@@ -388,7 +388,7 @@ func (h *Head) loadWAL(r *wal.Reader, multiRef map[uint64]uint64) (err error) {
388388 series , created := h .getOrCreateWithID (s .Ref , s .Labels .Hash (), s .Labels )
389389
390390 if ! created {
391- // There's already a different Ref for this series.
391+ // There's already a different ref for this series.
392392 multiRefLock .Lock ()
393393 multiRef [s .Ref ] = series .ref
394394 multiRefLock .Unlock ()
@@ -1650,7 +1650,7 @@ func (s *memSeries) chunksMetas() []chunks.Meta {
16501650}
16511651
16521652// reset re-initialises all the variable in the memSeries except 'lset', 'ref',
1653- // and 'chunkRange', like how it would appear after 'newmemSeries (...)'.
1653+ // and 'chunkRange', like how it would appear after 'newMemSeries (...)'.
16541654func (s * memSeries ) reset () {
16551655 s .chunks = nil
16561656 s .headChunk = nil
@@ -1661,7 +1661,7 @@ func (s *memSeries) reset() {
16611661 s .app = nil
16621662}
16631663
1664- // Appendable checks whether the given sample is valid for appending to the series.
1664+ // appendable checks whether the given sample is valid for appending to the series.
16651665func (s * memSeries ) appendable (t int64 , v float64 ) error {
16661666 c := s .head ()
16671667 if c == nil {
@@ -1694,7 +1694,7 @@ func (s *memSeries) chunkID(pos int) int {
16941694 return pos + s .firstChunkID
16951695}
16961696
1697- // TruncateChunksBefore removes all chunks from the series that have not timestamp
1697+ // truncateChunksBefore removes all chunks from the series that have not timestamp
16981698// at or after mint. Chunk IDs remain unchanged.
16991699func (s * memSeries ) truncateChunksBefore (mint int64 ) (removed int ) {
17001700 var k int
@@ -1715,7 +1715,7 @@ func (s *memSeries) truncateChunksBefore(mint int64) (removed int) {
17151715 return k
17161716}
17171717
1718- // Append adds the sample (t, v) to the series.
1718+ // append adds the sample (t, v) to the series.
17191719func (s * memSeries ) append (t int64 , v float64 ) (success , chunkCreated bool ) {
17201720 // Based on Gorilla white papers this offers near-optimal compression ratio
17211721 // so anything bigger that this has diminishing returns and increases
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