HoodieMetrics Guide

In this section, we will introduce the MetricsReporter and HoodieMetrics in Hudi. You can view the metrics-related configurations here.

MetricsReporter

MetricsReporter provides APIs for reporting HoodieMetrics to user-specified backends. Currently, the implementations include InMemoryMetricsReporter, JmxMetricsReporter, MetricsGraphiteReporter and DatadogMetricsReporter. Since InMemoryMetricsReporter is only used for testing, we will introduce the other three implementations.

JmxMetricsReporter

JmxMetricsReporter is an implementation of JMX reporter, which used to report JMX metrics.

Configurations

The following is an example of JmxMetricsReporter. More detaile configurations can be referenced here.

  hoodie.metrics.on=true
  hoodie.metrics.reporter.type=JMX
  hoodie.metrics.jmx.host=192.168.0.106
  hoodie.metrics.jmx.port=4001

Demo

As configured above, JmxMetricsReporter will started JMX server on port 4001. We can start a jconsole to connect to 192.168.0.106:4001. Below is an illustration of monitoring Hudi JMX metrics through jconsole.

hudi_jxm_metrics.png

MetricsGraphiteReporter

MetricsGraphiteReporter is an implementation of Graphite reporter, which connects to a Graphite server, and send HoodieMetrics to it.

Configurations

The following is an example of MetricsGraphiteReporter. More detaile configurations can be referenced here.

  hoodie.metrics.on=true
  hoodie.metrics.reporter.type=GRAPHITE
  hoodie.metrics.graphite.host=192.168.0.106
  hoodie.metrics.graphite.port=2003
  hoodie.metrics.graphite.metric.prefix=<your metrics prefix>

Demo

As configured above, assuming a Graphite server is running on host 192.168.0.106 and port 2003, a running Hudi job will connect and report metrics data to it. Below is an illustration of monitoring hudi metrics through Graphite.

hudi_graphite_metrics.png

DatadogMetricsReporter

DatadogMetricsReporter is an implementation of Datadog reporter. A reporter which publishes metric values to Datadog monitoring service via Datadog HTTP API.

Configurations

The following is an example of DatadogMetricsReporter. More detailed configurations can be referenced here.

hoodie.metrics.on=true
hoodie.metrics.reporter.type=DATADOG
hoodie.metrics.datadog.api.site=EU # or US
hoodie.metrics.datadog.api.key=<your api key>
hoodie.metrics.datadog.metric.prefix=<your metrics prefix>
  • hoodie.metrics.datadog.api.site will set the Datadog API site, which determines whether the requests will be sent to api.datadoghq.eu (EU) or api.datadoghq.com (US). Set this according to your Datadog account settings.
  • hoodie.metrics.datadog.api.key will set the api key.
  • hoodie.metrics.datadog.metric.prefix will help segregate metrics by setting different prefixes for different jobs. Note that it will use . to delimit the prefix and the metric name. For example, if the prefix is set to foo, then foo. will be prepended to the metric name.

Demo

In this demo, we ran a HoodieDeltaStreamer job with HoodieMetrics turned on and other configurations set properly.

hudi_datadog_metrics.png

As shown above, we were able to collect Hudi’s action-related metrics like

  • <prefix>.<table name>.commit.totalScanTime
  • <prefix>.<table name>.clean.duration
  • <prefix>.<table name>.index.lookup.duration

as well as HoodieDeltaStreamer-specific metrics

  • <prefix>.<table name>.deltastreamer.duration
  • <prefix>.<table name>.deltastreamer.hiveSyncDuration

UserDefinedMetricsReporter

Allows users to define a custom metrics reporter.

Configurations

The following is an example of UserDefinedMetricsReporter. More detailed configurations can be referenced here.

hoodie.metrics.on=true
hoodie.metrics.reporter.class=test.TestUserDefinedMetricsReporter

Demo

In this simple demo, TestMetricsReporter will print all gauges every 10 seconds

public static class TestUserDefinedMetricsReporter 
    extends AbstractUserDefinedMetricsReporter {
  private static final Logger log = LogManager.getLogger(DummyMetricsReporter.class);

  private ScheduledExecutorService exec = Executors.newScheduledThreadPool(1, r -> {
      Thread t = Executors.defaultThreadFactory().newThread(r);
      t.setDaemon(true);
      return t;
  });

  public TestUserDefinedMetricsReporter(Properties props, MetricRegistry registry) {
    super(props, registry);
  }

  @Override
  public void start() {
    exec.schedule(this::report, 10, TimeUnit.SECONDS);
  }

  @Override
  public void report() {
    this.getRegistry().getGauges().forEach((key, value) -> 
      log.info("key: " + key + " value: " + value.getValue().toString()));
  }

  @Override
  public Closeable getReporter() {
    return null;
  }

  @Override
  public void stop() {
    exec.shutdown();
  }
}

HoodieMetrics

Once the Hudi writer is configured with the right table and environment for HoodieMetrics, it produces the following HoodieMetrics, that aid in debugging hudi tables

  • Commit Duration - The amount of time it took to successfully commit a batch of records
  • Rollback Duration - Similarly, the amount of time taken to undo partial data left over by a failed commit (rollback happens automatically after a failing write)
  • File Level metrics - Shows the amount of new files added, versions, deleted (cleaned) in each commit
  • Record Level Metrics - Total records inserted/updated etc per commit
  • Partition Level metrics - number of partitions upserted (super useful to understand sudden spikes in commit duration)

These HoodieMetrics can then be plotted on a standard tool like grafana. Below is a sample commit duration chart.

hudi_commit_duration.png
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