): List<SmallSubprojectBucket> {
        // splitIntoBuckets() method expects us to split large element into N elements,
        // but we want to have a single bucket with N batches.
        // As a workaround, we repeat the bucket N times, and deduplicate the result at the end
        val resultIncludingDuplicates = splitIntoBuckets(
            LinkedList(subProjectTestClassTimes),

}

// FindInBatches finds all records in batches of batchSize
func (db *DB) FindInBatches(dest interface{}, batchSize int, fc func(tx *DB, batch int) error) *DB {
	var (
		tx = db.Order(clause.OrderByColumn{
			Column: clause.Column{Table: clause.CurrentTable, Name: clause.PrimaryKey},
		}).Session(&Session{})
		queryDB      = tx
		rowsAffected int64
		batch        int
	)

	// user specified offset or limit

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *

    matrices or batches of matrices (CPU only).
*   Added gradients for eigenvalues and eigenvectors computed using
    `self_adjoint_eig` or `self_adjoint_eigvals`.
*   Eliminated `batch_*` methods for most linear algebra and FFT ops and
    promoted the non-batch version of the ops to handle batches of matrices.

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *

		if len(SSES3SinglePartObjects) == 0 {
			for i := range batch {
				size, err := batch[i].GetActualSize()
				if err != nil {
					return err
				}
				batch[i].Size = size

				if _, ok := crypto.IsEncrypted(batch[i].UserDefined); ok {
					ETag, err := etag.Parse(batch[i].ETag)
					if err != nil {
						return err
					}
					batch[i].ETag = ETag.Format().String()
				}
			}

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *

	if err != nil {
		return err
	}
	*ef = BatchJobExpireFilter(tmp)
	ef.line, ef.col = value.Line, value.Column
	return err
}

// Matches returns true if obj matches the filter conditions specified in ef.
func (ef BatchJobExpireFilter) Matches(obj ObjectInfo, now time.Time) bool {
	switch ef.Type {
	case BatchJobExpireObject:
		if obj.DeleteMarker {
			return false
		}
	case BatchJobExpireDeleted:

    private final EventBus bus;
    private final List<StringCatcher> catchers;

    Registrator(EventBus bus, List<StringCatcher> catchers) {
      this.bus = bus;
      this.catchers = catchers;
    }

    @Override
    public void run() {
      StringCatcher catcher = new StringCatcher();
      bus.register(catcher);
      catchers.add(catcher);
    }
  }

  /**
   * A collector for DeadEvents.

            final Matcher matcher = pattern.matcher(v.trim());
            if (matcher.matches()) {
                final PrunedTag tag = new PrunedTag(matcher.group(1));
                if (matcher.group(2) != null) {
                    final String attrPair = matcher.group(2).substring(1, matcher.group(2).length() - 1);