Lucene查询对象浅析（一）
Lucene作为一个开源的搜索工具包，它为开发人员提供了丰富的查询方法，总结如下：
第一种：TermQuery.TermQuery是Lucene里面最基本的一种原子查询。开发人员可以通过它来检索索引中含有指定词条的Document。代码如下：
public static void main(String[] args) throws IOException {
createIndex();
termQuery();
}
private static void createIndex() throws IOException {
IndexWriter writer = new IndexWriter(STORE_PATH,
new StandardAnalyzer(), true);
writer.setUseCompoundFile(false);
Document doc1 = new Document();
Document doc2 = new Document();
Field field = new Field("PostTitle", "Lucene开发浅谈", Field.Store.YES,
Field.Index.TOKENIZED);
Field field1 = new Field("PostContent", "Lucene是一个开源的搜索工具包",
Field.Store.YES, Field.Index.TOKENIZED);
doc1.add(field);
doc1.add(field1);
Field field2 = new Field("PostTitle", "云计算浅谈", Field.Store.YES,
Field.Index.TOKENIZED);
Field field3 = new Field("PostContent",
"云计算是一种基于 Web 的服务,它使得普通计算机拥有超级计算机的能力", Field.Store.NO,
Field.Index.TOKENIZED);
doc2.add(field2);
doc2.add(field3);
writer.addDocument(doc1);
writer.addDocument(doc2);
writer.close();
}
private static void termQuery() throws IOException {
IndexSearcher searcher = new IndexSearcher(STORE_PATH);
Term term = new Term("PostContent", "lucene");
Query termQuery = new TermQuery(term);
Hits hits = searcher.search(termQuery);
System.out.println("TermQuery demo------");
System.out.println("hits.length()==" + hits.length());
for (int i = 0; i < hits.length(); i++) {
System.out.println(hits.doc(i));
}
}
运行结果如下：
TermQuery demo------ hits.length()==1 Document<stored/uncompressed,indexed,tokenized<PostTitle:Lucene开发浅谈> stored/uncompressed,indexed,tokenized<PostContent:Lucene是一个开源的搜索工具包>>
第二种：BooleanQuery。布尔查询其实就是将各种查询的结果再进行布尔运算，最后在得到查询结果。其中具体的组合方式有如下几种：
1 MUST,MUST
2 MUST,MUST_NOT
3 MUST_SHOULD
4 MUST_NOT,SHOULD.
5 SHOULD,SHOULD
6 MUST_NOT,MUST_NOT
具体代码如下：
public static void main(String[] args) throws IOException {
createIndex();
booleanQuery();
}
private static void booleanQuery() throws IOException {
IndexSearcher searcher = new IndexSearcher(STORE_PATH);
Term term1 = new Term("PostTitle", "谈");
Term term2 = new Term("PostContent", "源");
TermQuery termquery1 = new TermQuery(term1);
TermQuery termquery2 = new TermQuery(term2);
BooleanQuery query = new BooleanQuery();
query.add(termquery1, BooleanClause.Occur.MUST);
query.add(termquery2, BooleanClause.Occur.MUST);
Hits hits = searcher.search(query);
System.out.println("BooleanQuery demo with MUST and MUST -------");
System.out.println("hits.length()==" + hits.length());
for (int i = 0; i < hits.length(); i++) {
System.out.println(hits.doc(i));
}
System.out.println("-----------------------------------");
BooleanQuery query1 = new BooleanQuery();
query1.add(termquery1, BooleanClause.Occur.MUST);
query1.add(termquery2, BooleanClause.Occur.MUST_NOT);
Hits hits1 = searcher.search(query1);
System.out.println("BooleanQuery demo with MUST and MUST_NOT -------");
System.out.println("hits.length()==" + hits1.length());
for (int i = 0; i < hits1.length(); i++) {
System.out.println(hits1.doc(i));
}
System.out.println("-----------------------------------");
BooleanQuery query2 = new BooleanQuery();
query2.add(termquery1, BooleanClause.Occur.SHOULD);
query2.add(termquery2, BooleanClause.Occur.MUST_NOT);
Hits hits2 = searcher.search(query2);
System.out.println("BooleanQuery demo with SHOULD and MUST_NOT -------");
System.out.println("hits.length()==" + hits2.length());
for (int i = 0; i < hits2.length(); i++) {
System.out.println(hits2.doc(i));
