Java Flink WebUI中不提供Apache波束计数器/度量

我正在使用Flink 1.4.1和Beam 2.3.0，我想知道在Flink WebUI（或任何地方）中是否可以像在Dataflow WebUI中一样使用度量

我使用了计数器，例如：

import org.apache.beam.sdk.metrics.Counter;
import org.apache.beam.sdk.metrics.Metrics;
...
Counter elementsRead = Metrics.counter(getClass(), "elements_read");
...
elementsRead.inc();

---

但我在Flink WebUI中找不到可用的

“元素读取”

计数（任务度量或累加器）。我认为这将很简单。

一旦您在仪表板中选择了一个作业，您将看到该作业的DAG，DAG下面有一个选项卡列表

单击“任务度量”选项卡

单击DAG的一个框

单击“添加度量”按钮，以显示该运算符度量

---

如果管道以分离模式运行，则不支持查询指标。参考

但是，我可以使用slf4j查看指标

---

我可以在累加器选项卡中看到度量，但在度量选项卡中看不到。。我使用的是Flink版本：1.12.0。。使用最新的Apache Beam Master分支代码..

尝试过，但没有成功。我的计数器不在指标列表中。您是如何创建波束计数器/指标的？哼。。。你能在累加器选项卡上看到你的计数器吗？@robosoul，有什么进展吗？我也面临着同样的问题：我所能看到的只是标准指标，而没有我自定义指标的迹象。@diegoreico。。我可以在累加器选项卡中看到度量，但在度量选项卡中看不到。。我使用的是Flink版本：1.12.0。。使用最新的Apache Beam Master分支代码..@zorro，您如何使用slf4j reporter查看指标？

public class FlinkDetachedRunnerResult implements PipelineResult {

  FlinkDetachedRunnerResult() {}

  @Override
  public State getState() {
    return State.UNKNOWN;
  }

  @Override
  public MetricResults metrics() {
    throw new UnsupportedOperationException("The FlinkRunner does not currently support metrics.");
  }

  @Override
  public State cancel() throws IOException {
    throw new UnsupportedOperationException("Cancelling is not yet supported.");
  }

  @Override
  public State waitUntilFinish() {
    return State.UNKNOWN;
  }

  @Override
  public State waitUntilFinish(Duration duration) {
    return State.UNKNOWN;
  }

  @Override
  public String toString() {
    return "FlinkDetachedRunnerResult{}";
  }
}

from apache_beam.metrics.metric import Metrics
from apache_beam.metrics.metric import MetricsFilter
from apache_beam.options.pipeline_options import PipelineOptions
import apache_beam as beam
import csv
import logging

GAME_DATA = [
'user1_team1,team1,18,1447686663000,2015-11-16 15:11:03.921',
'user1_team1,team1,18,1447690263000,2015-11-16 16:11:03.921',
'user2_team2,team2,2,1447690263000,2015-11-16 16:11:03.955',
'user3_team3,team3,8,1447690263000,2015-11-16 16:11:03.955',
'user4_team3,team3,5,1447690263000,2015-11-16 16:11:03.959',
'user1_team1,team1,14,1447697463000,2015-11-16 18:11:03.955',
'robot1_team1,team1,9000,1447697463000,2015-11-16 18:11:03.955',
'robot2_team2,team2,1,1447697463000,2015-11-16 20:11:03.955',
'robot2_team2,team2,9000,1447697463000,2015-11-16 21:11:03.955',
'robot1_team1,1000,2447697463000,2915-11-16 21:11:03.955',
'robot2_team2,9000,1447697463000,2015-11-16 21:11:03.955']

class ParseGameEventFn(beam.DoFn):
    def __init__(self):
        super(ParseGameEventFn, self).__init__()
    self.game_events = Metrics.counter(self.__class__, 'game_events')

    def process(self, element, *args, **kwargs):
        try:
            self.game_events.inc()
            row = list(csv.reader([element]))[0]
            if int(row[2]) < 5:
               return
            yield {
                'user': row[0],
                'team': row[1],
                'score': int(row[2]),
                'timestamp': int(row[3]) / 1000.0,
            }
        except Exception as ex:
            logging.error('Parse error on {}: {}'.format(element, ex))

with beam.Pipeline(options=pipeline_options) as pipeline:
    results = (
        pipeline
        | "Create" >> beam.Create(GAME_DATA)
        | "Parsing" >> beam.ParDo(ParseGameEventFn())
        | "AddEventTimestamps" >> beam.Map(
             lambda elem: beam.window.TimestampedValue(elem, elem['timestamp']))
        | "Print" >> beam.Map(print))

metric_results = pipeline.result.metrics().query(MetricsFilter().with_name('game_events'))
outputs_user_counter = metric_results['counters'][0]
print(outputs_user_counter.committed)

metrics.reporters: prom
metrics.reporter.prom.class: org.apache.flink.metrics.prometheus.PrometheusReporter
metrics.reporter.prom.port: 9250-9260