},
		batches: make(map[ThreadID][]batch),
	}
	// Process the spilled batch.
	if spill != nil {
		g.gen = spill.gen
		if err := processBatch(g, *spill.batch); err != nil {
			return nil, nil, err
		}
		spill = nil
	}
	// Read batches one at a time until we either hit EOF or
	// the next generation.
	var spillErr error
	for {
		b, gen, err := readBatch(r)
		if err == io.EOF {
			break
		}

				}
				pluginName := resourceHandle.DriverName
				batches[pluginName] = append(batches[pluginName], claim)
			}

			return nil
		})
		if err != nil {
			return fmt.Errorf("locked cache operation: %w", err)
		}
	}

	// Call NodePrepareResources for all claims in each batch.
	// If there is any error, processing gets aborted.

			p.batchOffsets[raw.batchPid] = append(p.batchOffsets[raw.batchPid], bo)
			curP = raw.batchPid
		}

		batches := p.batchOffsets[curP]
		if len(batches) == 0 {
			return fmt.Errorf("read event %d with current P of %d, but P has no batches yet",
				raw.typ, curP)
		}
		batches[len(batches)-1].numEvents++

		if raw.typ == EvCPUSample {
			e := Event{Type: raw.typ}

			argOffset := 1

// usage, and minimal GC pressure. It allocates events in batches so that even
// though we have to load the entire trace into memory, the conversion process
// shouldn't result in a doubling of memory usage, even if all converted events
// are kept alive, as we free batches once we're done with them.
//
// The conversion process is lossless.

package trace

import (
	"errors"

// a placeholder for a differently encoded event that's actually present in the experimental data.
type ExperimentalData struct {
	// Batches contain the actual experimental data, along with metadata about each batch.
	Batches []ExperimentalBatch
}

// ExperimentalBatch represents a packet of unparsed data along with metadata about that packet.
type ExperimentalBatch struct {

//
// It groups the calls into batches, starting with a group of initialBatchSize.
// Within each batch, it may call the function multiple times concurrently.
//
// If a whole batch succeeds, the next batch may get exponentially larger.
// If there are any failures in a batch, all remaining batches are skipped
// after waiting for the current batch to complete.
//

    /** True if either side has cleanly shut down this stream. We shall send no more bytes. */
    var finished: Boolean = false,
  ) : Sink {
    /**
     * Buffer of outgoing data. This batches writes of small writes into this sink as larges frames
     * written to the outgoing connection. Batching saves the (small) framing overhead.
     */
    private val sendBuffer = Buffer()

// after an object is no longer referenced, the runtime is allowed to perform
// a space-saving optimization that batches objects together in a single
// allocation slot. The finalizer for an unreferenced object in such an
// allocation may never run if it always exists in the same batch as a
// referenced object. Typically, this batching only happens for tiny
// (on the order of 16 bytes or less) and pointer-free objects.
//

		// single span is in general a very fast operation, taking as little as 30 ns
		// on modern hardware. (See #54767.)
		//
		// As a result, bgsweep sweeps in batches, and only calls into the scheduler
		// at the end of every batch. Furthermore, it only yields its time if there
		// isn't spare idle time available on other cores. If there's available idle

		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()
				}
			}