}
System.out.println("-----------------------------------");
Term term3 = new Term("PostTitle","lucene");
Term term4 = new Term("PostContent","云");
TermQuery termquery3 = new TermQuery(term3);
TermQuery termquery4 = new TermQuery(term4);
BooleanQuery query3 = new BooleanQuery();
query3.add(termquery3, BooleanClause.Occur.SHOULD);
query3.add(termquery4, BooleanClause.Occur.SHOULD);
Hits hits3 = searcher.search(query3);
System.out.println("BooleanQuery demo with SHOULD and SHOULD -------");
System.out.println("hits.length()==" + hits3.length());
for (int i = 0; i < hits3.length(); i++) {
System.out.println(hits3.doc(i));
}
}
运行结果如下：
BooleanQuery demo with MUST and MUST ------- hits.length()==1 Document<stored/uncompressed,indexed,tokenized<PostTitle:Lucene开发浅谈> stored/uncompressed,indexed,tokenized<PostContent:Lucene是一个开源的搜索工具包>> ----------------------------------- BooleanQuery demo with MUST and MUST_NOT ------- hits.length()==1 Document<stored/uncompressed,indexed,tokenized<PostTitle:云计算浅谈>> ----------------------------------- BooleanQuery demo with SHOULD and MUST_NOT ------- hits.length()==1 Document<stored/uncompressed,indexed,tokenized<PostTitle:云计算浅谈>> ----------------------------------- BooleanQuery demo with SHOULD and SHOULD ------- hits.length()==2 Document<stored/uncompressed,indexed,tokenized<PostTitle:Lucene开发浅谈> stored/uncompressed,indexed,tokenized<PostContent:Lucene是一个开源的搜索工具包>> Document<stored/uncompressed,indexed,tokenized<PostTitle:云计算浅谈>>
其中Should和must组合时，检索结果为must的结果，当于must_not结合时就相当于must和must_not.
第三种：RangeQuery。范围查询顾名思意就是给定一个方位来查询，比如查询用户ID在“10001-10005”之间的用户等。具体的代码如下：
private static void rangeQuery() throws IOException {
IndexWriter writer = new IndexWriter(STORE_PATH,
new StandardAnalyzer(), true);
Field field1 = new Field("userID", "10001", Field.Store.YES,
Field.Index.TOKENIZED);
Field field2 = new Field("userID", "10002", Field.Store.YES,
Field.Index.TOKENIZED);
Field field3 = new Field("userID", "10003", Field.Store.YES,
Field.Index.TOKENIZED);
Field field4 = new Field("userID", "10004", Field.Store.YES,
Field.Index.TOKENIZED);
Field field5 = new Field("userID", "10005", Field.Store.YES,
Field.Index.TOKENIZED);
Document doc1 = new Document();
Document doc2 = new Document();
Document doc3 = new Document();
Document doc4 = new Document();
Document doc5 = new Document();
doc1.add(field1);
doc2.add(field2);
doc3.add(field3);
doc4.add(field4);
doc5.add(field5);
writer.addDocument(doc1);
writer.addDocument(doc2);
writer.addDocument(doc3);
writer.addDocument(doc4);
writer.addDocument(doc5);
writer.close();
IndexSearcher searcher = new IndexSearcher(STORE_PATH);
Term start = new Term("userID", "10001");
Term end = new Term("userID", "10002");
RangeQuery query = new RangeQuery(start, end, true);
Hits hits = searcher.search(query);
System.out.println("RangeQuery demo------");
System.out.println("hits.length()==" + hits.length());
for (int i = 0; i < hits.length(); i++) {
System.out.println(hits.doc(i));
}
}
运行结果如下：
RangeQuery demo------ hits.length()==5 Document<stored/uncompressed,indexed,tokenized<userID:10001>> Document<stored/uncompressed,indexed,tokenized<userID:10002>> Document<stored/uncompressed,indexed,tokenized<userID:10003>> Document<stored/uncompressed,indexed,tokenized<userID:10004>> Document<stored/uncompressed,indexed,tokenized<userID:10005>>
其中RangeQuery构造函数的第三个参数是用来指定是否包含边界值，如果是true，就是闭区间，如果为false则为开区间。