import org.opensearch.search.aggregations.metrics.PercentilesAggregationBuilder;
import org.opensearch.search.aggregations.metrics.ScriptedMetricAggregationBuilder;
import org.opensearch.search.aggregations.metrics.StatsAggregationBuilder;
import org.opensearch.search.aggregations.metrics.SumAggregationBuilder;
import org.opensearch.search.aggregations.metrics.TopHitsAggregationBuilder;
import org.opensearch.search.aggregations.metrics.ValueCountAggregationBuilder;

	logger.LogOnceIf(ctx, "etcd", err, id, errKind...)
}

func metricsLogIf(ctx context.Context, err error, errKind ...interface{}) {
	logger.LogIf(ctx, "metrics", err, errKind...)
}

func s3LogIf(ctx context.Context, err error, errKind ...interface{}) {
	logger.LogIf(ctx, "s3", err, errKind...)
}

  - Applications that fetch metrics from kube-scheduler should use a dedicated service account which is allowed to access nonResourceURLs `/metrics`. ([#96345](https://github.com/kubernetes/kubernetes/pull/96345), [@ingvagabund](https://github.com/ingvagabund)) [SIG Cloud Provider, Scheduling and Testing]

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

            if (this.endDate == null) return;

            this.calculateChosenLabel();
        },

        renderCalendar: function(side) {

            //
            // Build the matrix of dates that will populate the calendar
            //

            var calendar = side == 'left' ? this.leftCalendar : this.rightCalendar;
            var month = calendar.month.month();

 * Stopwatch} requires object allocation and additional method calls, which can reduce the accuracy
 * of the elapsed times reported. {@code Stopwatch} is still suitable for logging and metrics where
 * reasonably accurate values are sufficient. If the uncommon case that you need to maximize
 * accuracy, use {@code System.nanoTime()} directly instead.
 *
 * <p>Basic usage:
 *
 * <pre>{@code

    assertEquals(int[].class, arrayOf(int.class).getRawType());
  }

  @SuppressWarnings("unused") // used by reflection
  private static class Holder<T> {
    List<T>[] matrix;

    void setList(List<T> list) {}
  }

  public void testWildcardCaptured_methodParameter_upperBound() throws Exception {
    TypeToken<Holder<?>> type = new TypeToken<Holder<?>>() {};

2021602 E BX46 Parkchester 3709 2106 284 2 Bronx 028400 2028400 E BX37 Van Nest-Morris Park-Westchester Square 3704 3389497 2 2014-03-15 16:46:28 2014-03-15 16:54:39 N 1 -73.860969543457031 40.833728790283203 -73.851020812988281 40.850376129150391 1 1.76 8.5 0 0.5 3 0 12 1 1 182 242 green 0.00 0.0 0.0 58 42 8.95 1306 216.02 2 Bronx 021602 2021602 E BX46 Parkchester 3709 486 286 2 Bronx 028600 2028600 I BX37 Van Nest-Morris Park-Westchester Square 3704 3389498 2 2014-03-03 21:23:08 2014-03-03 21:34:43...

- Metrics server nanny has now poll period set to 30s (previously 5 minutes) to allow faster scaling of metrics server. ([#101869](https://github.com/kubernetes/kubernetes/pull/101869), [@olagacek](https://github.com/olagacek)) [SIG Cloud Provider and Instrumentation]

AAW,UAAY,GAC/B,CAAE,UAAW,OAAQxY,GAAOwY,UAAW,eACtCxY,GAAOwY,UAAW,eAAiB,EAAG,YACvC,CAAE,SAAU,OAAQxY,GAAOwY,UAAW,eACrCxY,GAAOwY,UAAW,eAAiB,EAAG,aAExCqB,EAAQ,UACRxB,EAAU,CACTwB,MAAO,WACN,OAAOA,GAERC,OAAQ,WAEP,OADAC,EAASlT,KAAMpF,WAAY6W,KAAM7W,WAC1B1E,MAERid,QAAS,SAAU7Z,GAClB,OAAOkY,EAAQE,KAAM,KAAMpY,IAI5B8Z,KAAM,WACL,IAAIC,EAAMzY,UAEV,OAAOzB,GAAO0Z,SAAU,SAAUS,GACjCna,GAAOsB,KAAMsY,EAAQ,SAAUzU,EAAIiV,GAGlC,IAAIja,EAAK/B,EAAY8b,EAAKE,EAAO,MAAWF,EAAKE,EAAO,IAKxDL,EAAUK,EAAO,IAAO,WACvB,IAAIC,EAAWla,GAAM...