写入VictoriaMetrics的数据,首先被保存在内存shard,内存shard的数据定期的被压缩到inmemoryPart(内存中),inmemoryPart的数据被定期的合并到磁盘part中。
tv的压缩,发生在内存shard转换为inmemoryPart的过程中。
一. 入口代码
shard中存放原始数据,经过压缩后,数据被存放到inmemoryPart:
- rows被压缩到inmemoryPart的入口:mp.InitFromRows(rows);
// lib/storage/partition.go
func (pt *partition) addRowsPart(rows []rawRow) {
...
mp := getInmemoryPart()
mp.InitFromRows(rows) //这里:将rows数据压缩后保存到inmemoryPart中
...
p, err := mp.NewPart()
pw := &partWrapper{
p: p,
mp: mp,
refCount: 1,
}
pt.partsLock.Lock()
pt.smallParts = append(pt.smallParts, pw)
ok := len(pt.smallParts)
二. 整体流程
shard的rows按(tsid,timestamp)排序,然后将其分为N个block,每个block最多8k rows;
对每个block中进行压缩,压缩后block中包含:
- tsid: 即seriesId;
- timestamps: []int64
- values: 原为[]float64,转为[]int64和scale(保存在header中);
由于block中的values和times均为[]int64,故可使用相同的压缩算法:
对于[]int64的压缩,VictoriaMetrics针对不同的场景做了优化:
- 若[]int64内都是相同的值,则保存第一个值即可;
- 若[]int64内是delta相同的等差数列,则保存第一个值和delta值即可;
- 若[]int64内是Gauge类型值,则先计算value的delta,然后用zigzag压缩;
- 若[]int64内是Counter类型值,则先计算value的delta of delta,然后用zigzag压缩;
三. 源码分析
1.代码入口
由RawRowsMarshaller执行序列化和压缩:
// lib/storage/inmemory_part.go
// InitFromRows initializes mp from the given rows.
func (mp *inmemoryPart) InitFromRows(rows []rawRow) {
if len(rows) == 0 {
logger.Panicf("BUG: Inmemory.InitFromRows must accept at least one row")
}
mp.Reset()
rrm := getRawRowsMarshaler()
rrm.marshalToInmemoryPart(mp, rows)
putRawRowsMarshaler(rrm)
mp.creationTime = fasttime.UnixTimestamp()
}
2.划分block,每个block分别执行
- 首先,对所有的rows按照tsid,timestamp进行排序;
- 然后,将rows按照metricID和maxRowsPerBlock(8K),划分为1个个的Block;
-
然后,Block内的values值由[]float64转为[]int64+scale;
- scale保存在block.header中;
- 最后,执行block的压缩;
// lib/storage/raw_row.go
func (rrm *rawRowsMarshaler) marshalToInmemoryPart(mp *inmemoryPart, rows []rawRow) {
...
rrm.bsw.InitFromInmemoryPart(mp)
ph := &mp.ph
ph.Reset()
// 1.对所有的rows执行sort(按tsid,timestamp)
// Sort rows by (TSID, Timestamp) if they aren't sorted yet.
rrs := rawRowsSort(rows)
if !sort.IsSorted(&rrs) {
sort.Sort(&rrs)
}
// 2.按block进行划分
// Group rows into blocks.
var scale int16
var rowsMerged uint64
r := &rows[0]
tsid := &r.TSID
precisionBits := r.PrecisionBits
tmpBlock := getBlock()
defer putBlock(tmpBlock)
for i := range rows {
r = &rows[i]
if r.TSID.MetricID == tsid.MetricID && len(rrm.auxTimestamps)
[]float64转[]int64+scale,由decimal.AppendFloatToDecimal完成:
// lib/decimal/decimal.go
// AppendFloatToDecimal converts each item in src to v*10^e and appends
// each v to dst returning it as va.
//
// It tries minimizing each item in dst.
func AppendFloatToDecimal(dst []int64, src []float64) ([]int64, int16) {
...
// 比如,输入{1.2, 3.4, 5, 6, 7.8}
// 输出:{12 34 50 60 78},scale=-1
...
}
3.block内的压缩
- 首先,将block内的timestamps和values进行压缩,压缩为[]byte;
- 然后,将timestampsData的[]byte写入;
- 最后,将valuesData的[]byte写入;
// lib/storage/block_stream_writer.go
// WriteExternalBlock writes b to bsw and updates ph and rowsMerged.
func (bsw *blockStreamWriter) WriteExternalBlock(b *Block, ph *partHeader, rowsMerged *uint64) {
...
// 1.将block内的timestamp/values进行压缩
headerData, timestampsData, valuesData := b.MarshalData(bsw.timestampsBlockOffset, bsw.valuesBlockOffset)
...
// 2.写入timestampsData
fs.MustWriteData(bsw.timestampsWriter, timestampsData)
...
// 3.写入valuesData
fs.MustWriteData(bsw.valuesWriter, valuesData)
...
// 更新partHeader
updatePartHeader(b, ph)
}
重点看一下block内数据的压缩过程:
- 依次压缩values和timestamps;
- PrecisionBits默认=64,即无损压缩;
// lib/storage/block.go
// MarshalData marshals the block into binary representation.
func (b *Block) MarshalData(timestampsBlockOffset, valuesBlockOffset uint64) ([]byte, []byte, []byte) {
...
timestamps := b.timestamps[b.nextIdx:]
values := b.values[b.nextIdx:]
...
