func shuffleWithDist[T any](input []T, distribution []int) []T {
	if distribution == nil {
		return input
	}
	shuffled := make([]T, len(input))
	for index := range input {
		blockIndex := distribution[index]
		shuffled[blockIndex-1] = input[index]
	}
	return shuffled
}

// Return shuffled partsMetadata depending on distribution.
func shufflePartsMetadata(partsMetadata []FileInfo, distribution []int) []FileInfo {

	var err error
	allModels := []interface{}{&User{}, &Account{}, &Pet{}, &Company{}, &Toy{}, &Language{}, &Coupon{}, &CouponProduct{}, &Order{}, &Parent{}, &Child{}, &Tools{}}
	rand.Seed(time.Now().UnixNano())
	rand.Shuffle(len(allModels), func(i, j int) { allModels[i], allModels[j] = allModels[j], allModels[i] })

	DB.Migrator().DropTable("user_friends", "user_speaks")

	if err = DB.Migrator().DropTable(allModels...); err != nil {

    for (int attempts = 0; attempts < reduceIterationsIfGwt(1000); attempts++) {
      ArrayList<Integer> elements = createOrderedList(10);
      shuffle(elements, random);
      MinMaxPriorityQueue<Integer> queue = MinMaxPriorityQueue.create(elements);
      shuffle(elements, random);
      for (Integer element : elements) {
        assertThat(queue.remove(element)).isTrue();
        assertIntact(queue);

mapreduce.fileoutputcommitter.algorithm.version=2 # Use the latest committer version
mapreduce.job.reduce.slowstart.completedmaps=0.99 # 99% map, then reduce
mapreduce.reduce.shuffle.input.buffer.percent=0.9 # Min % buffer in RAM
mapreduce.reduce.shuffle.merge.percent=0.9 # Minimum % merges in RAM
mapreduce.reduce.speculative=false # Disable speculation for reducing
mapreduce.task.io.sort.factor=999 # Threshold before writing to disk

              return null;
            }
          });
    }
    assertEquals(allTasks.size() + 1, barrier.getParties());
    for (int i = 0; i < 1000; i++) {
      Collections.shuffle(allTasks);
      AbstractFuture<String> future = new AbstractFuture<String>() {};
      currentFuture.set(future);
      for (Callable<?> task : allTasks) {

              return null;
            }
          });
    }
    assertEquals(allTasks.size() + 1, barrier.getParties());
    for (int i = 0; i < 1000; i++) {
      Collections.shuffle(allTasks);
      AbstractFuture<String> future = new AbstractFuture<String>() {};
      currentFuture.set(future);
      for (Callable<?> task : allTasks) {

		}
		buf = xlMetaV2TrimData(buf)

		vers = append(vers, metaCacheEntry{
			name:     "a",
			metadata: buf,
		})
	}

	// Shuffle...
	for i := range 100 {
		rng := rand.New(rand.NewSource(int64(i)))
		rng.Shuffle(len(vers), func(i, j int) {
			vers[i], vers[j] = vers[j], vers[i]
		})
		var entries []chan metaCacheEntry
		for _, v := range vers {
			v.cached = nil

			NextCycle: oldCache.Info.NextCycle,
		},
		Cache: make(map[string]dataUsageEntry, len(oldCache.Cache)),
	}

	// Put all buckets into channel.
	bucketCh := make(chan BucketInfo, len(buckets))

	// Shuffle buckets to ensure total randomness of buckets, being scanned.
	// Otherwise same set of buckets get scanned across erasure sets always.
	// at any given point in time. This allows different buckets to be scanned

		// Run for a number of times, shuffling the input to ensure that output is consistent.
		for i := range 10 {
			t.Run(fmt.Sprintf("test-%d-%s-run-%d", testID, tt.name, i), func(t *testing.T) {
				if i > 0 {
					rng.Shuffle(len(tt.m), func(i, j int) {
						tt.m[i], tt.m[j] = tt.m[j], tt.m[i]
					})
				}
				gotSelected, gotOk := tt.m.resolve(&tt.r)
				if gotOk != tt.wantOk {

		askDisks = len(disks) // use all available drives
	}

	// However many we ask, versions must exist on ~50%
	listingQuorum := (askDisks + 1) / 2

	if askDisks > 0 && len(disks) > askDisks {
		rand.Shuffle(len(disks), func(i, j int) {
			disks[i], disks[j] = disks[j], disks[i]
		})
		fallbackDisks = disks[askDisks:]
		disks = disks[:askDisks]
	}

	// How to resolve results.