException: org.apache.flink.runtime.rest.util.RestClientException: [Job termination (STOP) failed: This job is not stoppable.]
at java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
at java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1915)
at org.apache.flink.client.program.rest.RestClusterClient.stop(RestClusterClient.java:392)
at org.apache.flink.client.cli.CliFrontend.lambda$stop$5(CliFrontend.java:552)
... 9 more
Caused by: org.apache.flink.runtime.rest.util.RestClientException: [Job termination (STOP) failed: This job is not stoppable.]
at org.apache.flink.runtime.rest.RestClient.parseResponse(RestClient.java:380)
at org.apache.flink.runtime.rest.RestClient.lambda$submitRequest$3(RestClient.java:364)
at java.util.concurrent.CompletableFuture.uniCompose(CompletableFuture.java:952)
at java.util.concurrent.CompletableFuture$UniCompose.tryFire(CompletableFuture.java:926)
at java.util.concurrent.CompletableFuture$Completion.run(CompletableFuture.java:442)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)

从日志里面能看出 Stop 命令执行失败了。一个 Job 能够被 Stop 要求所有的 Source 都是可以 Stoppable 的,即实现了 StoppableFunction 接口。

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/**
* 需要能 stoppable 的函数必须实现这个接口,例如流式任务的 source。
* stop() 方法在任务收到 STOP 信号的时候调用。
* source 在接收到这个信号后,必须停止发送新的数据且优雅的停止。
*/
@PublicEvolving
public interface StoppableFunction {
/**
* 停止 source。与 cancel() 不同的是,这是一个让 source 优雅停止的请求。
* 等待中的数据可以继续发送出去,不需要立即停止。
*/
void stop();
}
Cancel

取消任务。如果在 conf/flink-conf.yaml 里面配置了 state.savepoints.dir,会保存 Savepoint,否则不会保存 Savepoint。

复制代码
➜ flink-1.7.2 bin/flink cancel -m 127.0.0.1:8081 5e20cb6b0f357591171dfcca2eea09de
Cancelling job 5e20cb6b0f357591171dfcca2eea09de.
Cancelled job 5e20cb6b0f357591171dfcca2eea09de.

也可以在停止的时候显示指定 Savepoint 目录。

复制代码
➜ flink-1.7.2 bin/flink cancel -m 127.0.0.1:8081 -s /tmp/savepoint 29da945b99dea6547c3fbafd57ed8759
Cancelling job 29da945b99dea6547c3fbafd57ed8759 with savepoint to /tmp/savepoint.
Cancelled job 29da945b99dea6547c3fbafd57ed8759. Savepoint stored in file:/tmp/savepoint/savepoint-29da94-88299bacafb7.
➜ flink-1.7.2 ll /tmp/savepoint/savepoint-29da94-88299bacafb7
total 32K
-rw-r--r-- 1 baoniu 29K Mar 24 10:33 _metadata

取消和停止(流作业)的区别如下:

  • cancel() 调用,立即调用作业算子的 cancel() 方法,以尽快取消它们。如果算子在接到 cancel() 调用后没有停止,Flink 将开始定期中断算子线程的执行,直到所有算子停止为止。
  • stop() 调用,是更优雅的停止正在运行流作业的方式。stop() 仅适用于 Source 实现了 StoppableFunction 接口的作业。当用户请求停止作业时,作业的所有 Source 都将接收 stop() 方法调用。直到所有 Source 正常关闭时,作业才会正常结束。这种方式,使作业正常处理完所有作业。
Savepoint

触发 Savepoint。

复制代码
➜ flink-1.7.2 bin/flink savepoint -m 127.0.0.1:8081 ec53edcfaeb96b2a5dadbfbe5ff62bbb /tmp/savepoint
Triggering savepoint for job ec53edcfaeb96b2a5dadbfbe5ff62bbb.
Waiting for response...
Savepoint completed. Path: file:/tmp/savepoint/savepoint-ec53ed-84b00ce500ee
You can resume your program from this savepoint with the run command.

说明:Savepoint 和 Checkpoint 的区别(详见文档):

  • Checkpoint 是增量做的,每次的时间较短,数据量较小,只要在程序里面启用后会自动触发,用户无须感知;Checkpoint 是作业 failover 的时候自动使用,不需要用户指定。
  • Savepoint 是全量做的,每次的时间较长,数据量较大,需要用户主动去触发。Savepoint 一般用于程序的版本更新(详见文档),Bug 修复,A/B Test 等场景,需要用户指定。

通过 -s 参数从指定的 Savepoint 启动:

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➜ flink-1.7.2 bin/flink run -d -s /tmp/savepoint/savepoint-f049ff-24ec0d3e0dc7 ./examples/streaming/TopSpeedWindowing.jar
Starting execution of program
Executing TopSpeedWindowing example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.