//1. 压缩values, PrecisionBits默认=64,即无损压缩
b.valuesData, b.bh.ValuesMarshalType, b.bh.FirstValue = encoding.MarshalValues(b.valuesData[:0], values, b.bh.PrecisionBits)
b.bh.ValuesBlockOffset = valuesBlockOffset
b.bh.ValuesBlockSize = uint32(len(b.valuesData))
b.values = b.values[:0]
// 2. 压缩timestamps, PrecisionBits默认=64,即无损压缩
b.timestampsData, b.bh.TimestampsMarshalType, b.bh.MinTimestamp = encoding.MarshalTimestamps(b.timestampsData[:0], timestamps, b.bh.PrecisionBits)
b.bh.TimestampsBlockOffset = timestampsBlockOffset
b.bh.TimestampsBlockSize = uint32(len(b.timestampsData))
b.bh.MaxTimestamp = timestamps[len(timestamps)-1]
b.timestamps = b.timestamps[:0]
b.bh.RowsCount = uint32(len(values))
b.headerData = b.bh.Marshal(b.headerData[:0])
b.nextIdx = 0
return b.headerData, b.timestampsData, b.valuesData
}
encode.MarshalValues和MarshallTimestamps都是对[]int64进行压缩,压缩的流程是相同的;
// lib/encoding/encoding.go
func MarshalValues(dst []byte, values []int64, precisionBits uint8) (result []byte, mt MarshalType, firstValue int64) {
return marshalInt64Array(dst, values, precisionBits)
}
func MarshalTimestamps(dst []byte, timestamps []int64, precisionBits uint8) (result []byte, mt MarshalType, firstTimestamp int64) {
return marshalInt64Array(dst, timestamps, precisionBits)
}
重点看一下[]int64的压缩过程:
- 若[]int64内都是相同的值,则保存第一个值即可;
- 若[]int64内是delta的等差数列,则保存第一个值和delta值;
- 若[]int64内是Gauge类型的值,则使用delta encoding进行压缩;
- 若[]int64内是Counter类型的值,则使用delta2 encoding进行压缩;
最后,还对结果使用zstd算法进行二次压缩:
// lib/encoding/encoding.go
func marshalInt64Array(dst []byte, a []int64, precisionBits uint8) (result []byte, mt MarshalType, firstValue int64) {
// 1.[]int64内都是相同的值
if isConst(a) {
firstValue = a[0]
return dst, MarshalTypeConst, firstValue
}
// 2.[]int64内是delta相同的等差数列
if isDeltaConst(a) {
firstValue = a[0]
dst = MarshalVarInt64(dst, a[1]-a[0])
return dst, MarshalTypeDeltaConst, firstValue
}
bb := bbPool.Get()
// 3.[]int64内是Gauge类型的数值
if isGauge(a) {
// 使用delta encoding压缩
// Gauge values are better compressed with delta encoding.
mt = MarshalTypeZSTDNearestDelta
pb := precisionBits
...
bb.B, firstValue = marshalInt64NearestDelta(bb.B[:0], a, pb)
} else {
// 4.[]int64内是Counter类型的数值,使用delta2 encoding
// Non-gauge values, i.e. counters are better compressed with delta2 encoding.
mt = MarshalTypeZSTDNearestDelta2
bb.B, firstValue = marshalInt64NearestDelta2(bb.B[:0], a, precisionBits)
}
// 5.最后还用zstd对结果进行二次压缩
// Try compressing the result.
dstOrig := dst
if len(bb.B) >= minCompressibleBlockSize { //minCompressibleBlockSize常量=128
compressLevel := getCompressLevel(len(a))
dst = CompressZSTDLevel(dst, bb.B, compressLevel)
}
...
return dst, mt, firstValue
}
看一下delta encoding的具体实现:
// lib/encoding/nearest_delta.go
// marshalInt64NearestDelta encodes src using `nearest delta` encoding
// with the given precisionBits and appends the encoded value to dst.
// precisionBits默认=64,即无损压缩
func marshalInt64NearestDelta(dst []byte, src []int64, precisionBits uint8) (result []byte, firstValue int64) {
...
// 1.计算src内value的delta
// 即delta=curValue-preValue
firstValue = src[0]
v := src[0]
src = src[1:]
is := GetInt64s(len(src))
if precisionBits == 64 {
// Fast path.
for i, next := range src {
d := next - v
v += d
is.A[i] = d
}
} else {
....
}
// 2.将[]delta结果使用zigzag进行压缩
dst = MarshalVarInt64s(dst, is.A)
PutInt64s(is)
return dst, firstValue
}
MarshalVarInt64s()负责将[]delta使用zigzag进行压缩:
// lib/encoding/int.go
// MarshalVarInt64s appends marshaled vs to dst and returns the result.
func MarshalVarInt64s(dst []byte, vs []int64) []byte {
for _, v := range vs {
if v -0x40 {
// Fast path
c := int8(v)
v := (c > 7) // zig-zag encoding without branching.
dst = append(dst, byte(v))
continue
}
v = (v > 63) // zig-zag encoding without branching.
u := uint64(v)
for u > 0x7f {
dst = append(dst, 0x80|byte(u))
u >>= 7
}
dst = append(dst, byte(u))
}
return dst
}
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