das Programm nun Dinge in den Arbeitsspeicher lädt, zum Beispiel ein Modell für maschinelles Lernen in einer Variablen oder den Inhalt einer großen Datei in einer Variablen, verbraucht das alles **einen Teil des Arbeitsspeichers (RAM – Random Access Memory)** des Servers.

Und mehrere Prozesse teilen sich normalerweise keinen Speicher. Das bedeutet, dass jeder laufende Prozess seine eigenen Dinge, eigenen Variablen und eigenen Speicher hat. Und wenn Sie in Ihrem Code viel Speicher verbrauchen,...

- Fix memory leak in the job controller related to JobTrackingWithFinalizers ([#111723](https://github.com/kubernetes/kubernetes/pull/111723), [@alculquicondor](https://github.com/alculquicondor)) [SIG Apps]

      represent, as a whole, an original work of authorship. For the purposes
      of this License, Derivative Works shall not include works that remain
      separable from, or merely link (or bind by name) to the interfaces of,
      the Work and Derivative Works thereof.

      "Contribution" shall mean any work of authorship, including

	ctx := logger.SetReqInfo(GlobalContext, reqInfo)
	peersLogOnceIf(ctx, err, "add-node-err-"+addr)
	nodeInfo.SetAddr(addr)
	nodeInfo.SetError(err.Error())
}

// GetSysErrors - Memory information
func (sys *NotificationSys) GetSysErrors(ctx context.Context) []madmin.SysErrors {
	reply := make([]madmin.SysErrors, len(sys.peerClients))

	g := errgroup.WithNErrs(len(sys.peerClients))

      }
    }
  }

  @GwtIncompatible // DoubleMath.roundToLong(double, RoundingMode)
  public void testRoundExactIntegralDoubleToLong() {
    for (double d : INTEGRAL_DOUBLE_CANDIDATES) {
      // every mode except UNNECESSARY
      BigDecimal expected = new BigDecimal(d).setScale(0, UNNECESSARY);
      boolean isInBounds =
          expected.compareTo(MAX_LONG_AS_BIG_DECIMAL) <= 0

     of any Contributor. You must make it absolutely clear that any such
     warranty, support, indemnity, or liability obligation is offered by You
     alone, and You hereby agree to indemnify every Contributor for any
     liability incurred by such Contributor as a result of warranty, support,
     indemnity or liability terms You offer. You may include additional

     behalf of any Contributor. You must make it absolutely clear that any
     such warranty, support, indemnity, or liability obligation is offered by
     You alone, and You hereby agree to indemnify every Contributor for any
     liability incurred by such Contributor as a result of warranty, support,
     indemnity or liability terms You offer. You may include additional

introduced significant changes to its garbage collection algorithm. As a result, we observed an increase in memory usage for kube-apiserver in larger an heavily loaded clusters up to ~25% (with the benefit of API call latencies drop by up to 10x on 99th percentiles). If the memory increase is not acceptable for you you can mitigate by setting GOGC env variable (for our tests using GOGC=63 brings memory usage back to original value, although the exact value may depend on usage patterns on your cluster)....

         *
         * We carry out this computation in modular arithmetic. Since times2ToThe32Mod accepts any
         * unsigned long, we don't have to do a mod on every operation, only when intermediate
         * results can exceed 2^63.
         */
        long result = times2ToThe32Mod(aHi * bHi /* < 2^62 */, m); // < m < 2^63

limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/c_api_experimental.h"

#include <cstdint>
#include <memory>
#include <utility>
#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/strings/match.h"
#include "absl/time/time.h"
#include "tensorflow/c/c_api.h"