查看 JobManager 的日志,能够看到类似这样的 Log:

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2019-03-28 10:30:53,957 INFO org.apache.flink.runtime.checkpoint.CheckpointCoordinator
- Starting job 790d7b98db6f6af55d04aec1d773852d from savepoint /tmp/savepoint/savepoint-f049ff-24ec0d3e0dc7 ()
2019-03-28 10:30:53,959 INFO org.apache.flink.runtime.checkpoint.CheckpointCoordinator
- Reset the checkpoint ID of job 790d7b98db6f6af55d04aec1d773852d to 2.
2019-03-28 10:30:53,959 INFO org.apache.flink.runtime.checkpoint.CheckpointCoordinator
- Restoring job 790d7b98db6f6af55d04aec1d773852d from latest valid checkpoint: Checkpoint 1 @ 0 for 790d7b98db6f6af55d04aec1d773852d.
Modify

修改任务并行度。

为了方便演示,我们修改 conf/flink-conf.yaml 将 Task Slot 数从默认的 1 改为 4,并配置 Savepoint 目录。(Modify 参数后面接 -s 指定 Savepoint 路径当前版本可能有 Bug,提示无法识别)

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taskmanager.numberOfTaskSlots: 4
state.savepoints.dir: file:///tmp/savepoint

修改参数后需要重启集群生效,然后再启动任务:

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➜ flink-1.7.2 bin/stop-cluster.sh && bin/start-cluster.sh
Stopping taskexecutor daemon (pid: 53139) on host zkb-MBP.local.
Stopping standalonesession daemon (pid: 52723) on host zkb-MBP.local.
Starting cluster.
Starting standalonesession daemon on host zkb-MBP.local.
Starting taskexecutor daemon on host zkb-MBP.local.
➜ flink-1.7.2 bin/flink run -d examples/streaming/TopSpeedWindowing.jar
Starting execution of program
Executing TopSpeedWindowing example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
Job has been submitted with JobID 7752ea7b0e7303c780de9d86a5ded3fa

从页面上能看到 Task Slot 变为了 4,这时候任务的默认并发度是 1。

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

通过 Modify 命令依次将并发度修改为 4 和 3,可以看到每次 Modify 命令都会触发一次 Savepoint。

复制代码
➜ flink-1.7.2 bin/flink modify -p 4 7752ea7b0e7303c780de9d86a5ded3fa
Modify job 7752ea7b0e7303c780de9d86a5ded3fa.
Rescaled job 7752ea7b0e7303c780de9d86a5ded3fa. Its new parallelism is 4.
➜ flink-1.7.2 ll /tmp/savepoint
total 0
drwxr-xr-x 3 baoniu 96 Jun 17 09:05 savepoint-7752ea-00c05b015836/
➜ flink-1.7.2 bin/flink modify -p 3 7752ea7b0e7303c780de9d86a5ded3fa
Modify job 7752ea7b0e7303c780de9d86a5ded3fa.
Rescaled job 7752ea7b0e7303c780de9d86a5ded3fa. Its new parallelism is 3.
➜ flink-1.7.2 ll /tmp/savepoint
total 0
drwxr-xr-x 3 baoniu 96 Jun 17 09:08 savepoint-7752ea-449b131b2bd4/

Apache Flink零基础入门(四):客户端操作的5种模式

查看 JobManager 的日志,可以看到:

复制代码
2019-06-17 09:05:11,179 INFO org.apache.flink.runtime.checkpoint.CheckpointCoordinator - Starting job 7752ea7b0e7303c780de9d86a5ded3fa from savepoint file:/tmp/savepoint/savepoint-790d7b-3581698f007e ()
2019-06-17 09:05:11,182 INFO org.apache.flink.runtime.checkpoint.CheckpointCoordinator - Reset the checkpoint ID of job 7752ea7b0e7303c780de9d86a5ded3fa to 3.
2019-06-17 09:05:11,182 INFO org.apache.flink.runtime.checkpoint.CheckpointCoordinator - Restoring job 790d7b98db6f6af55d04aec1d773852d from latest valid checkpoint: Checkpoint 2 @ 0 for 7752ea7b0e7303c780de9d86a5ded3fa.
2019-06-17 09:05:11,184 INFO org.apache.flink.runtime.checkpoint.CheckpointCoordinator - No master state to restore
2019-06-17 09:05:11,184 INFO org.apache.flink.runtime.executiongraph.ExecutionGraph - Job CarTopSpeedWindowingExample (7752ea7b0e7303c780de9d86a5ded3fa) switched from state RUNNING to SUSPENDING.
org.apache.flink.util.FlinkException: Job is being rescaled.
Info

Info 命令是用来查看 Flink 任务的执行计划(StreamGraph)的。

复制代码
➜ flink-1.7.2 bin/flink info examples/streaming/TopSpeedWindowing.jar
----------------------- Execution Plan -----------------------
{"nodes":[{"id":1,"type":"Source: Custom Source","pact":"Data Source","contents":"Source: Custom Source","parallelism":1},{"id":2,"type":"Timestamps/Watermarks","pact":"Operator","contents":"Timestamps/Watermarks","parallelism":1,"predecessors":[{"id":1,"ship_strategy":"FORWARD","side":"second"}]},{"id":4,"type":"Window(GlobalWindows(), DeltaTrigger, TimeEvictor, ComparableAggregator, PassThroughWindowFunction)","pact":"Operator","contents":"Window(GlobalWindows(), DeltaTrigger, TimeEvictor, ComparableAggregator, PassThroughWindowFunction)","parallelism":1,"predecessors":[{"id":2,"ship_strategy":"HASH","side":"second"}]},{"id":5,"type":"Sink: Print to Std. Out","pact":"Data Sink","contents":"Sink: Print to Std. Out","parallelism":1,"predecessors":[{"id":4,"ship_strategy":"FORWARD","side":"second"}]}]}
--------------------------------------------------------------

