当执行Hits htis = search(query);这一行代码的时候,到底中间经过了怎样的过程,最终使得我们获取到了含有检索结果的集合Hits hits呢?
这里,以最简单的检索为例,追踪并理解Lucene(2.2.0版本)获取到检索结果的过程。
1、IndexSearcher继承自Searcher类的最简单的search方法,如下所示:
public final Hits search(Query query) throws IOException {
return search(query, (Filter)null);
}
这里,调用了Searcher类的带有两个参数的search方法,返回Hits,如下所示:
public Hits search(Query query, Filter filter) throws IOException {
return new Hits(this, query, filter);
}
这时,是通过根据传递进来的Query、Filter(简单地考虑,Filter=null)和实例化的Searcher来构造一个Hits的,其实,没有那么简单,想也能想得到,一定是在Hits类中,通过Searcher实例进行了具体的检索过程。
Hits类拥有如下成员:
private Weight weight;
private Searcher searcher;
private Filter filter = null;
private Sort sort = null;
private int length; // 检索到的匹配的Document的个数
private Vector hitDocs = new Vector(); // 最终将检索命中的Document(封装到Hit中,包含了一个Document的丰富信息)放到hitDocs中,取出来呈现给检索的用户
private HitDoc first; // head of LRU cache
private HitDoc last; // tail of LRU cache
private int numDocs = 0; // number cached
private int maxDocs = 200; // max to cache
2、在Hits类中,只有构造好了含有检索结果的Hits才是最终的检索目标,如下所示:
Hits(Searcher s, Query q, Filter f) throws IOException {
weight = q.weight(s);
searcher = s;
filter = f;
getMoreDocs(50); // 缓存检索结果50*2=100个
}
因为一个Query实例需要被多次使用,故而使用Weight来记录Query的状态。重点看在Hits类调用getMoreDocs方法,该方法实现如下:
private final void getMoreDocs(int min) throws IOException {
if (hitDocs.size() > min) { // hitDocs.size() <min=50,说明缓存的结果数量小于预计要加入到缓存中的结果的数量,因此不执行该if分支,无需改变min(缓存容量)的大小
min = hitDocs.size();
}
int n = min * 2; // 由50变成100,目的是:直接扩充缓存为原来的2倍,缓存双倍的检索结果以备用户直接从缓存中提取检索结果;间接地一次性为HitQueue(优先级队列)分配大小,防止频繁分配增加系统开销
TopDocs topDocs = (sort == null) ? searcher.search(weight, filter, n) : searcher.search(weight, filter, n, sort);
length = topDocs.totalHits;
ScoreDoc[] scoreDocs = topDocs.scoreDocs;
float scoreNorm = 1.0f;
if (length > 0 && topDocs.getMaxScore() > 1.0f) {
scoreNorm = 1.0f / topDocs.getMaxScore();
}
int end = scoreDocs.length < length ? scoreDocs.length : length;
for (int i = hitDocs.size(); i < end; i++) {
hitDocs.addElement(new HitDoc(scoreDocs[i].score * scoreNorm,
scoreDocs[i].doc));
}
}
第一次调用该方法的时候,作为Hits类的一个成员private Vector hitDocs = new Vector();,它是用作缓存检索结果的。
当sort == null)的时候,执行searcher.search(weight, filter, n),这时,又回到了IndexSearcher类中,执行含有三个参数的重载search方法(见下文),返回检索结果存放于TopDocs topDocs中。关于TopDocs有必要熟悉一下:
public class TopDocs implements java.io.Serializable {
public int totalHits;
public ScoreDoc[] scoreDocs;
private float maxScore;
public float getMaxScore() {
return maxScore;
}
public void setMaxScore(float maxScore) {
this.maxScore=maxScore;
}
TopDocs(int totalHits, ScoreDoc[] scoreDocs, float maxScore) {
this.totalHits = totalHits;
this.scoreDocs = scoreDocs;
this.maxScore = maxScore;
}
}
totalHits成员是本次查询Query检索到的Hits的总数;maxScore成员是最大分数。
ScoreDoc[]成员就是从所有满足查询Query的得分不为0的Document的数组,根据要求选择前n个Docunent返回,它包含Document的编号和得分这两个成员:
package org.apache.lucene.search;
public class ScoreDoc implements java.io.Serializable {
public float score;
public int doc;
public ScoreDoc(int doc, float score) {
this.doc = doc;
this.score = score;
}
}
接着,根据返回的TopDocs topDocs取得其长度length = topDocs.totalHits;用来计算得分标准化因子,以对检索结果按照得分进行排序,并把相关的检索结果缓存到hitDocs中。
3、在IndexSearcher类中,根据searcher.search(weight, filter, n),执行public TopDocs search(Weight weight, Filter filter, final int nDocs)方法,如下所示:
