wukongd/engine/engine.go

package engine

import (
	"fmt"
	"github.com/cznic/kv"
	"github.com/huichen/murmur"
	"github.com/huichen/sego"
	"github.com/huichen/wukong/core"
	"github.com/huichen/wukong/types"
	"github.com/huichen/wukong/utils"
	"log"
	"os"
	"runtime"
	"sort"
	"strconv"
	"sync/atomic"
	"time"
)

const (
	NumNanosecondsInAMillisecond = 1000000
)

type Engine struct {
	// 计数器，用来统计有多少文档被索引等信息
	numDocumentsIndexed uint64
	numIndexingRequests uint64
	numTokenIndexAdded  uint64
	numDocumentsStored  uint64

	// 记录初始化参数
	initOptions types.EngineInitOptions
	initialized bool

	indexers   []core.Indexer
	rankers    []core.Ranker
	segmenter  sego.Segmenter
	stopTokens StopTokens
	dbs        []*kv.DB

	// 建立索引器使用的通信通道
	segmenterChannel               chan segmenterRequest
	indexerAddDocumentChannels     []chan indexerAddDocumentRequest
	rankerAddScoringFieldsChannels []chan rankerAddScoringFieldsRequest

	// 建立排序器使用的通信通道
	indexerLookupChannels             []chan indexerLookupRequest
	rankerRankChannels                []chan rankerRankRequest
	rankerRemoveScoringFieldsChannels []chan rankerRemoveScoringFieldsRequest

	// 建立持久存储使用的通信通道
	persistentStorageIndexDocumentChannel chan persistentStorageIndexDocumentRequest
	persistentStorageInitChannel          chan bool
}

func (engine *Engine) Init(options types.EngineInitOptions) {
	// 将线程数设置为CPU数
	runtime.GOMAXPROCS(runtime.NumCPU())

	// 初始化初始参数
	if engine.initialized {
		log.Fatal("请勿重复初始化引擎")
	}
	options.Init()
	engine.initOptions = options
	engine.initialized = true

	// 载入分词器词典
	engine.segmenter.LoadDictionary(options.SegmenterDictionaries)

	// 初始化停用词
	engine.stopTokens.Init(options.StopTokenFile)

	// 初始化索引器和排序器
	for shard := 0; shard < options.NumShards; shard++ {
		engine.indexers = append(engine.indexers, core.Indexer{})
		engine.indexers[shard].Init(*options.IndexerInitOptions)

		engine.rankers = append(engine.rankers, core.Ranker{})
		engine.rankers[shard].Init()
	}

	// 初始化分词器通道
	engine.segmenterChannel = make(
		chan segmenterRequest, options.NumSegmenterThreads)

	// 初始化索引器通道
	engine.indexerAddDocumentChannels = make(
		[]chan indexerAddDocumentRequest, options.NumShards)
	engine.indexerLookupChannels = make(
		[]chan indexerLookupRequest, options.NumShards)
	for shard := 0; shard < options.NumShards; shard++ {
		engine.indexerAddDocumentChannels[shard] = make(
			chan indexerAddDocumentRequest,
			options.IndexerBufferLength)
		engine.indexerLookupChannels[shard] = make(
			chan indexerLookupRequest,
			options.IndexerBufferLength)
	}

	// 初始化排序器通道
	engine.rankerAddScoringFieldsChannels = make(
		[]chan rankerAddScoringFieldsRequest, options.NumShards)
	engine.rankerRankChannels = make(
		[]chan rankerRankRequest, options.NumShards)
	engine.rankerRemoveScoringFieldsChannels = make(
		[]chan rankerRemoveScoringFieldsRequest, options.NumShards)
	for shard := 0; shard < options.NumShards; shard++ {
		engine.rankerAddScoringFieldsChannels[shard] = make(
			chan rankerAddScoringFieldsRequest,
			options.RankerBufferLength)
		engine.rankerRankChannels[shard] = make(
			chan rankerRankRequest,
			options.RankerBufferLength)
		engine.rankerRemoveScoringFieldsChannels[shard] = make(
			chan rankerRemoveScoringFieldsRequest,
			options.RankerBufferLength)
	}

	// 初始化持久化存储通道
	if engine.initOptions.UsePersistentStorage {
		engine.persistentStorageIndexDocumentChannel = make(
			chan persistentStorageIndexDocumentRequest,
			engine.initOptions.PersistentStorageShards)
		engine.persistentStorageInitChannel = make(
			chan bool, engine.initOptions.PersistentStorageShards)
	}

