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Lucene 中的 IndexSearcher 提供了一整套完整的搜索体系，这套查询体系是建立在 SpanQuery 类的基础上。SpanQuery 类大致的反映了 Lucene 的 Query 类体系。今天我们一起来学习学习 SpanQuery 类的一些子类和使用实例。
SpanQuery 是指 Field 域（字段）中的起始语汇单元和终止语汇单元的位置。SpanQuery 中的一些常用的子类如下表所示：
| SpanQuery类型 | 描述 |
|---|---|
| FieldMaskingSpanQuery | 用于在多个域之间查询，即把另一个域看作某个域，从而看起来就像在同一个域里查询，因为 Lucene 默认某个条件只能作用在单个域上，不支持跨域查询，只能在同一个域里查询，所以有了 FieldMaskingSpanQuery |
| SpanTermQuery | 和其它跨度查询类型结合使用，单独使用时相当于 TermQuery，唯一的区别就是使用 SpanTermQuery 可以得到 Term 的 Span 跨度信息 |
| SpanNearQuery | 用来匹配两个 Term 之间的跨度的，即一个 Term 经过几个跨度可以到达另一个 Term，slop 为跨度因子，用来限制两个 Term 之间的最大跨度。还有一个 inOrder 参数，它用来设置是否允许进行倒序跨度，什么意思？即 TermA 到 TermB 不一定是从左到右去匹配也可以从右到左，而从右到左就是倒序，inOrder 为 true 即表示 order（顺序）很重要不能倒序去匹配必须正向去匹配，false 则反之。注意停用词不在 slop 统计范围内 |
| SpanFirstQuery | 表示对出现在一个域中的[0, n]范围内的 term 项进行的匹配查询，关键是n指定了查询的 term 出现范围的上限 |
| SpanContainingQuery | 返回在另一个范围内的查询匹配结果，big 和 little 的子句可以是任何 span 类型查询。在包含 little 匹配中从 big 匹配跨度返回。例如“a beautiful and boring world”，big 查询是 SpanNearQuery(SpanTermQuery(“beautiful”), SpanTermQuery(“world”)).setSlop(2)，而 little 查询是 SpanTermQuery(“boring”)，则该 Doc 命中，并从 big 匹配跨度返回，即 big 优先级高 |
| SpanWithinQuery | 与 SpanContainingQuery 类似，只不过是从 little 匹配跨度返回，换句话说，SpanContainingQuery 是 big 查询优先级更高，而 SpanWithinQuery 是 little 查询优先级更高。也许英文说的更清晰，In clear, the SpanContainingQuery will keep matches that contain another Spans, while the SpanWithinQuery will keep matches that are contained within another Spans. |
| SpanNotQuery | 使用场景是当使用 SpanNearQuery 时，如果两个 Term 从 TermA 到 TermB 有多种情况，即可能出现 TermA 或者 TermB 在索引中重复出现，则可能有多种情况，SpanNotQuery 就是用来限制 TermA 和 TermB 之间不存在 TermC，从而排除一些情况，实现更精确的控制 |
| SpanOrQuery | 这个查询会嵌套一些子查询，子查询之间的逻辑关系为或 |
关于这些 SpanQuery 的使用，我们直接上代码好了！
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.analysis.core.WhitespaceAnalyzer;
import org.apache.lucene.analysis.tokenattributes.OffsetAttribute;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.document.StringField;
import org.apache.lucene.document.TextField;
import org.apache.lucene.index.*;
import org.apache.lucene.search.*;
import org.apache.lucene.search.spans.*;
import org.apache.lucene.store.RAMDirectory;
import org.junit.After;
import org.junit.Assert;
import org.junit.Before;
import org.junit.Test;
import java.io.IOException;
import java.io.StringReader;
public class SpanQueryDemo {
private RAMDirectory directory;
private IndexSearcher indexSearcher;
private IndexReader indexReader;
private SpanTermQuery quick;
private SpanTermQuery brown;
private SpanTermQuery red;
private SpanTermQuery fox;
private SpanTermQuery lazy;
private SpanTermQuery sleepy;
private SpanTermQuery dog;
private SpanTermQuery cat;
private Analyzer analyzer;
private IndexWriter indexWriter;
private IndexWriterConfig indexWriterConfig;
@Before
public void setUp() throws IOException {
directory = new RAMDirectory();
analyzer = new WhitespaceAnalyzer();
indexWriterConfig = new IndexWriterConfig(analyzer);
indexWriterConfig.setOpenMode(IndexWriterConfig.OpenMode.CREATE_OR_APPEND);
indexWriter = new IndexWriter(directory, indexWriterConfig);
Document document = new Document();
//TextField使用Store.YES时索引文档、频率、位置信息
document.add(new TextField("f", "What's amazing, the quick brown fox jumps over the lazy dog", Field.Store.YES));
indexWriter.addDocument(document);
document = new Document();
document.add(new TextField("f", "Wow! the quick red fox jumps over the sleepy cat", Field.Store.YES));
indexWriter.addDocument(document);
indexWriter.commit();
indexSearcher = new IndexSearcher(DirectoryReader.open(directory));
indexReader = indexSearcher.getIndexReader();
quick = new SpanTermQuery(new Term("f", "quick"));
