一. 整体流程
- client写入时,会首先写入内存的shard,若shard写入成功,则直接返回client;
- 若写入后shard已满,则将shard内的数据压缩后保存为inmemoryPart(仍然在内存中),然后返回client:
- inmemoryPart的数据,被后台的goroutine,定期的merge为part结构,保存到disk中;
时序数据在磁盘中的存储:
- partition: 一个月1个目录,比如2023_05:
- part: 作为partition下的子目录,里面包含tv和索引信息;
# ls 2023_05/
117_117_20230504085731.987_20230504085737.814_175ADBE68C628DDD
# # ls 2023_05/117_117_20230504085731.987_20230504085737.814_175ADBE68C628DDD/
index.bin metaindex.bin min_dedup_interval timestamps.bin values.bin
二. 内存shard
shards的个数:
- shards个数跟CPU核数有关;
- 对4C4G的机器来说,就1个shard;
// The number of shards for rawRow entries per partition.
//
var rawRowsShardsPerPartition = (cgroup.AvailableCPUs() + 3) / 4
每个shard保存的rows个数:
- 范围=1w~50w;
- unsafe.Sizeof(rawRow{})=50
对4C4G机器来说:
- memory.Allowed() = 4G×60%;
- rowRowsShardsPerPartition=1;
- 每个shard保存的rows个数:结果=(4G×60% / 1 / 256 / 50) = 18w;
// getMaxRawRowsPerShard returns the maximum number of rows that haven't been converted into parts yet.
func getMaxRawRowsPerShard() int {
maxRawRowsPerPartitionOnce.Do(func() {
n := memory.Allowed() / rawRowsShardsPerPartition / 256 / int(unsafe.Sizeof(rawRow{}))
if n < 1e4 {
n = 1e4
}
if n > 500e3 {
n = 500e3
}
maxRawRowsPerPartition = n
})
return maxRawRowsPerPartition
}
若存在N个shards,写入时保存到哪个shard?
按顺序轮转写:roundRobin
- 第一次写第一个,下一次写第二个...
func (rrss *rawRowsShards) addRows(pt *partition, rows []rawRow) {
n := atomic.AddUint32(&rrss.shardIdx, 1)
shards := rrss.shards
idx := n % uint32(len(shards))
shard := &shards[idx]
shard.addRows(pt, rows)
}
三. 写入的代码
首先,根据rows时间找目标partition,为简化分析,仅考虑一个partition写入的情况:
- 一个partition就是一个month;
// lib/storage/table.go
func (tb *table) AddRows(rows []rawRow) error {
if len(rows) == 0 {
return nil
}
// Verify whether all the rows may be added to a single partition.
ptwsX := getPartitionWrappers()
defer putPartitionWrappers(ptwsX)
ptwsX.a = tb.GetPartitions(ptwsX.a[:0])
ptws := ptwsX.a
for i, ptw := range ptws {
singlePt := true
for j := range rows {
if !ptw.pt.HasTimestamp(rows[j].Timestamp) {
singlePt = false
break
}
}
if !singlePt {
continue
}
...
// 所有rows都在一个partition
// Fast path - add all the rows into the ptw.
ptw.pt.AddRows(rows)
tb.PutPartitions(ptws)
return nil
}
...
}
确定partition后,后面的流程即在partion内写入:
- rows会被先写入partition内的[]shard;
// lib/storage/partition.go
// AddRows adds the given rows to the partition pt.
func (pt *partition) AddRows(rows []rawRow) {
if len(rows) == 0 {
return
}
// Validate all the rows.
...
// 写入到[]shard
pt.rawRows.addRows(pt, rows)
}
shard内的写入:
- 若shard内有足够的空位写入rows,则写入shard并返回client了;
- 否则,将shard内已有的rows和新rows保存在rowsToFlush中;然后将rowsToFlush中的数据写入inmemoryPart;
// lib/storage/partition.go
func (rrs *rawRowsShard) addRows(pt *partition, rows []rawRow) {
var rowsToFlush []rawRow
rrs.mu.Lock()
if cap(rrs.rows) == 0 {
n := getMaxRawRowsPerShard()
rrs.rows = make([]rawRow, 0, n)
}
maxRowsCount := cap(rrs.rows)
capacity := maxRowsCount - len(rrs.rows)
// 还有空位
if capacity >= len(rows) {
// Fast path - rows fit capacity.
rrs.rows = append(rrs.rows, rows...)
} else {
// shard中没有空位了
// 将shard中的rows和新rows保存在rowsToFlush中
// Slow path - rows don't fit capacity.
// Put rrs.rows and rows to rowsToFlush and convert it to a part.
rowsToFlush = append(rowsToFlush, rrs.rows...)
rowsToFlush = append(rowsToFlush, rows...)
rrs.rows = rrs.rows[:0]
rrs.lastFlushTime = fasttime.UnixTimestamp()
}
rrs.mu.Unlock()
// 将rowsToFlush内的rows写入inmemoryPart
pt.flushRowsToParts(rowsToFlush)
}
将rowsToFlush的数据写入inmemoryPart的过程:
- 这里可以看到,若rowsToFlush为空的话,函数就直接返回了;
- 具体工作由pt.addRowsPart(rowsPart)执行;
// lib/storage/partition.go
func (pt *partition) flushRowsToParts(rows []rawRow) {
maxRows := getMaxRawRowsPerShard()
wg := getWaitGroup()
for len(rows) > 0 {
n := maxRows
if n > len(rows) {
n = len(rows)
}
wg.Add(1)
go func(rowsPart []rawRow) {
defer wg.Done()
pt.addRowsPart(rowsPart) // 执行工作的函数
}(rows[:n])
rows = rows[n:]
}
wg.Wait()
putWaitGroup(wg)
}
将rows内容写入inmemoryPart,然后构造一个partWrapper,将partWrapper保存到partition.smallParts中;
与此同时,判断pt.smallParts是否超过256个,若<=256则直接返回;否则帮助执行merge part;
// lib/storage/partition.go
func (pt *partition) addRowsPart(rows []rawRow) {
// 将rows的内容写入inmemoryPart
mp := getInmemoryPart()
mp.InitFromRows(rows) //将rows写入inmemoryPart时会对rows数据进行压缩
...
// 构造一个partWrapper
p, err := mp.NewPart()
pw := &partWrapper{
p: p,
mp: mp,
refCount: 1,
}
// 将新的partWrapper保存在partition的smallParts中
pt.smallParts = append(pt.smallParts, pw)
// 判定是否超过256
ok := len(pt.smallParts) <= maxSmallPartsPerPartition
pt.partsLock.Unlock()
if ok {
return // smallParts <= 256,直接返回
}
// 若 smallParts > 256,则帮忙执行merge
// The added part exceeds available limit. Help merging parts.
...
err = pt.mergeSmallParts(false)
if err == nil {
atomic.AddUint64(&pt.smallAssistedMerges, 1)
return
}
....
}
四. 总结
最快的流程:
- rows写入到partition写的某个shard,然后返回;
- shard内的rows被goroutine定期的保存到inmemoryPart;
次快的流程:
- rows写入的目标shard满了,将shard rows和新rows存入inmemoryPart,保存到partition.smallParts中;
- inmemoryPart内的rows被goroutine定期的merge到磁盘,保存为part目录;
最慢的流程:
- 在上一个流程的基础上,发现pt.smallParts超过256个,帮助执行merge;
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