// pod-1, etc) and the controller will wait until each pod is ready before
  // continuing. When scaling down, the pods are removed in the opposite order.
  // The alternative policy is `Parallel` which will create pods in parallel
  // to match the desired scale without waiting, and on scale down will delete
  // all pods at once.
  // +optional
  optional string podManagementPolicy = 6;

		if errors.Is(err, errDriveIsRoot) {
			// This is a root drive, ignore and move on
			return nil
		}
		if !errors.Is(err, errUnformattedDisk) {
			return err
		}
	}

	// Prevent parallel erasure set healing
	locker := z.NewNSLock(minioMetaBucket, fmt.Sprintf("new-drive-healing/%d/%d", poolIdx, setIdx))
	lkctx, err := locker.GetLock(ctx, newDiskHealingTimeout)
	if err != nil {

    ```

    **Note:** You can add `--test_sharding_strategy=disabled` to the `flags` to
    disable the sharding so that all the test outputs are in one file. However,
    it may slow down the tests for not running in parallel and may cause the
    test to timeout but it could be useful when you need to execute a single
    test or more in general your filtered/selected tests have a very low
    execution time and the sharding

			[]string{"hello", "dir/bar", "readonly"},
		},
		{
			"testdata/subdir.zip",
			[]string{"a/b/c"},
		},
	} {
		test := test
		t.Run(test.file, func(t *testing.T) {
			t.Parallel()
			z, err := OpenReader(test.file)
			if err != nil {
				t.Fatal(err)
			}
			defer z.Close()
			if err := fstest.TestFS(z, test.want...); err != nil {
				t.Error(err)
			}
		})
	}

    multipartBody.writeTo(Buffer())
    val mixed: MediaType = MultipartBody.MIXED
    val alternative: MediaType = MultipartBody.ALTERNATIVE
    val digest: MediaType = MultipartBody.DIGEST
    val parallel: MediaType = MultipartBody.PARALLEL
    val form: MediaType = MultipartBody.FORM
  }

  @Test
  fun multipartBodyPart() {
    val requestBody: RequestBody = "".toRequestBody(null)

   *
   * <p><b>Performance note:</b> The resulting stream is not <a
   * href="http://gee.cs.oswego.edu/dl/html/StreamParallelGuidance.html">efficiently splittable</a>.
   * This may harm parallel performance.
   */
  @Beta
  public static <A extends @Nullable Object, B extends @Nullable Object, R extends @Nullable Object>
      Stream<R> zip(

        }
        final Deque<ActivationFrame> stk = new LinkedList<>();

        final Supplier<String> pathSupplier = () -> {
            final boolean parallel = false;
            return StreamSupport.stream(((Iterable<ActivationFrame>) stk::descendingIterator).spliterator(), parallel)
                    .map(ActivationFrame::location)
                    .collect(Collectors.joining("."));
        };

  /**
   * Returns all locations that {@code classloader} and parent loaders load classes and resources
   * from. Callers can {@linkplain LocationInfo#scanResources scan} individual locations selectively
   * or even in parallel.
   */
  static ImmutableSet<LocationInfo> locationsFrom(ClassLoader classloader) {
    ImmutableSet.Builder<LocationInfo> builder = ImmutableSet.builder();

}

// BenchmarkPutObject50MbErasure - Benchmark Erasure.PutObject() for object size of 50MB.
func BenchmarkPutObject50MbErasure(b *testing.B) {
	benchmarkPutObject(b, "Erasure", 50*humanize.MiByte)
}

// parallel benchmarks for ObjectLayer.PutObject() .

// BenchmarkParallelPutObjectVerySmallFS - BenchmarkParallel FS.PutObject() for object size of 10 bytes.
func BenchmarkParallelPutObjectVerySmallFS(b *testing.B) {

Vorab-Schritte ausführt, *auch* wenn Sie anschließend **mehrere Prozesse** (mehrere Worker) für die Anwendung selbst starten. Wenn diese Schritte von **mehreren Prozessen** ausgeführt würden, würden diese die Arbeit **verdoppeln**, indem sie sie **parallel** ausführen, und wenn es sich bei den Schritten um etwas Delikates wie eine Datenbankmigration handelt, könnte das miteinander Konflikte verursachen.

Natürlich gibt es Fälle, in denen es kein Problem darstellt, die Vorab-Schritte mehrmals...