wukong引擎源码分析之索引——part 2 持久化 直接set（key，docID数组）在kv存储里

前面说过，接收indexerRequest的代码在index_worker.go里：

func (engine *Engine) indexerAddDocumentWorker(shard int) {
    for {
        request := <-engine.indexerAddDocumentChannels[shard] //关键
        addInvertedIndex := engine.indexers[shard].AddDocument(request.document, request.dealDocInfoChan) // 向反向索引表(数组)中加入一个文档
        // save
        if engine.initOptions.UsePersistentStorage {
            for k, v := range addInvertedIndex {
                engine.persistentStorageIndexDocumentChannels[shard] <- persistentStorageIndexDocumentRequest{
                    typ:            "index",
                    keyword:        k,
                    keywordIndices: v,
                }
            }
        }

        atomic.AddUint64(&engine.numTokenIndexAdded,
            uint64(len(request.document.Keywords)))
        atomic.AddUint64(&engine.numDocumentsIndexed, )
    }
} 

持久化的代码：engine/persistent_storage_worker.go

package engine

import (
    "bytes"
    "encoding/binary"
    "encoding/gob"
    "github.com/huichen/wukong/core"
    "github.com/huichen/wukong/types"
    "sync"
    "sync/atomic"
)

type persistentStorageIndexDocumentRequest struct {
    typ string //"info"or"index"

    // typ=="info"时，以下两个字段有效
    docId   uint64
    docInfo *types.DocInfo

    // typ=="index"时，以下两个字段有效
    keyword        string
    keywordIndices *types.KeywordIndices
}

func (engine *Engine) persistentStorageIndexDocumentWorker(shard int) {
    for {
        request := <-engine.persistentStorageIndexDocumentChannels[shard]
        switch request.typ {
        case "info":
            // 得到key
            b := make([]byte, )
            length := binary.PutUvarint(b, request.docId)

            // 得到value
            var buf bytes.Buffer
            enc := gob.NewEncoder(&buf)
            err := enc.Encode(request.docInfo)
            if err != nil {
                atomic.AddUint64(&engine.numDocumentsStored, )
                return
            }

            // 将key-value写入数据库
            engine.dbs[shard][getDB(request.typ)].Set(b[:length], buf.Bytes())
            atomic.AddUint64(&engine.numDocumentsStored, )

        case "index":
            // 得到key
            b := []byte(request.keyword)

            // 得到value
            var buf bytes.Buffer
            enc := gob.NewEncoder(&buf)
            err := enc.Encode(request.keywordIndices)
            if err != nil {
                return
            }

            // 将key-value写入数据库
            engine.dbs[shard][getDB(request.typ)].Set(b, buf.Bytes())
        }
    }
}

func (engine *Engine) persistentStorageRemoveDocumentWorker(docId uint64, shard int) {
    // 得到key
    b := make([]byte, )
    length := binary.PutUvarint(b, docId)

    // 从数据库删除该key
    engine.dbs[shard][getDB("info")].Delete(b[:length])
}

func (engine *Engine) persistentStorageInitWorker(shard int) {
    var finish sync.WaitGroup
    finish.Add()
    // 恢复docInfo
    go func() {
        defer finish.Add(-)
        engine.dbs[shard][getDB("info")].ForEach(func(k, v []byte) error {
            key, value := k, v
            // 得到docID
            docId, _ := binary.Uvarint(key)

            // 得到data
            buf := bytes.NewReader(value)
            dec := gob.NewDecoder(buf)
            var data types.DocInfo
            err := dec.Decode(&data)
            if err == nil {
                // 添加索引
                core.AddDocInfo(shard, docId, &data)
            }
            return nil
        })
    }()

    // 恢复invertedIndex
    go func() {
        defer finish.Add(-)
        engine.dbs[shard][getDB("index")].ForEach(func(k, v []byte) error {
            key, value := k, v
            // 得到keyword
            keyword := string(key)

            // 得到data
            buf := bytes.NewReader(value)
            dec := gob.NewDecoder(buf)
            var data types.KeywordIndices
            err := dec.Decode(&data)
            if err == nil {
                // 添加索引
                core.AddKeywordIndices(shard, keyword, &data)
            }
            return nil
        })
    }()
    finish.Wait()
    engine.persistentStorageInitChannel <- true
}

可以看到，倒排索引存在DB里是丑陋的，直接set(key, value) 其中，key是倒排列表的关键字，而value是doc id list也就是数组。

如果索引比较多，每次去DB set是非常耗时的，尤其针对同一个keyword有doc id插入时！

总之，wukong对于持久化的做法很丑陋！