// Arrange: program send() to simulate first, next, next(NO_MORE_FILES)
        List<String[]> batches = new ArrayList<>();
        batches.add(new String[] { ".", "..", "a", "b" }); // first batch, dot entries filtered
        batches.add(new String[] { "c" }); // second batch
        batches.add(new String[] {}); // last -> NO_MORE_FILES

        // send() answer that mutates the provided response

    /**
     * Executes and optionally caches a batch of requests using the provided supplier function.
     * This method allows for efficient batch processing of multiple requests.
     * <p>
     * The implementation may optimize the execution by:
     * <ul>
     *   <li>Returning cached results for previously executed requests</li>
     *   <li>Grouping similar requests for batch processing</li>

    ): 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

  inner class FramingSink(
    /** 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()

  ```bash
  curl -u admin:admin ...
  # or
  curl -H "Authorization: Basic YWRtaW46YWRtaW4=" ...
  ```

#### Issue: Large bulk imports timing out

**Solution**:
- Split large files into smaller batches (e.g., 10,000 docs per file)
- Increase timeout in `system.properties`:
  ```properties
  crawler.document.request.timeout=600000
  ```
- Use asynchronous import via Admin UI instead of API

   * 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()
				}
			}

    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.

    be only be used to accelerate a transition to OkHttp's request/response API.
    These deprecated modules will be dropped in an upcoming OkHttp 3.x release.

 *  **Canceling batches of calls is now the application's responsibility.**
    The API to cancel calls by tag has been removed and replaced with a more
    general mechanism. The dispatcher now exposes all in-flight calls via its