数据写入流程分析

本篇不涉及存储层的写入，只分析写入请求的处理流程

Influxdb名词介绍

如果想搞清楚Influxdb数据写入流程，Influxdb本身的用法和其一些主要的专用词还是要明白是什么意思，比如measurement, field key,field value, tag key, tag value, tag set, line protocol, point, series, query, retention policy等;

分析入口

我们还是以http写请求为入口来分析，在httpd/handler.go中创建Handler时有如下代码:

Route{

"write", // Data-ingest route.

"POST", "/write", true, writeLogEnabled, h.serveWrite,

}

因此对写入请求的处理就在函数 func (h *Handler) serveWrite(w http.ResponseWriter, r *http.Request, user meta.User)中。

Handler.serveWrite流程梳理:

2.1 获取写入的db并判断db是否存在

database := r.URL.Query().Get("db")

if database == "" {

h.httpError(w, "database is required", http.StatusBadRequest)

return

}

if di := h.MetaClient.Database(database); di == nil {

h.httpError(w, fmt.Sprintf("database not found: %q", database), http.StatusNotFound)

return

}

2.2 权限验证

if h.Config.AuthEnabled {

if user == nil {

h.httpError(w, fmt.Sprintf("user is required to write to database %q", database), http.StatusForbidden)

return

}

if err := h.WriteAuthorizer.AuthorizeWrite(user.ID(), database); err != nil {

h.httpError(w, fmt.Sprintf("%q user is not authorized to write to database %q", user.ID(), database), http.StatusForbidden)

return

}

}

2.3 获取http请求的body部分，如需gzip解压缩则解压，并且作body size的校验，因为有body size大小限制

body := r.Body

if h.Config.MaxBodySize > 0 {

body = truncateReader(body, int64(h.Config.MaxBodySize))

}

...

_, err := buf.ReadFrom(body)

2.4 从http body中解析出 points

points, parseError := models.ParsePointsWithPrecision(buf.Bytes(), time.Now().UTC(),

r.URL.Query().Get("precision"))

2.5 将解析出的points写入db

h.PointsWriter.WritePoints(database, r.URL.Query().Get("rp"), consistency, user, points);

Points的解析

将http body解析成Points是写入前的最主要的一步, 相关内容定义在 models/points.go中;

我们先来看一下一条写入语句是什么样子的： insert test_mea_1,tag1=v1,tag2=v2 cpu=1,memory=10

其中test_mea_1是measurement, tag key是tag1和tag2, 对应的tag value是v1和v2, field key是cpu和memory, field value是1和10;

先来看下point的定义，它实现了Point interface

type point struct {

time time.Time

//这个 key包括了measurement和tag set, 且tag set是排序好的

key []byte

// text encoding of field data

fields []byte

// text encoding of timestamp

ts []byte

// cached version of parsed fields from data

cachedFields map[string]interface{}

// cached version of parsed name from key

cachedName string

// cached version of parsed tags

cachedTags Tags

//用来遍历所有的field

it fieldIterator

}

解析出Points

func ParsePointsWithPrecision(buf []byte, defaultTime time.Time, precision string) ([]Point, error) {

points := make([]Point, 0, bytes.Count(buf, []byte{'\n'})+1)

var (

pos int

block []byte

failed []string

)

for pos < len(buf) {

pos, block = scanLine(buf, pos)

pos++

...

pt, err := parsePoint(block[start:], defaultTime, precision)

if err != nil {

failed = append(failed, fmt.Sprintf("unable to parse '%s': %v", string(block[start:]), err))

} else {

points = append(points, pt)

}

}

return points, nil

}

这里的解析并没有用正则之类的方案，纯的字符串逐次扫描,这里不详细展开说了.

PointsWriter分析

定义在coordinator/points_writer.go中

主要负责将数据写入到本地的存储,我们重点分析下WritePointsPrivileged

func (w *PointsWriter) WritePointsPrivileged(database, retentionPolicy string, consistencyLevel models.ConsistencyLevel, points []models.Point) error {

....

//将point按time对应到相应的Shar上, 这个对应关系存储在shardMappings里, 这个MapShareds我们后面会分析

shardMappings, err := w.MapShards(&WritePointsRequest{Database: database, RetentionPolicy: retentionPolicy, Points: points})

if err != nil {

return err

}

// Write each shard in it's own goroutine and return as soon as one fails.

ch := make(chan error, len(shardMappings.Points))

for shardID, points := range shardMappings.Points {

// 每个 Shard启动一个goroutine作写入操作, 真正的写入操作w.writeToShard

go func(shard *meta.ShardInfo, database, retentionPolicy string, points []models.Point) {

err := w.writeToShard(shard, database, retentionPolicy, points)

if err == tsdb.ErrShardDeletion {

err = tsdb.PartialWriteError{Reason: fmt.Sprintf("shard %d is pending deletion", shard.ID), Dropped: len(points)}

}

ch

}(shardMappings.Shards[shardID], database, retentionPolicy, points)

}

...

// 写入超时会return ErrTimeout

timeout := time.NewTimer(w.WriteTimeout)

defer timeout.Stop()

for range shardMappings.Points {

select {

case

return ErrWriteFailed

case

atomic.AddInt64(&w.stats.WriteTimeout, 1)

// return timeout error to caller

return ErrTimeout

case err :=

if err != nil {

return err

}

}

}

return err

}

Point到Shard的映谢

3.1 先根据point的time找到对应的ShardGroup, 没有就创建新的ShardGroup;

3.2 按Point的key(measurement + tag set取hash)来散

sgi.Shards[hash%uint64(len(sgi.Shards))]