拷贝输出的 Json 内容,粘贴到这个网站: http://flink.apache.org/visualizer/

Apache Flink零基础入门(四):客户端操作的5种模式

可以和实际运行的物理执行计划对比:

Apache Flink零基础入门(四):客户端操作的5种模式

2.1.2 Yarn per-job

单任务 Attach 模式

默认是 Attach 模式,即客户端会一直等待直到程序结束才会退出。

  • 通过 -m yarn-cluster 指定 Yarn 模式
  • Yarn 上显示名字为 Flink session cluster,这个 Batch 的 Wordcount 任务运行完会 FINISHED。
  • 客户端能看到结果输出
复制代码
[admin@z17.sqa.zth /home/admin/flink/flink-1.7.2]
$echo $HADOOP_CONF_DIR
/etc/hadoop/conf/
[admin@z17.sqa.zth /home/admin/flink/flink-1.7.2]
$./bin/flink run -m yarn-cluster ./examples/batch/WordCount.jar
2019-06-17 09:15:24,511 INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at z05c05217.sqa.zth.tbsite.net/11.163.188.29:8050
2019-06-17 09:15:24,690 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-06-17 09:15:24,690 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-06-17 09:15:24,907 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Cluster specification: ClusterSpecification{masterMemoryMB=1024, taskManagerMemoryMB=1024, numberTaskManagers=1, slotsPerTaskManager=4}
2019-06-17 09:15:25,430 WARN org.apache.hadoop.hdfs.shortcircuit.DomainSocketFactory - The short-circuit local reads feature cannot be used because libhadoop cannot be loaded.
2019-06-17 09:15:25,438 WARN org.apache.flink.yarn.AbstractYarnClusterDescriptor - The configuration directory ('/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/conf') contains both LOG4J and Logback configuration files. Please delete or rename one of them.
2019-06-17 09:15:36,239 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Submitting application master application_1532332183347_0724
2019-06-17 09:15:36,276 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl - Submitted application application_1532332183347_0724
2019-06-17 09:15:36,276 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Waiting for the cluster to be allocated
2019-06-17 09:15:36,281 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Deploying cluster, current state ACCEPTED
2019-06-17 09:15:40,426 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - YARN application has been deployed successfully.
Starting execution of program
Executing WordCount example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
(a,5)
(action,1)
(after,1)
(against,1)
(all,2)
... ...
(would,2)
(wrong,1)
(you,1)
Program execution finished
Job with JobID 8bfe7568cb5c3254af30cbbd9cd5971e has finished.
Job Runtime: 9371 ms
Accumulator Results:
- 2bed2c5506e9237fb85625416a1bc508 (java.util.ArrayList) [170 elements]

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

如果我们以 Attach 模式运行 Streaming 的任务,客户端会一直等待不退出,可以运行以下的例子试验下:

复制代码
./bin/flink run -m yarn-cluster ./examples/streaming/TopSpeedWindowing.jar
单任务 Detached 模式
  • 由于是 Detached 模式,客户端提交完任务就退出了
  • Yarn 上显示为 Flink per-job cluster
复制代码
$./bin/flink run -yd -m yarn-cluster ./examples/streaming/TopSpeedWindowing.jar
2019-06-18 09:21:59,247 INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at z05c05217.sqa.zth.tbsite.net/11.163.188.29:8050
2019-06-18 09:21:59,428 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-06-18 09:21:59,428 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-06-18 09:21:59,940 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Cluster specification: ClusterSpecification{masterMemoryMB=1024, taskManagerMemoryMB=1024, numberTaskManagers=1, slotsPerTaskManager=4}
2019-06-18 09:22:00,427 WARN org.apache.hadoop.hdfs.shortcircuit.DomainSocketFactory - The short-circuit local reads feature cannot be used because libhadoop cannot be loaded.
2019-06-18 09:22:00,436 WARN org.apache.flink.yarn.AbstractYarnClusterDescriptor - The configuration directory ('/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/conf') contains both LOG4J and Logback configuration files. Please delete or rename one of them.
^@2019-06-18 09:22:12,113 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Submitting application master application_1532332183347_0729
2019-06-18 09:22:12,151 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl - Submitted application application_1532332183347_0729
2019-06-18 09:22:12,151 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Waiting for the cluster to be allocated
2019-06-18 09:22:12,155 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Deploying cluster, current state ACCEPTED
2019-06-18 09:22:16,275 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - YARN application has been deployed successfully.
2019-06-18 09:22:16,275 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - The Flink YARN client has been started in detached mode. In order to stop Flink on YARN, use the following command or a YARN web interface to stop it:
yarn application -kill application_1532332183347_0729
Please also note that the temporary files of the YARN session in the home directory will not be removed.
Job has been submitted with JobID e61b9945c33c300906ad50a9a11f36df

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

2.1.3 Yarn session

启动 Session
复制代码
./bin/yarn-session.sh -tm 2048 -s 3

表示启动一个 Yarn session 集群,每个 TM 的内存是 2 G,每个 TM 有 3 个 Slot。(注意:-n 参数不生效)

