// standard metadata headers
			// specified in the filter
			var match bool
			for k, v := range obj.UserDefined {
				if !stringsHasPrefixFold(k, "x-amz-meta-") && !isStandardHeader(k) {
					continue
				}
				// We only need to match x-amz-meta or standardHeaders
				if kv.Match(BatchJobKV{Key: k, Value: v}) {
					match = true
				}
			}
			if !match {
				return false

// flags:
//   filter:
//     newerThan: "7d" # match objects newer than this value (e.g. 7d10h31s)
//     olderThan: "7d" # match objects older than this value (e.g. 7d10h31s)
//     createdAfter: "date" # match objects created after "date"
//     createdBefore: "date" # match objects created before "date"
//     tags:
//       - key: "name"
//         value: "pick*" # match objects with tag 'name', with all values starting with 'pick'

					continue
				}

				batch = append(batch, obj)

				if len(batch) < *r.Source.Snowball.Batch {
					continue
				}
				writeFn(batch)
				batch = batch[:0]
			}
			writeFn(batch)
			xioutil.SafeClose(slowCh)
		}()
	} else {
		slowCh = walkCh
	}

	workerSize, err := strconv.Atoi(env.Get("_MINIO_BATCH_REPLICATION_WORKERS", strconv.Itoa(runtime.GOMAXPROCS(0)/2)))

		results = append(results, sub...)
		lastBatch = batch
		return nil
	}); result.Error != nil || result.RowsAffected != 5 {
		t.Errorf("Failed to batch find, got error %v, rows affected: %v", result.Error, result.RowsAffected)
	}
	if lastBatch != 3 {
		t.Fatalf("incorrect last batch, expected: %v, got: %v", 3, lastBatch)
	}

		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()
				}
			}

	logger.LogIf(ctx, "healing", err, errKind...)
}

func batchLogIf(ctx context.Context, err error, errKind ...interface{}) {
	logger.LogIf(ctx, "batch", err, errKind...)
}

func batchLogOnceIf(ctx context.Context, err error, id string, errKind ...interface{}) {
	logger.LogOnceIf(ctx, "batch", err, id, errKind...)
}

func bootLogIf(ctx context.Context, err error, errKind ...interface{}) {
	logger.LogIf(ctx, "bootstrap", err, errKind...)

		} else {
			globalHealConfig.Update(healCfg)
		}
	case config.BatchSubSys:
		batchCfg, err := batch.LookupConfig(s[config.BatchSubSys][config.Default])
		if err != nil {
			errs = append(errs, fmt.Errorf("Unable to apply batch config: %w", err))
		} else {
			globalBatchConfig.Update(batchCfg)
		}
	case config.ScannerSubSys:

	Enabled bool `json:"enabled"`
}

// Audit/Logger constants
const (
	Endpoint   = "endpoint"
	AuthToken  = "auth_token"
	ClientCert = "client_cert"
	ClientKey  = "client_key"
	BatchSize  = "batch_size"
	QueueSize  = "queue_size"
	QueueDir   = "queue_dir"
	Proxy      = "proxy"

	KafkaBrokers       = "brokers"
	KafkaTopic         = "topic"
	KafkaTLS           = "tls"
	KafkaTLSSkipVerify = "tls_skip_verify"

For deployments with [bucket](https://min.io/docs/minio/linux/administration/bucket-replication.html) or [batch](https://min.io/docs/minio/linux/administration/batch-framework.html#replicate) configurations, these metrics populate instead under the [Bucket Metrics](#bucket-metrics) endpoint.

*   `tf.data`:
    *   Graduated experimental APIs:
        * [`tf.data.Dataset.ragged_batch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#ragged_batch), which batches elements of `tf.data.Dataset`s into `tf.RaggedTensor`s.
        * [`tf.data.Dataset.sparse_batch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#sparse_batch), which batches elements of `tf.data.Dataset`s into `tf.sparse.SparseTensor`s.