brown = new SpanTermQuery(new Term("f", "brown"));
red = new SpanTermQuery(new Term("f", "red"));
fox = new SpanTermQuery(new Term("f", "fox"));
lazy = new SpanTermQuery(new Term("f", "lazy"));
dog = new SpanTermQuery(new Term("f", "dog"));
sleepy = new SpanTermQuery(new Term("f", "sleepy"));
cat = new SpanTermQuery(new Term("f", "cat"));
}
@After
public void setDown() {
if (indexWriter != null && indexWriter.isOpen()) {
try {
indexWriter.close();
} catch (IOException e) {
System.out.println(e);
}
}
}
private void assertOnlyBrownFox(Query query) throws IOException {
TopDocs search = indexSearcher.search(query, 10);
Assert.assertEquals(1, search.totalHits);
Assert.assertEquals("wrong doc", 0, search.scoreDocs[0].doc);
}
private void assertBothFoxes(Query query) throws IOException {
TopDocs search = indexSearcher.search(query, 10);
Assert.assertEquals(2, search.totalHits);
}
private void assertNoMatches(Query query) throws IOException {
TopDocs search = indexSearcher.search(query, 10);
Assert.assertEquals(0, search.totalHits);
}
/**
* 输出跨度查询的结果
*
* @param query
* @throws IOException
*/
private void dumpSpans(SpanQuery query) throws IOException {
SpanWeight weight = query.createWeight(indexSearcher, true);
Spans spans = weight.getSpans(indexReader.getContext().leaves().get(0), SpanWeight.Postings.POSITIONS);
System.out.println(query);
TopDocs search = indexSearcher.search(query, 10);
float[] scores = new float[2];
for (ScoreDoc sd : search.scoreDocs) {
scores[sd.doc] = sd.score;
}
int numSpans = 0;
//处理所有跨度
while (spans.nextDoc() != Spans.NO_MORE_DOCS) {
while (spans.nextStartPosition() != Spans.NO_MORE_POSITIONS) {
numSpans++;
int id = spans.docID();
//检索文档
Document doc = indexReader.document(id);
//重新分析文本
TokenStream stream = analyzer.tokenStream("contents", new StringReader(doc.get("f")));
stream.reset();
OffsetAttribute offsetAttribute = stream.addAttribute(OffsetAttribute.class);
int i = 0;
StringBuilder sb = new StringBuilder();
sb.append(" ");
//处理所有语汇单元
while (stream.incrementToken()) {
if (i == spans.startPosition()) {
sb.append("<");
}
sb.append(offsetAttribute.toString());
if (i + 1 == spans.endPosition()) {
sb.append(">");
}
sb.append(" ");
i++;
}
sb.append("(").append(scores[id]).append(")");
System.out.println(sb.toString());
stream.close();
}
if (numSpans == 0) {
System.out.println(" No Spans");
}
}
}
@Test
public void testSpanTermQuery() throws IOException {
assertOnlyBrownFox(brown);
dumpSpans(brown);
dumpSpans(new SpanTermQuery(new Term("f", "the")));
dumpSpans(new SpanTermQuery(new Term("f", "fox")));
}
/**
* SpanFirstQuery可以对出现在域中前面某位置的跨度进行查询
*/
@Test
public void testSpanFirstQuery() throws IOException {
SpanFirstQuery spanFirstQuery = new SpanFirstQuery(brown, 2);
assertNoMatches(spanFirstQuery);
dumpSpans(spanFirstQuery);
//设置从前面开始10个跨度查找brown，一个切分结果是一个跨度，使用的是空格分词器
spanFirstQuery = new SpanFirstQuery(brown, 5);
dumpSpans(spanFirstQuery);
assertOnlyBrownFox(spanFirstQuery);
}
@Test
public void testSpanNearQuery() throws IOException {
SpanQuery[] queries = new SpanQuery[]{quick, brown, dog};
SpanNearQuery spanNearQuery = new SpanNearQuery(queries, 0, true);
assertNoMatches(spanNearQuery);
dumpSpans(spanNearQuery);
spanNearQuery = new SpanNearQuery(queries, 4, true);
assertNoMatches(spanNearQuery);
dumpSpans(spanNearQuery);
spanNearQuery = new SpanNearQuery(queries, 5, true);
assertOnlyBrownFox(spanNearQuery);
dumpSpans(spanNearQuery);
//将inOrder设置为false，那么就不会考虑顺序，只要两者中间不超过三个就可以检索到
spanNearQuery = new SpanNearQuery(new SpanQuery[]{lazy, fox}, 3, false);
assertOnlyBrownFox(spanNearQuery);
dumpSpans(spanNearQuery);
//在考虑顺序的情况下，是检索不到的
spanNearQuery = new SpanNearQuery(new SpanQuery[]{lazy, fox}, 3, true);