复制代码
➜ flink-1.7.2 ./bin/yarn-session.sh -tm 2048 -s 3
2019-06-17 09:21:50,177 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.rpc.address, localhost
2019-06-17 09:21:50,179 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.rpc.port, 6123
2019-06-17 09:21:50,179 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.heap.size, 1024m
2019-06-17 09:21:50,179 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: taskmanager.heap.size, 1024m
2019-06-17 09:21:50,179 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: taskmanager.numberOfTaskSlots, 4
2019-06-17 09:21:50,179 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: state.savepoints.dir, file:///tmp/savepoint
2019-06-17 09:21:50,180 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: parallelism.default, 1
2019-06-17 09:21:50,180 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: rest.port, 8081
2019-06-17 09:21:50,644 WARN org.apache.hadoop.util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2019-06-17 09:21:50,746 INFO org.apache.flink.runtime.security.modules.HadoopModule - Hadoop user set to baoniu (auth:SIMPLE)
2019-06-17 09:21:50,848 INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at z05c05217.sqa.zth.tbsite.net/11.163.188.29:8050
2019-06-17 09:21:51,148 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Cluster specification: ClusterSpecification{masterMemoryMB=1024, taskManagerMemoryMB=2048, numberTaskManagers=1, slotsPerTaskManager=3}
2019-06-17 09:21:51,588 WARN org.apache.hadoop.hdfs.shortcircuit.DomainSocketFactory - The short-circuit local reads feature cannot be used because libhadoop cannot be loaded.
2019-06-17 09:21:51,596 WARN org.apache.flink.yarn.AbstractYarnClusterDescriptor - The configuration directory ('/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/conf') contains both LOG4J and Logback configuration files. Please delete or rename one of them.
^@2019-06-17 09:22:03,304 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Submitting application master application_1532332183347_0726
2019-06-17 09:22:03,336 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl - Submitted application application_1532332183347_0726
2019-06-17 09:22:03,336 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Waiting for the cluster to be allocated
2019-06-17 09:22:03,340 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Deploying cluster, current state ACCEPTED
2019-06-17 09:22:07,722 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - YARN application has been deployed successfully.
2019-06-17 09:22:08,050 INFO org.apache.flink.runtime.rest.RestClient - Rest client endpoint started.
Flink JobManager is now running on z07.sqa.net:37109 with leader id 00000000-0000-0000-0000-000000000000.
JobManager Web Interface: http://z07.sqa.net:37109

客户端默认是 Attach 模式,不会退出:

  • 可以 ctrl + c 退出,然后再通过 ./bin/yarn-session.sh -id application_1532332183347_0726 连上来;
  • 或者启动的时候用 -d 则为 detached 模式
    Yarn 上显示为 Flink session cluster;

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

  • 在本机的临时目录(有些机器是 /tmp 目录)下会生成一个文件:
复制代码
➜ flink-1.7.2 cat /var/folders/2b/r6d49pcs23z43b8fqsyz885c0000gn/T/.yarn-properties-baoniu
#Generated YARN properties file
#Mon Jun 17 09:22:08 CST 2019
parallelism=3
dynamicPropertiesString=
applicationID=application_1532332183347_0726
提交任务
复制代码
./bin/flink run ./examples/batch/WordCount.jar

将会根据 /tmp/.yarn-properties-admin 文件内容提交到了刚启动的 Session。

复制代码
➜ flink-1.7.2 ./bin/flink run ./examples/batch/WordCount.jar
2019-06-17 09:26:42,767 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - Found Yarn properties file under /var/folders/2b/r6d49pcs23z43b8fqsyz885c0000gn/T/.yarn-properties-baoniu.
2019-06-17 09:26:42,767 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - Found Yarn properties file under /var/folders/2b/r6d49pcs23z43b8fqsyz885c0000gn/T/.yarn-properties-baoniu.
2019-06-17 09:26:43,058 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - YARN properties set default parallelism to 3
2019-06-17 09:26:43,058 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - YARN properties set default parallelism to 3
YARN properties set default parallelism to 3
2019-06-17 09:26:43,097 INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at z05c05217.sqa.zth.tbsite.net/11.163.188.29:8050
2019-06-17 09:26:43,229 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-06-17 09:26:43,229 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-06-17 09:26:43,327 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Found application JobManager host name 'z05c07216.sqa.zth.tbsite.net' and port '37109' from supplied application id 'application_1532332183347_0726'
Starting execution of program
Executing WordCount example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
^@(a,5)
(action,1)
(after,1)
(against,1)
(all,2)
(and,12)
... ...
(wrong,1)
(you,1)
Program execution finished
Job with JobID ad9b0f1feed6d0bf6ba4e0f18b1e65ef has finished.
Job Runtime: 9152 ms
Accumulator Results:
- fd07c75d503d0d9a99e4f27dd153114c (java.util.ArrayList) [170 elements]

运行结束后 TM 的资源会释放。

Apache Flink零基础入门(四):客户端操作的5种模式

提交到指定的 Session

通过 -yid 参数来提交到指定的 Session。

复制代码
$./bin/flink run -d -p 30 -m yarn-cluster -yid application_1532332183347_0708 ./examples/streaming/TopSpeedWindowing.jar
2019-03-24 12:36:33,668 INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at z05c05217.sqa.zth.tbsite.net/11.163.188.29:8050
2019-03-24 12:36:33,773 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-03-24 12:36:33,773 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-03-24 12:36:33,837 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Found application JobManager host name 'z05c05218.sqa.zth.tbsite.net' and port '60783' from supplied application id 'application_1532332183347_0708'
Starting execution of program
Executing TopSpeedWindowing example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
Job has been submitted with JobID 58d5049ebbf28d515159f2f88563f5fd

