}
					value = sql.FormatSQLTimestamp(time.Unix(0, 0).Add(duration))
				}
			} else if se.GetConvertedType() == parquettypes.ConvertedType_TIMESTAMP_MILLIS {
				duration := time.Duration(val) * time.Millisecond
				value = sql.FormatSQLTimestamp(time.Unix(0, 0).Add(duration))
			} else if se.GetConvertedType() == parquettypes.ConvertedType_TIMESTAMP_MICROS {

			// Otherwise, we risk the decoder hanging.
		}
		r.readerWg.Done()
	}

	// We cannot reuse as we are sending parsed objects elsewhere.
	simdjson.ParseNDStream(readCloser, r.input, nil)
	r.readerWg.Add(1)
	go r.startReader()
	return &r
}

// NewElementReader - creates new JSON reader using readCloser.
func NewElementReader(ch chan simdjson.Object, err *error, args *json.ReaderArgs) *Reader {
	return &Reader{

	var paxHdrs map[string]string
	var gnuLongName, gnuLongLink string

	// Externally, Next iterates through the tar archive as if it is a series of
	// files. Internally, the tar format often uses fake "files" to add meta
	// data that describes the next file. These meta data "files" should not
	// normally be visible to the outside. As such, this loop iterates through
	// one or more "header files" until it finds a "normal file".

	if r.columnNames == nil {
		r.columnNames = make([]string, len(csvRecord))
		for i := range csvRecord {
			r.columnNames[i] = fmt.Sprintf("_%v", i+1)
		}
	}

	// If no index map, add that.
	if r.nameIndexMap == nil {
		r.nameIndexMap = make(map[string]int64)
		for i := range r.columnNames {
			r.nameIndexMap[r.columnNames[i]] = int64(i)
		}
	}
	dstRec, ok := dst.(*Record)
	if !ok {

	r.expectedMin = expectedMin
}

// SetExpectedMax set expected max data expected from reader
func (r *Reader) SetExpectedMax(expectedMax int64) {
	r.expectedMax = expectedMax
}

// AddChecksum will add checksum checks as specified in
// https://docs.aws.amazon.com/AmazonS3/latest/userguide/checking-object-integrity.html
// Returns ErrInvalidChecksum if a problem with the checksum is found.