Cloud Dataproc V1 API - Class Google::Cloud::Dataproc::V1::DataprocMetricConfig::Metric (v0.14.0)

Reference documentation and code samples for the Cloud Dataproc V1 API class Google::Cloud::Dataproc::V1::DataprocMetricConfig::Metric.

A Dataproc OSS metric.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#metric_overrides

def metric_overrides() -> ::Array<::String>
Returns
  • (::Array<::String>) —

    Optional. Specify one or more available OSS metrics to collect for the metric course (for the SPARK metric source, any Spark metric 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 will be collected for the metric source. For example, if one or more spark:executive metrics are listed as metric overrides, other SPARK metrics will not be collected. The collection of the default metrics for other OSS metric sources is unaffected. For example, if both SPARK andd YARN metric sources are enabled, and overrides are provided for Spark metrics only, all default YARN metrics will be collected.

#metric_overrides=

def metric_overrides=(value) -> ::Array<::String>
Parameter
  • value (::Array<::String>) —

    Optional. Specify one or more available OSS metrics to collect for the metric course (for the SPARK metric source, any Spark metric 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 will be collected for the metric source. For example, if one or more spark:executive metrics are listed as metric overrides, other SPARK metrics will not be collected. The collection of the default metrics for other OSS metric sources is unaffected. For example, if both SPARK andd YARN metric sources are enabled, and overrides are provided for Spark metrics only, all default YARN metrics will be collected.
Returns
  • (::Array<::String>) —

    Optional. Specify one or more available OSS metrics to collect for the metric course (for the SPARK metric source, any Spark metric 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 will be collected for the metric source. For example, if one or more spark:executive metrics are listed as metric overrides, other SPARK metrics will not be collected. The collection of the default metrics for other OSS metric sources is unaffected. For example, if both SPARK andd YARN metric sources are enabled, and overrides are provided for Spark metrics only, all default YARN metrics will be collected.

#metric_source

def metric_source() -> ::Google::Cloud::Dataproc::V1::DataprocMetricConfig::MetricSource
Returns

#metric_source=

def metric_source=(value) -> ::Google::Cloud::Dataproc::V1::DataprocMetricConfig::MetricSource
Parameter
Returns