Apache Flink零基础入门(四):客户端操作的5种模式

注: Blink 版本 的 Session 与 Flink 的 Session 的区别:

  • Flink 的 session -n 参数不生效,而且不会提前启动 TM;
  • Blink 的 session 可以通过 -n 指定启动多少个 TM,而且 TM 会提前起来;

2.2 Scala Shell

官方文档: https://ci.apache.org/projects/flink/flink-docs-release-1.7/ops/scala_shell.html

2.2.1 Deploy

Local
复制代码
$bin/start-scala-shell.sh local
Starting Flink Shell:
Starting local Flink cluster (host: localhost, port: 8081).
Connecting to Flink cluster (host: localhost, port: 8081).
... ...
scala>

任务运行说明:

  • Batch 任务内置了 benv 变量,通过 print() 将结果输出到控制台;
  • Streaming 任务内置了 senv 变量,通过 senv.execute(“job name”) 来提交任务,且 Datastream 的输出只有在 Local 模式下打印到控制台;
Remote

先启动一个 yarn session cluster:

复制代码
$./bin/yarn-session.sh -tm 2048 -s 3
2019-03-25 09:52:16,341 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.rpc.address, localhost
2019-03-25 09:52:16,342 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.rpc.port, 6123
2019-03-25 09:52:16,342 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.heap.size, 1024m
2019-03-25 09:52:16,343 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: taskmanager.heap.size, 1024m
2019-03-25 09:52:16,343 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: taskmanager.numberOfTaskSlots, 4
2019-03-25 09:52:16,343 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: parallelism.default, 1
2019-03-25 09:52:16,343 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: state.savepoints.dir, file:///tmp/savepoint
2019-03-25 09:52:16,343 INFO org.apache.flink.configuration.GlobalConfiguration
… ...
Flink JobManager is now running on z054.sqa.net:28665 with leader id 00000000-0000-0000-0000-000000000000.
JobManager Web Interface: http://z054.sqa.net:28665

启动 scala shell,连到 jm:

复制代码
$bin/start-scala-shell.sh remote z054.sqa.net 28665
Starting Flink Shell:
Connecting to Flink cluster (host: z054.sqa.net, port: 28665).
... ...
scala>
Yarn
复制代码
$./bin/start-scala-shell.sh yarn -n 2 -jm 1024 -s 2 -tm 1024 -nm flink-yarn
Starting Flink Shell:
2019-03-25 09:47:44,695 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.rpc.address, localhost
2019-03-25 09:47:44,697 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.rpc.port, 6123
2019-03-25 09:47:44,697 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: jobmanager.heap.size, 1024m
2019-03-25 09:47:44,697 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: taskmanager.heap.size, 1024m
2019-03-25 09:47:44,697 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: taskmanager.numberOfTaskSlots, 4
2019-03-25 09:47:44,698 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: parallelism.default, 1
2019-03-25 09:47:44,698 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: state.savepoints.dir, file:///tmp/savepoint
2019-03-25 09:47:44,698 INFO org.apache.flink.configuration.GlobalConfiguration - Loading configuration property: rest.port, 8081
2019-03-25 09:47:44,717 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - Found Yarn properties file under /tmp/.yarn-properties-admin.
2019-03-25 09:47:45,041 INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at z05c05217.sqa.zth.tbsite.net/11.163.188.29:8050
2019-03-25 09:47:45,098 WARN org.apache.hadoop.util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2019-03-25 09:47:45,266 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2019-03-25 09:47:45,275 INFO org.apache.flink.yarn.cli.FlinkYarnSessionCli - The argument yn is deprecated in will be ignored.
2019-03-25 09:47:45,357 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Cluster specification: ClusterSpecification{masterMemoryMB=1024, taskManagerMemoryMB=1024, numberTaskManagers=2, slotsPerTaskManager=2}
2019-03-25 09:47:45,711 WARN org.apache.hadoop.hdfs.shortcircuit.DomainSocketFactory - The short-circuit local reads feature cannot be used because libhadoop cannot be loaded.
2019-03-25 09:47:45,718 WARN org.apache.flink.yarn.AbstractYarnClusterDescriptor - The configuration directory ('/home/admin/flink/flink-1.7.2/conf') contains both LOG4J and Logback configuration files. Please delete or rename one of them.
2019-03-25 09:47:46,514 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Submitting application master application_1532332183347_0710
2019-03-25 09:47:46,534 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl - Submitted application application_1532332183347_0710
2019-03-25 09:47:46,534 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Waiting for the cluster to be allocated
2019-03-25 09:47:46,535 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - Deploying cluster, current state ACCEPTED
2019-03-25 09:47:51,051 INFO org.apache.flink.yarn.AbstractYarnClusterDescriptor - YARN application has been deployed successfully.
2019-03-25 09:47:51,222 INFO org.apache.flink.runtime.rest.RestClient - Rest client endpoint started.
Connecting to Flink cluster (host: 10.10.10.10, port: 56942).