	// 启动分词器
	for iThread := 0; iThread < options.NumSegmenterThreads; iThread++ {
		go engine.segmenterWorker()
	}

	// 启动索引器和排序器
	for shard := 0; shard < options.NumShards; shard++ {
		go engine.indexerAddDocumentWorker(shard)
		go engine.rankerAddScoringFieldsWorker(shard)
		go engine.rankerRemoveScoringFieldsWorker(shard)

		for i := 0; i < options.NumIndexerThreadsPerShard; i++ {
			go engine.indexerLookupWorker(shard)
		}
		for i := 0; i < options.NumRankerThreadsPerShard; i++ {
			go engine.rankerRankWorker(shard)
		}
	}

	// 启动持久化存储工作协程
	if engine.initOptions.UsePersistentStorage {
		err := os.MkdirAll(engine.initOptions.PersistentStorageFolder, 0700)
		if err != nil {
			log.Fatal("无法创建目录", engine.initOptions.PersistentStorageFolder)
		}

		// 打开或者创建数据库
		engine.dbs = make([]*kv.DB, engine.initOptions.PersistentStorageShards)
		for shard := 0; shard < engine.initOptions.PersistentStorageShards; shard++ {
			dbPath := engine.initOptions.PersistentStorageFolder + "/persist." + strconv.Itoa(shard) + "-of-" + strconv.Itoa(engine.initOptions.PersistentStorageShards)
			db, err := utils.OpenOrCreateKv(dbPath, &kv.Options{})
			if db == nil || err != nil {
				log.Fatal("无法打开数据库", dbPath, ": ", err)
			}
			engine.dbs[shard] = db
		}

		// 从数据库中恢复
		for shard := 0; shard < engine.initOptions.PersistentStorageShards; shard++ {
			go engine.persistentStorageInitWorker(shard)
		}

		// 等待恢复完成
		for shard := 0; shard < engine.initOptions.PersistentStorageShards; shard++ {
			<-engine.persistentStorageInitChannel
		}
		for {
			runtime.Gosched()
			if engine.numIndexingRequests == engine.numDocumentsIndexed {
				break
			}
		}

		for shard := 0; shard < engine.initOptions.PersistentStorageShards; shard++ {
			go engine.persistentStorageIndexDocumentWorker(shard)
		}
	}

	atomic.AddUint64(&engine.numDocumentsStored, engine.numIndexingRequests)
}

// 将文档加入索引
//
// 输入参数：
// 	docId	标识文档编号，必须唯一
//	data	见DocumentIndexData注释
//
// 注意：
//      1. 这个函数是线程安全的，请尽可能并发调用以提高索引速度
// 	2. 这个函数调用是非同步的，也就是说在函数返回时有可能文档还没有加入索引中，因此
//         如果立刻调用Search可能无法查询到这个文档。强制刷新索引请调用FlushIndex函数。
func (engine *Engine) IndexDocument(docId uint64, data types.DocumentIndexData) {
	engine.internalIndexDocument(docId, data)
	if engine.initOptions.UsePersistentStorage {
		engine.persistentStorageIndexDocumentChannel <- persistentStorageIndexDocumentRequest{docId: docId, data: data}
	}
}

func (engine *Engine) internalIndexDocument(docId uint64, data types.DocumentIndexData) {
	if !engine.initialized {
		log.Fatal("必须先初始化引擎")
	}

	atomic.AddUint64(&engine.numIndexingRequests, 1)
	hash := murmur.Murmur3([]byte(fmt.Sprint("%d%s", docId, data.Content)))
	engine.segmenterChannel <- segmenterRequest{
		docId: docId, hash: hash, data: data}
}

// 将文档从索引中删除
//
// 输入参数：
// 	docId	标识文档编号，必须唯一
//
// 注意：这个函数仅从排序器中删除文档的自定义评分字段，索引器不会发生变化。所以
// 你的自定义评分字段必须能够区别评分字段为nil的情况，并将其从排序结果中删除。
func (engine *Engine) RemoveDocument(docId uint64) {
	if !engine.initialized {
		log.Fatal("必须先初始化引擎")
	}

	for shard := 0; shard < engine.initOptions.NumShards; shard++ {
		engine.rankerRemoveScoringFieldsChannels[shard] <- rankerRemoveScoringFieldsRequest{docId: docId}
	}

	if engine.initOptions.UsePersistentStorage {
		// 从数据库中删除
		for shard := 0; shard < engine.initOptions.PersistentStorageShards; shard++ {
			go engine.persistentStorageRemoveDocumentWorker(docId, shard)
		}
	}
}

