Metric(mapping=None, *, ignore_unknown_fields=False, **kwargs)A Dataproc custom metric.
Attributes | |
|---|---|
| Name | Description |
metric_source |
google.cloud.dataproc_v1.types.DataprocMetricConfig.MetricSource
Required. A standard set of metrics is collected unless metricOverrides are specified for the metric source (see
[Custom metrics]
(https://cloud.google.com/dataproc/docs/guides/dataproc-metrics#custom_metrics)
for more information).
|
metric_overrides |
MutableSequence[str]
Optional. Specify one or more [Custom metrics] (https://cloud.google.com/dataproc/docs/guides/dataproc-metrics#custom_metrics) to collect for the metric course (for the SPARK metric
source (any [Spark metric]
(https://spark.apache.org/docs/latest/monitoring.html#metrics)
can be specified).
Provide metrics in the following format:
METRIC_SOURCE:INSTANCE:GROUP:METRIC Use camelcase as
appropriate.
Examples:
::
yarn:ResourceManager:QueueMetrics:AppsCompleted
spark:driver:DAGScheduler:job.allJobs
sparkHistoryServer:JVM:Memory:NonHeapMemoryUsage.committed
hiveserver2:JVM:Memory:NonHeapMemoryUsage.used
Notes:
- Only the specified overridden metrics are collected for
the metric source. For example, if one or more
spark:executive metrics are listed as metric
overrides, other SPARK metrics are not collected. The
collection of the metrics for other enabled custom metric
sources is unaffected. For example, if both SPARK
andd YARN metric sources are enabled, and overrides
are provided for Spark metrics only, all YARN metrics are
collected.
|