Apache Flink零基础入门(四):客户端操作的5种模式

按 CTRL + C 退出 Shell 后,这个 Flink cluster 还会继续运行,不会退出。

2.2.2 Execute

DataSet
复制代码
➜ flink-1.7.2 bin/stop-cluster.sh
No taskexecutor daemon to stop on host zkb-MBP.local.
No standalonesession daemon to stop on host zkb-MBP.local.
➜ flink-1.7.2 bin/start-scala-shell.sh local
Starting Flink Shell:
Starting local Flink cluster (host: localhost, port: 8081).
Connecting to Flink cluster (host: localhost, port: 8081).
scala> val text = benv.fromElements("To be, or not to be,--that is the question:--")
text: org.apache.flink.api.scala.DataSet[String] = org.apache.flink.api.scala.DataSet@5b407336
scala> val counts = text.flatMap { _.toLowerCase.split("\\W+") }.map { (_, 1) }.groupBy(0).sum(1)
counts: org.apache.flink.api.scala.AggregateDataSet[(String, Int)] = org.apache.flink.api.scala.AggregateDataSet@6ee34fe4
scala> counts.print()
(be,2)
(is,1)
(not,1)
(or,1)
(question,1)
(that,1)
(the,1)
(to,2)

对 DataSet 任务来说,print() 会触发任务的执行。

Apache Flink零基础入门(四):客户端操作的5种模式

也可以将结果输出到文件(先删除 /tmp/out1,不然会报错同名文件已经存在),继续执行以下命令:

复制代码
scala> counts.writeAsText("/tmp/out1")
res1: org.apache.flink.api.java.operators.DataSink[(String, Int)] = DataSink '<unnamed>' (TextOutputFormat (/tmp/out1) - UTF-8)
scala> benv.execute("batch test")
res2: org.apache.flink.api.common.JobExecutionResult = org.apache.flink.api.common.JobExecutionResult@737652a9

查看 /tmp/out1 文件就能看到输出结果。

复制代码
➜ flink-1.7.2 cat /tmp/out1
(be,2)
(is,1)
(not,1)
(or,1)
(question,1)
(that,1)
(the,1)
(to,2)

Apache Flink零基础入门(四):客户端操作的5种模式

DataStream
复制代码
scala> val textStreaming = senv.fromElements("To be, or not to be,--that is the question:--")
textStreaming: org.apache.flink.streaming.api.scala.DataStream[String] = org.apache.flink.streaming.api.scala.DataStream@4970b93d
scala> val countsStreaming = textStreaming.flatMap { _.toLowerCase.split("\\W+") }.map { (_, 1) }.keyBy(0).sum(1)
countsStreaming: org.apache.flink.streaming.api.scala.DataStream[(String, Int)] = org.apache.flink.streaming.api.scala.DataStream@6a478680
scala> countsStreaming.print()
res3: org.apache.flink.streaming.api.datastream.DataStreamSink[(String, Int)] = org.apache.flink.streaming.api.datastream.DataStreamSink@42bfc11f
scala> senv.execute("Streaming Wordcount")
(to,1)
(be,1)
(or,1)
(not,1)
(to,2)
(be,2)
(that,1)
(is,1)
(the,1)
(question,1)
res4: org.apache.flink.api.common.JobExecutionResult = org.apache.flink.api.common.JobExecutionResult@1878815a

对 DataStream 任务,print() 并不会触发任务的执行,需要显示调用 execute(“job name”) 才会执行任务。

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

TableAPI

在 Blink 开源版本里面,支持了 TableAPI 方式提交任务(可以用 btenv.sqlQuery 提交 SQL 查询),社区版本 Flink 1.8 会支持 TableAPI: https://issues.apache.org/jira/browse/FLINK-9555

2.3 SQL Client Beta

SQL Client 目前还只是测试版,处于开发阶段,只能用于 SQL 的原型验证,不推荐在生产环境使用。

2.3.1 基本用法

复制代码
➜ flink-1.7.2 bin/start-cluster.sh
Starting cluster.
Starting standalonesession daemon on host zkb-MBP.local.
Starting taskexecutor daemon on host zkb-MBP.local.
➜ flink-1.7.2 ./bin/sql-client.sh embedded
No default environment specified.
Searching for '/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/conf/sql-client-defaults.yaml'...found.
Reading default environment from: file:/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/conf/sql-client-defaults.yaml
No session environment specified.
Validating current environment...done.
… …
Flink SQL> help;
The following commands are available:
QUIT Quits the SQL CLI client.
CLEAR Clears the current terminal.
HELP Prints the available commands.
SHOW TABLES Shows all registered tables.
SHOW FUNCTIONS Shows all registered user-defined functions.
DESCRIBE Describes the schema of a table with the given name.
EXPLAIN Describes the execution plan of a query or table with the given name.
SELECT Executes a SQL SELECT query on the Flink cluster.
INSERT INTO Inserts the results of a SQL SELECT query into a declared table sink.
CREATE VIEW Creates a virtual table from a SQL query. Syntax: 'CREATE VIEW <name> AS <query>;'
DROP VIEW Deletes a previously created virtual table. Syntax: 'DROP VIEW <name>;'
SOURCE Reads a SQL SELECT query from a file and executes it on the Flink cluster.
SET Sets a session configuration property. Syntax: 'SET <key>=<value>;'. Use 'SET;' for listing all properties.
RESET Resets all session configuration properties.
Hint: Make sure that a statement ends with ';' for finalizing (multi-line) statements.
Select 查询
复制代码
Flink SQL> SELECT 'Hello World';

