mapred.maxthreads.generate.mapoutput=2 # Num threads to write map outputs
mapred.maxthreads.partition.closer=0 # Asynchronous map flushers
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

Spark/Hadoop workloads which use Hadoop MR Committer v1/v2 algorithm upload objects to a temporary prefix in a bucket. These objects are 'renamed' to a different prefix on Job commit. Object storage admins are forced to configure separate ILM policies to expire these objects and their versions to reclaim space.

	"$content-encoding":        true,
	"$expires":                 true,
	"$key":                     true,
	"$success_action_redirect": true,
	"$redirect":                true,
	"$success_action_status":   true,
	"$x-amz-algorithm":         false,
	"$x-amz-credential":        false,
	"$x-amz-date":              false,
}

var postPolicyIgnoreKeys = map[string]bool{
	"Policy":              true,
	xhttp.AmzSignature:    true,

	return dm.lockBlocking(ctx, cancel, id, source, isReadLock, opts)
}

// lockBlocking will try to acquire either a read or a write lock
//
// The function will loop using a built-in timing randomized back-off
// algorithm until either the lock is acquired successfully or more
// time has elapsed than the timeout value.

			tillOffset := erasure.ShardFileOffset(0, partSize, partSize)
			readers := make([]io.ReaderAt, len(latestDisks))
			prefer := make([]bool, len(latestDisks))
			checksumAlgo := erasureInfo.GetChecksumInfo(partNumber).Algorithm
			for i, disk := range latestDisks {
				if disk == OfflineDisk {
					continue
				}
				checksumInfo := copyPartsMetadata[i].Erasure.GetChecksumInfo(partNumber)