public TopDocs search(Weight weight, Filter filter, final int nDocs)
throws IOException {
if (nDocs <= 0) // nDocs=n=2*50=100
throw new IllegalArgumentException("nDocs must be > 0");
TopDocCollector collector = new TopDocCollector(nDocs);
search(weight, filter, collector);
return collector.topDocs();
}
上面,构造了一个TopDocCollector实例,使用如下构造方法:
public TopDocCollector(int numHits) {
this(numHits, new HitQueue(numHits));
}
调用重载的构造方法TopDocCollector(int numHits, PriorityQueue hq),初始化一个Hit的优先级队列,大小为100。其实,关于Hit的优先级队列就是这样的:对于ScoreDoc hitA和ScoreDoc hitB,如果hitA.score>=hitB.score,则选择hitA入队列。
根据构造的TopDocCollector collector,再次调用IndexSearcher类的另一个不同的重载的search方法search(weight, filter, collector);,将检索结果存放到了TopDocCollector collector中,最后根据TopDocCollector collector返回TopDocs。
关于search(weight, filter, collector);调用,实现如下所示:
public void search(Weight weight, Filter filter,
final HitCollector results) throws IOException {
HitCollector collector = results;
if (filter != null) { // 我们一直设定Filter=null,该分支不执行
final BitSet bits = filter.bits(reader);
collector = new HitCollector() {
public final void collect(int doc, float score) {
if (bits.get(doc)) { // skip docs not in bits
results.collect(doc, score);
}
}
};
}
Scorer scorer = weight.scorer(reader);
if (scorer == null)
return;
scorer.score(collector);
}
先看Scorer scorer,通过weight的scorer方法获取到一个Scorer,在内部类org.apache.lucene.search.TermQuery.TermWeight中可以看到TermWeight的score方法如何实现的:
public Scorer scorer(IndexReader reader) throws IOException {
TermDocs termDocs = reader.termDocs(term);
if (termDocs == null)
return null;
return new TermScorer(this, termDocs, similarity,reader.norms(term.field()));
}
通过IndexReader reader获取到一个TermDocs,其中TermDocs是与检索相关的(即查询中使用Term构造了查询)包含Term的所有<document, frequency>对,document为Document的编号,frequency为Term在该Document中出现的频率(次数)。
执行reader.termDocs(term);时,调用了IndexReader类的termDocs方法,如下所示:
public TermDocs termDocs(Term term) throws IOException {
ensureOpen();
TermDocs termDocs = termDocs();
termDocs.seek(term);
return termDocs;
}
TermScorer是Scorer的子类,它有如下一些成员:
private Weight weight;
private TermDocs termDocs;
private byte[] norms;
private float weightValue;
private int doc;
private final int[] docs = new int[32]; // buffered doc numbers
private final int[] freqs = new int[32]; // buffered term freqs
private int pointer;
private int pointerMax;
private static final int SCORE_CACHE_SIZE = 32;
private float[] scoreCache = new float[SCORE_CACHE_SIZE];
通过这些成员,我们能够知道返回一个TermScorer对象都包含哪些内容,从而为使用Scorer scorer = weight.scorer(reader);便于理解。
weight.scorer(reader) 返回的是一个Scorer,它是用来迭代得分与查询匹配的Docuemnt的。
最后,执行scorer.score(collector);,最终的检索结果可以直接从一个HitCollector collector中提取出来,返回最终的检索结果。
Scorer类的score方法如下:
public void score(HitCollector hc) throws IOException {
while (next()) {
hc.collect(doc(), score());
}
}
再看TopDocCollector(extends HitCollector)类的collect方法的实现:
public void collect(int doc, float score) {
if (score > 0.0f) {
totalHits++;
if (hq.size() < numHits || score >= minScore) {
hq.insert(new ScoreDoc(doc, score));
minScore = ((ScoreDoc)hq.top()).score; // maintain minScore
}
}
}
根据Document的编号和得分,调整Hit的优先级队列,获得满足条件的Docuemt的集合,最终构造出ScoreDoc,实际上是得到了一个ScoreDoc[]数组,从而访问TopDocs的这个ScoreDoc[]成员,就返回了最终检索的结果集合。