Apache Flink零基础入门(四):客户端操作的5种模式

按 “Q” 退出这个界面

打开 http://127.0.0.1:8081 能看到这条 Select 语句产生的查询任务已经结束了。这个查询采用的是读取固定数据集的 Custom Source,输出用的是 Stream Collect Sink,且只输出一条结果。

注意:如果本机的临时目录存在类似 .yarn-properties-baoniu 的文件,任务会提交到 Yarn 上。

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

Explain

Explain 命令可以查看 SQL 的执行计划。

复制代码
Flink SQL> explain SELECT name, COUNT(*) AS cnt FROM (VALUES ('Bob'), ('Alice'), ('Greg'), ('Bob')) AS NameTable(name) GROUP BY name;
== Abstract Syntax Tree == // 抽象语法树
LogicalAggregate(group=[{0}], cnt=[COUNT()])
LogicalValues(tuples=[[{ _UTF-16LE'Bob ' }, { _UTF-16LE'Alice' }, { _UTF-16LE'Greg ' }, { _UTF-16LE'Bob ' }]])
== Optimized Logical Plan == // 优化后的逻辑执行计划
DataStreamGroupAggregate(groupBy=[name], select=[name, COUNT(*) AS cnt])
DataStreamValues(tuples=[[{ _UTF-16LE'Bob ' }, { _UTF-16LE'Alice' }, { _UTF-16LE'Greg ' }, { _UTF-16LE'Bob ' }]])
== Physical Execution Plan == // 物理执行计划
Stage 3 : Data Source
content : collect elements with CollectionInputFormat
Stage 5 : Operator
content : groupBy: (name), select: (name, COUNT(*) AS cnt)
ship_strategy : HASH

2.3.2 结果展示

SQL Client 支持两种模式来维护并展示查询结果:

  • table mode: 在内存中物化查询结果,并以分页 table 形式展示。用户可以通过以下命令启用 table mode;
复制代码
SET execution.result-mode=table
  • changlog mode: 不会物化查询结果,而是直接对 continuous query 产生的添加和撤回(retractions)结果进行展示。
复制代码
SET execution.result-mode=changelog

接下来通过实际的例子进行演示。

Table mode
复制代码
Flink SQL> SET execution.result-mode=table;
[INFO] Session property has been set.
Flink SQL> SELECT name, COUNT(*) AS cnt FROM (VALUES ('Bob'), ('Alice'), ('Greg'), ('Bob')) AS NameTable(name) GROUP BY name;

运行结果如下图所示:

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

Changlog mode
复制代码
Flink SQL> SET execution.result-mode=changelog;
[INFO] Session property has been set.
Flink SQL> SELECT name, COUNT(*) AS cnt FROM (VALUES ('Bob'), ('Alice'), ('Greg'), ('Bob')) AS NameTable(name) GROUP BY name;

运行结果如下图所示:

Apache Flink零基础入门(四):客户端操作的5种模式

其中 ‘-’ 代表的就是撤回消息。

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

2.3.3 Environment Files

目前的 SQL Client 还不支持 DDL 语句,只能通过 yaml 文件的方式来定义 SQL 查询需要的表,UDF 和运行参数等信息。

首先,准备 env.yaml 和 input.csv 两个文件。

复制代码
➜ flink-1.7.2 cat /tmp/env.yaml
tables:
- name: MyTableSource
type: source-table
update-mode: append
connector:
type: filesystem
path: "/tmp/input.csv"
format:
type: csv
fields:
- name: MyField1
type: INT
- name: MyField2
type: VARCHAR
line-delimiter: "\n"
comment-prefix: "#"
schema:
- name: MyField1
type: INT
- name: MyField2
type: VARCHAR
- name: MyCustomView
type: view
query: "SELECT MyField2 FROM MyTableSource"
- name: MyTableSink
type: sink-table
update-mode: append
connector:
type: filesystem
path: "/tmp/output.csv"
format:
type: csv
fields:
- name: MyField1
type: INT
- name: MyField2
type: VARCHAR
schema:
- name: MyField1
type: INT
- name: MyField2
type: VARCHAR
# Execution properties allow for changing the behavior of a table program.
execution:
type: streaming # required: execution mode either 'batch' or 'streaming'
result-mode: table # required: either 'table' or 'changelog'
max-table-result-rows: 1000000 # optional: maximum number of maintained rows in
# 'table' mode (1000000 by default, smaller 1 means unlimited)
time-characteristic: event-time # optional: 'processing-time' or 'event-time' (default)
parallelism: 1 # optional: Flink's parallelism (1 by default)
periodic-watermarks-interval: 200 # optional: interval for periodic watermarks (200 ms by default)
max-parallelism: 16 # optional: Flink's maximum parallelism (128 by default)
min-idle-state-retention: 0 # optional: table program's minimum idle state time
max-idle-state-retention: 0 # optional: table program's maximum idle state time
restart-strategy: # optional: restart strategy
type: fallback # "fallback" to global restart strategy by default
# Deployment properties allow for describing the cluster to which table programs are submitted to.
deployment:
response-timeout: 5000
➜ flink-1.7.2 cat /tmp/input.csv
1,hello
2,world
3,hello world
1,ok
3,bye bye
4,yes

启动 SQL Client:

