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;
- 相关的专用名词解释可参考： InfluxDB glossary of terms
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 <- err
}(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 <-w.closing:
return ErrWriteFailed
case <-timeout.C:
atomic.AddInt64(&w.stats.WriteTimeout, 1)
// return timeout error to caller
return ErrTimeout
case err := <-ch:
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))]
