【Flink Rest-ful API 】

Flink 有了一些查询job状态指标的API,这些监控 API is a REST-ful API 接受 HTTP 请求并返回JSON data ；这些监控API以jobManager中web server 为基础，默认其监听端口为8081，当然你可以在flink-conf.yaml 配置中通过 rest.port 自定义其端口，下面我们就对其REST-ful API 进行尝试。

一： Flink 上传JAR包REST-ful API

请求方式：POST

请求路径：http://localhost:8081/jar/upload

请求头： application/x-java-archive

POST  http://localhost:8081/jars/upload
说明 The jar must be sent as multi-part data. Make sure that the "Content-Type" header is set to "application/x-java-archive"
另外一个方式，可以尝试用下面请求提交jar包curl -X POST --header "Except:" -F "jarfile=@/home/opt/dbappLot-flink-1.0-SNAPSHOT-jar-with-dependencies.jar" http://localhost:8081/jars/upload其返回值：
{"filename":"/tmp/flink-web-26298886-4da6-4bf4-b635-fa301dee092e/flink-web-upload/82ea69b3-27c5-469d-992a-82be8c3d929d_dbappLot-flink-1.0-SNAPSHOT-jar-with-dependencies.jar","status":"success"}
其中filename 为存在地址
其中82ea69b3-27c5-469d-992a-82be8c3d929d_dbappLot-flink-1.0-SNAPSHOT-jar-with-dependencies.jar  为jarid

二：查看JAR包ID REST-ful API

请求   GET  http://localhost:8081/jars
返回值：
{"address": "http://localhost:8081","files": [{"id": "82ea69b3-27c5-469d-992a-82be8c3d929d_dbappLot-flink-1.0-SNAPSHOT-jar-with-dependencies.jar","name": "dbappLot-flink-1.0-SNAPSHOT-jar-with-dependencies.jar","uploaded": 1617180292000,"entry": [{"name": "com.dbapp.main.ApplicationMain","description": null}]}]
}

三：启动JOB REST-ful API

请求方式：POST

请求路径：http://localhost:8081/jar/{jarId}/run

请求   POST  http://localhost:8081/jars/82ea69b3-27c5-469d-992a-82be8c3d929d_dbappLot-flink-1.0-SNAPSHOT-jar-with-dependencies.jar/run
在请求中可以带上参数
allowNonRestoredState (optional): Boolean value that specifies whether the job submission should be rejected if the savepoint contains state that cannot be mapped back to the job.
savepointPath (optional): String value that specifies the path of the savepoint to restore the job from.
programArg (optional): Comma-separated list of program arguments.
entry-class (optional): String value that specifies the fully qualified name of the entry point class. Overrides the class defined in the jar file manifest.
parallelism (optional): Positive integer value that specifies the desired parallelism for the job.POST  http://localhost:8081/jars/82ea69b3-27c5-469d-992a-82be8c3d929d_dbappLot-flink-1.0-SNAPSHOT-jar-with-dependencies.jar/run? parallelism =21、http://192.168.196.3:8081/jars/a9ffd519-5222-40aa-9228-22464417a055_examples-java-1.0.jar/run?entry-class=io.github.streamingwithflink.demo.BatchCountFromJdbc&programArgsList=--bootstrap.servers hadoop2.test.yunwei.puppet.dh:6667,hadoop3.test.yunwei.puppet.dh:6667,hadoop4.test.yunwei.puppet.dh:6667 --group.id m3gcn_tab_map_race_3 --client.id m3gcn_tab_map_race_3 --config.file hdfs://DHTestCluster/user/gezhihui/flink/configuration/m3gcn_tab_map_race2.txt --job.name m3gcn_tab_map_race
2、http://localhost:8081/jars/java-3.0.jar/run
{"entryClass":"streamingwithflink.ApplicationMain""programArgsList": ["--name","wen"]
}请求体中的programArgsList可以传值到main函数的string[]args，取值可以通过ParameterTool parameters =
ParameterTool.fromArgs(args);String name = parameters.get("name");所以他的key-value的格式是key为"--key"或者"-key",
value为key的下一行，根据上述代码，value不要以"-"作为开头，这里也可以自己去解析String[]，这里args就对应我们programArgsList
的传参，如3所示3、http://localhost:8081/jars/java-2.0.jar/run
{"entryClass":"streamingwithflink.ApplicationMain""programArgsList": ["--name","wen"]}

其放回值为：

{
"jobid": "c18ac90bea03abcbc117a85a1080ba3b"
}

四：查看 JOB REST-ful API

请求方式：GET

请求路径：http://localhost:8081/jobs

返回值：{"jobs":[{"id":"c18ac90bea03abcbc117a85a1080ba3b","status":"RUNNING"},{"id":"43948e17785acc47deb6344d9165c6b3","status":"CANCELED"}]}

五：获取JOB详细信息 REST-ful API

请求方式：GET

请求路径：http://localhost:8081/jobs/{jobId}

返回值：

{"jid": "c18ac90bea03abcbc117a85a1080ba3b","name": "jobName","isStoppable": false,"state": "RUNNING","start-time": 1617189444432,"end-time": -1,"duration": 374118,"now": 1617189818550,"timestamps": {"RESTARTING": 0,"FINISHED": 0,"CANCELED": 0,"FAILING": 0,"RECONCILING": 0,"RUNNING": 1617189444440,"SUSPENDED": 0,"FAILED": 0,"CANCELLING": 0,"CREATED": 1617189444432},"vertices": [{"id": "cbc357ccb763df2852fee8c4fc7d55f2","name": "Source: dbappLot_kafkaSource -> flattenJson -> avitorMap -> schemaMap -> unFlattenJson -> (Sink: Print to Std. Out, Sink: KafkaSink)","parallelism": 1,"status": "RUNNING","start-time": 1617189444517,"end-time": -1,"duration": 374033,"tasks": {"CANCELED": 0,"SCHEDULED": 0,"RUNNING": 1,"FINISHED": 0,"RECONCILING": 0,"CREATED": 0,"FAILED": 0,"DEPLOYING": 0,"CANCELING": 0},"metrics": {"read-bytes": 0,"read-bytes-complete": false,"write-bytes": 0,"write-bytes-complete": false,"read-records": 0,"read-records-complete": false,"write-records": 0,"write-records-complete": false}}],"status-counts": {"CANCELED": 0,"SCHEDULED": 0,"RUNNING": 1,"FINISHED": 0,"RECONCILING": 0,"CREATED": 0,"FAILED": 0,"DEPLOYING": 0,"CANCELING": 0},"plan": {"jid": "c18ac90bea03abcbc117a85a1080ba3b","name": "jobName","nodes": [{"id": "cbc357ccb763df2852fee8c4fc7d55f2","parallelism": 1,"operator": "","operator_strategy": "","description": "Source: dbappLot_kafkaSource -&gt; flattenJson -&gt; avitorMap -&gt; schemaMap -&gt; unFlattenJson -&gt; (Sink: Print to Std. Out, Sink: KafkaSink)","optimizer_properties": {}}]}
}

六：关闭JOB REST-ful API

请求方式：PATCH

请求路径：http://localhost:8081/jobs/{jobId}

返回值：

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