复制代码
➜ flink-1.7.2 ./bin/sql-client.sh embedded -e /tmp/env.yaml
No default environment specified.
Searching for '/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/conf/sql-client-defaults.yaml'...found.
Reading default environment from: file:/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/conf/sql-client-defaults.yaml
Reading session environment from: file:/tmp/env.yaml
Validating current environment...done.
Flink SQL> show tables;
MyCustomView
MyTableSink
MyTableSource
Flink SQL> describe MyTableSource;
root
|-- MyField1: Integer
|-- MyField2: String
Flink SQL> describe MyCustomView;
root
|-- MyField2: String
Flink SQL> create view MyView1 as select MyField1 from MyTableSource;
[INFO] View has been created.
Flink SQL> show tables;
MyCustomView
MyTableSource
MyView1
Flink SQL> describe MyView1;
root
|-- MyField1: Integer
Flink SQL> select * from MyTableSource;

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

使用 insert into 写入结果表:

复制代码
Flink SQL> insert into MyTableSink select * from MyTableSource;
[INFO] Submitting SQL update statement to the cluster...
[INFO] Table update statement has been successfully submitted to the cluster:
Cluster ID: StandaloneClusterId
Job ID: 3fac2be1fd891e3e07595c684bb7b7a0
Web interface: http://localhost:8081

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

查询生成的结果数据文件:

复制代码
➜ flink-1.7.2 cat /tmp/output.csv
1,hello
2,world
3,hello world
1,ok
3,bye bye
4,yes

也可以在 Environment 文件里面定义 UDF,在 SQL Client 里面通过 「HOW FUNCTIONS」查询和使用,这里就不再说明了。

SQL Client 功能社区还在开发中,详见 FLIP-24

2.4 Restful API

接下来我们演示如何通过 Rest API 来提交 Jar 包和执行任务。

更详细的操作请参考 Flink 的 Restful API 文档: https://ci.apache.org/projects/flink/flink-docs-stable/monitoring/rest_api.html

复制代码
➜ flink-1.7.2 curl http://127.0.0.1:8081/overview
{"taskmanagers":1,"slots-total":4,"slots-available":0,"jobs-running":3,"jobs-finished":0,"jobs-cancelled":0,"jobs-failed":0,"flink-version":"1.7.2","flink-commit":"ceba8af"}%
➜ flink-1.7.2 curl -X POST -H "Expect:" -F "jarfile=@/Users/baoniu/Documents/work/tool/flink/flink-1.7.2/examples/streaming/TopSpeedWindowing.jar" http://127.0.0.1:8081/jars/upload
{"filename":"/var/folders/2b/r6d49pcs23z43b8fqsyz885c0000gn/T/flink-web-124c4895-cf08-4eec-8e15-8263d347efc2/flink-web-upload/6077eca7-6db0-4570-a4d0-4c3e05a5dc59_TopSpeedWindowing.jar","status":"success"}%
➜ flink-1.7.2 curl http://127.0.0.1:8081/jars
{"address":"http://localhost:8081","files":[{"id":"6077eca7-6db0-4570-a4d0-4c3e05a5dc59_TopSpeedWindowing.jar","name":"TopSpeedWindowing.jar","uploaded":1553743438000,"entry":[{"name":"org.apache.flink.streaming.examples.windowing.TopSpeedWindowing","description":null}]}]}%
➜ flink-1.7.2 curl http://127.0.0.1:8081/jars/6077eca7-6db0-4570-a4d0-4c3e05a5dc59_TopSpeedWindowing.jar/plan
{"plan":{"jid":"41029eb3feb9132619e454ec9b2a89fb","name":"CarTopSpeedWindowingExample","nodes":[{"id":"90bea66de1c231edf33913ecd54406c1","parallelism":1,"operator":"","operator_strategy":"","description":"Window(GlobalWindows(), DeltaTrigger, TimeEvictor, ComparableAggregator, PassThroughWindowFunction) -&gt; Sink: Print to Std. Out","inputs":[{"num":0,"id":"cbc357ccb763df2852fee8c4fc7d55f2","ship_strategy":"HASH","exchange":"pipelined_bounded"}],"optimizer_properties":{}},{"id":"cbc357ccb763df2852fee8c4fc7d55f2","parallelism":1,"operator":"","operator_strategy":"","description":"Source: Custom Source -&gt; Timestamps/Watermarks","optimizer_properties":{}}]}}% ➜ flink-1.7.2 curl -X POST http://127.0.0.1:8081/jars/6077eca7-6db0-4570-a4d0-4c3e05a5dc59_TopSpeedWindowing.jar/run
{"jobid":"04d80a24b076523d3dc5fbaa0ad5e1ad"}%

Apache Flink零基础入门(四):客户端操作的5种模式

Apache Flink零基础入门(四):客户端操作的5种模式

Restful API 还提供了很多监控和 Metrics 相关的功能,对于任务提交的操作也支持的比较全面。

2.5 Web

在 Flink Dashboard 页面左侧可以看到有个「Submit new Job」的地方,用户可以上传 Jar 包和显示执行计划和提交任务。Web 提交功能主要用于新手入门和演示用。

Apache Flink零基础入门(四):客户端操作的5种模式

3. 结语

本文主要讲解了 Flink 的 5 种任务提交的方式。熟练掌握各种任务提交方式,有利于提高我们日常的开发和运维效率。

视频回顾: https://www.bilibili.com/video/av47600600/?spm_id_from=333.788.videocard.5

更多干货内容参见 Apache Flink 零基础入门专题。

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