assertNoMatches(spanNearQuery);
dumpSpans(spanNearQuery);
PhraseQuery phraseQuery = new PhraseQuery.Builder().add(new Term("f", "lazy")).add(new Term("f", "fox")).setSlop(4).build();
assertNoMatches(phraseQuery);
PhraseQuery phraseQuery1 = new PhraseQuery.Builder().setSlop(5).add(phraseQuery.getTerms()[0]).add(phraseQuery.getTerms()[1]).build();
assertOnlyBrownFox(phraseQuery1);
}
@Test
public void testSpanNotQuery() throws IOException {
//设置slop为1
SpanNearQuery quickFox = new SpanNearQuery(new SpanQuery[]{quick, fox}, 1, true);
assertBothFoxes(quickFox);
dumpSpans(quickFox);
//第一个参数表示要包含的跨度对象，第二个参数则表示要排除的跨度对象
SpanNotQuery quickFoxDog = new SpanNotQuery(quickFox, dog);
assertBothFoxes(quickFoxDog);
dumpSpans(quickFoxDog);
//下面把red排除掉，那么就只能查到一条记录
SpanNotQuery noQuickRedFox = new SpanNotQuery(quickFox, red);
assertOnlyBrownFox(noQuickRedFox);
dumpSpans(noQuickRedFox);
}
@Test
public void testSpanOrQuery() throws IOException {
SpanNearQuery quickFox = new SpanNearQuery(new SpanQuery[]{quick, fox}, 1, true);
SpanNearQuery lazyDog = new SpanNearQuery(new SpanQuery[]{lazy, dog}, 0, true);
SpanNearQuery sleepyCat = new SpanNearQuery(new SpanQuery[]{sleepy, cat}, 0, true);
SpanNearQuery quickFoxNearLazyDog = new SpanNearQuery(new SpanQuery[]{quickFox, lazyDog}, 3, true);
assertOnlyBrownFox(quickFoxNearLazyDog);
dumpSpans(quickFoxNearLazyDog);
SpanNearQuery quickFoxNearSleepyCat = new SpanNearQuery(new SpanQuery[]{quickFox, sleepyCat}, 3, true);
dumpSpans(quickFoxNearSleepyCat);
SpanOrQuery or = new SpanOrQuery(new SpanQuery[]{quickFoxNearLazyDog, quickFoxNearSleepyCat});
assertBothFoxes(or);
dumpSpans(or);
}
/**
* 测试安全过滤
*
* @throws IOException
*/
@Test
public void testSecurityFilter() throws IOException {
Document document = new Document();
document.add(new StringField("owner", "eric", Field.Store.YES));
document.add(new TextField("keywords", "A B of eric", Field.Store.YES));
indexWriter.addDocument(document);
document = new Document();
document.add(new TextField("owner", "jobs", Field.Store.YES));
document.add(new TextField("keywords", "A B of jobs", Field.Store.YES));
indexWriter.addDocument(document);
document.add(new TextField("owner", "jack", Field.Store.YES));
document.add(new TextField("keywords", "A B of jack", Field.Store.YES));
indexWriter.addDocument(document);
indexWriter.commit();
TermQuery termQuery = new TermQuery(new Term("owner", "eric"));
TermQuery termQuery1 = new TermQuery(new Term("keywords", "A"));
//把FILTER看做是Like即可，也就是说owner必须是eric的才允许检索到
Query query = new BooleanQuery.Builder().add(termQuery1, BooleanClause.Occur.MUST).add(termQuery,
BooleanClause.Occur.FILTER).build();
System.out.println(query);
indexSearcher = new IndexSearcher(DirectoryReader.open(directory));
TopDocs search = indexSearcher.search(query, 10);
Assert.assertEquals(1, search.totalHits);
//如果不加安全过滤的话，那么应该检索到三条记录
query = new BooleanQuery.Builder().add(termQuery1, BooleanClause.Occur.MUST).build();
System.out.println(query);
search = indexSearcher.search(query, 10);
Assert.assertEquals(3, search.totalHits);
String keywords = indexSearcher.doc(search.scoreDocs[0].doc).get("keywords");
System.out.println("使用Filter查询：" + keywords);
//使用BooleanQuery可以实现同样的功能
BooleanQuery booleanQuery = new BooleanQuery.Builder().add(termQuery,
BooleanClause.Occur.MUST).add(termQuery1, BooleanClause.Occur.MUST).build();
search = indexSearcher.search(booleanQuery, 10);
Assert.assertEquals(1, search.totalHits);
System.out.println("使用BooleanQuery查询：" + indexSearcher.doc(search.scoreDocs[0].doc).get("keywords"));
}
}
有人说我这些案例都是哪里来的，答案就是官方文档。所以想要学好一门新框架，看官方文档就可以了。
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本文原文出处：业余草： » Lucene 实战教程第十二章详解 Lucene 的高级搜索技术