// 阻塞等待直到所有索引添加完毕
func (engine *Engine) FlushIndex() {
	for {
		runtime.Gosched()
		if engine.numIndexingRequests == engine.numDocumentsIndexed &&
			(!engine.initOptions.UsePersistentStorage ||
				engine.numIndexingRequests == engine.numDocumentsStored) {
			return
		}
	}
}

// 查找满足搜索条件的文档，此函数线程安全
func (engine *Engine) Search(request types.SearchRequest) (output types.SearchResponse) {
	if !engine.initialized {
		log.Fatal("必须先初始化引擎")
	}

	var rankOptions types.RankOptions
	if request.RankOptions == nil {
		rankOptions = *engine.initOptions.DefaultRankOptions
	} else {
		rankOptions = *request.RankOptions
	}
	if rankOptions.ScoringCriteria == nil {
		rankOptions.ScoringCriteria = engine.initOptions.DefaultRankOptions.ScoringCriteria
	}

	// 收集关键词
	tokens := []string{}
	if request.Text != "" {
		querySegments := engine.segmenter.Segment([]byte(request.Text))
		for _, s := range querySegments {
			token := s.Token().Text()
			if !engine.stopTokens.IsStopToken(token) {
				tokens = append(tokens, s.Token().Text())
			}
		}
	} else {
		for _, t := range request.Tokens {
			tokens = append(tokens, t)
		}
	}

	// 建立排序器返回的通信通道
	rankerReturnChannel := make(
		chan rankerReturnRequest, engine.initOptions.NumShards)

	// 生成查找请求
	lookupRequest := indexerLookupRequest{
		tokens:              tokens,
		labels:              request.Labels,
		docIds:              request.DocIds,
		options:             rankOptions,
		rankerReturnChannel: rankerReturnChannel}

	// 向索引器发送查找请求
	for shard := 0; shard < engine.initOptions.NumShards; shard++ {
		engine.indexerLookupChannels[shard] <- lookupRequest
	}

	// 从通信通道读取排序器的输出
	rankOutput := types.ScoredDocuments{}
	timeout := request.Timeout
	isTimeout := false
	if timeout <= 0 {
		// 不设置超时
		for shard := 0; shard < engine.initOptions.NumShards; shard++ {
			rankerOutput := <-rankerReturnChannel
			for _, doc := range rankerOutput.docs {
				rankOutput = append(rankOutput, doc)
			}
		}
	} else {
		// 设置超时
		deadline := time.Now().Add(time.Nanosecond * time.Duration(NumNanosecondsInAMillisecond*request.Timeout))
		for shard := 0; shard < engine.initOptions.NumShards; shard++ {
			select {
			case rankerOutput := <-rankerReturnChannel:
				for _, doc := range rankerOutput.docs {
					rankOutput = append(rankOutput, doc)
				}
			case <-time.After(deadline.Sub(time.Now())):
				isTimeout = true
				break
			}
		}
	}

	// 再排序
	if rankOptions.ReverseOrder {
		sort.Sort(sort.Reverse(rankOutput))
	} else {
		sort.Sort(rankOutput)
	}

	// 准备输出
	output.Tokens = tokens
	var start, end int
	if rankOptions.MaxOutputs == 0 {
		start = utils.MinInt(rankOptions.OutputOffset, len(rankOutput))
		end = len(rankOutput)
	} else {
		start = utils.MinInt(rankOptions.OutputOffset, len(rankOutput))
		end = utils.MinInt(start+rankOptions.MaxOutputs, len(rankOutput))
	}
	output.Docs = rankOutput[start:end]
	output.Timeout = isTimeout
	return
}

// 关闭引擎
func (engine *Engine) Close() {
	engine.FlushIndex()
	if engine.initOptions.UsePersistentStorage {
		for _, db := range engine.dbs {
			db.Close()
		}
	}
}

// 从文本hash得到要分配到的shard
func (engine *Engine) getShard(hash uint32) int {
	return int(hash - hash/uint32(engine.initOptions.NumShards)*uint32(engine.initOptions.NumShards))
}