Lucene查询方式总结

--------------------------------------------------
IndexReader的设计
--------------------------------------------------
IndexReader的创建需要消耗大量内存空间,
所以通过将IndexReader设计出属性值，进行一次创建

整个项目周期就只有一个IndexReader

1.// IndexReader的设计

private static IndexReader reader = null;
2.在构造方法中对IndexReader进行初始化
// 创建indexReader
reader = IndexReader.open(directory);
3.创建getSearch()方法，返回IndexSearch
private static IndexSearcher getSearch() {
return new IndexSearcher(reader);
}
4.最后在使用IndexReader完毕后，只需要关闭IndexSearch
// 最后只需要关闭search

search.close();

PS：
因此此IndexReader属于单例模式，在IndexReader过程中如果改变IndexWriter的索引，IndexReader所search出的数据将不会改变，除非重新构建一个新的IndexReader
代码优化：
// 优化

try {if (reader == null) {reader = IndexReader.open(directory);//reader = IndexReader.open(directory,false);  //不设置为只读的reader} else {// 如果Index索引改变了将返回一个新的reader，否则将返回nullIndexReader read = IndexReader.openIfChanged(reader);if (read != null) {                //把原来的reader给close()掉reader.close();reader = read;}}return new IndexSearcher(reader);} catch (CorruptIndexException e) {e.printStackTrace();} catch (IOException e) {e.printStackTrace();}return null;

//因为此时Reader已经为全局范围，用reader也能删除文档
/*
 * 使用reader删除，会立即更新索引信息(但不建议)
*/

// reader.deleteDocuments(new Term("id","1"));// reader.close();

有时候整个项目周期中只有一个IndexWriter
这时候，IndexWriter就不能关闭
那么怎么提交呢？
使用IndexWriter.commit()方法提交对索引操作后的数据


--------------------------------------------------------
Directory的几种操作方式
--------------------------------------------------------
FSDirectory.open()。。系统会根据具体运行环境使用最佳方式打开一个Directory
new RAMDirectory()。。就是将索引存储在内存中。好处：速度快。坏处：不能持久化
RAMDirectory（Directory dir）。也可以将一个持久化好的directory放入内存中。


-------------------------------------------------------
lucene的搜索_TermRange等基本搜索
-------------------------------------------------------
1.创建IndexSearch
/*
* 创建IndexSearch的方法
*/

public IndexSearcher getSearch() {try {if (reader == null) {reader = IndexReader.open(directory);} else {IndexReader read = IndexReader.openIfChanged(reader);if (read != null) {reader.close();reader = read;}}return new IndexSearcher(reader);} catch (CorruptIndexException e) {e.printStackTrace();} catch (IOException e) {e.printStackTrace();}return null;}

2.查询的几种
======精确查询：

IndexSearcher search = getSearch();Query query = new TermQuery(new Term(field, name));TopDocs tds = search.search(query, num);for (ScoreDoc sdc : tds.scoreDocs) {   Document doc = search.doc(sdc.doc);}search.close();

======基于字符串的范围查询（TermRange）
// true表示闭区间

IndexSearcher search = getSearch();Query query = new TermRangeQuery(field, start, end, true, true);TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);

======基于数字的范围查询（NumericRangeQuery.new...)

IndexSearcher search = getSearch(); // true表示闭区间Query query = NumericRangeQuery.newIntRange(field, start, end,true, true);TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);

======PS:tds.totalHits是总记录数，与我们传入的num，没有任何关系
eg:
   // 基于范围的查询(参数：传入的field，开始字符，结束字符，显示数目)

public void SearchByTermRange(String field, String start, String end,int num) {try {IndexSearcher search = getSearch();// 范围查询// true表示闭区间（是否包含开始字符和结束字符，默认为true）Query query = new TermRangeQuery(field, start, end, true, true);TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}

-----------------------------------------------------------------
lucene的搜索_其他常用Query搜索
-----------------------------------------------------------------
======前缀搜索（prefixquery）

Query query = new PrefixQuery(new Term(field, value));

======通配符搜索（wildcardquery）

Query query = new WildcardQuery(new Term(field, value));

//使用方法

sutil.SearchByWildCard("name", "l*", 3);

在传入的value中可以使用通配符? 和 * 
？表示匹配一个字符，*表示匹配任意多个字符。可以在任何位置使用。


=======可以连接多个条件（BooleanQuery）

BooleanQuery query = new BooleanQuery();// Occur.Must表必须 //Occur.SHOULD表示可有可无 //Occur.MUST_NOT表示必须没有query.add(new TermQuery(new Term("name", "lili")), Occur.MUST);query.add(new TermQuery(new Term("content", "hello")), Occur.MUST);

=======短语查询（phrasequery）

PhraseQuery query = new PhraseQuery();// setSlop()设置跳数,及两个单词之间有几个单词query.setSlop(1);// 设置field字段，即哪两个单词// 第一个termquery.add(new Term("content", "i"));// 产生距离后的第二个termquery.add(new Term("content", "basketball"));

======模糊查询（FuzzyQuery）
//会匹配有一个字符出错的情况

Query query=new FuzzyQuery(new Term("name", "mirk"));

-------------------------------------------------------------
lucene的搜索_基于QueryParser的搜索
-------------------------------------------------------------

//基于字符串操作public void SearchByQueryParse(Query query,int num){try {IndexSearcher search = getSearch();TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}

//使用query查询(创建queryparser，再通过queryparser创建query)                                // 1.创建Parse对象(设置默认搜索域为content)QueryParser parse = new QueryParser(Version.LUCENE_35, "content",new StandardAnalyzer(Version.LUCENE_35));// 改变空格的默认操作(改为AND型)parse.setDefaultOperator(Operator.AND);// 开启第一个字符的通配符匹配(*xxx,?xxx),默认关闭,因为效率比较低parse.setAllowLeadingWildcard(true);// 2.通过parse生成query(搜索content域中包含有like的)Query query = parse.parse("like");// 能够一直加条件(空格默认就是OR)query = parse.parse("basketball i");// 改变搜索域(域:值)query = parse.parse("name:mark");// 同样能进行*或？的通配符匹配(通配符默认不能放在首位)query = parse.parse("name:*i");// name中不包含mark,但是content中包含basketball(-和+必须放在域说明的前面)query = parse.parse("- name:mark + basketball");// id的1~3(TO表示一个闭区间,TO必须是大写的)query = parse.parse("id:[1 TO 3]");// {}表示1~3的开区间匹配query = parse.parse("id:{1 TO 3}");// name域值是lili或mark,默认域值是gamequery = parse.parse("name:(lili OR mark) AND game");// 两个‘’号表示短语匹配query = parse.parse("'i like basketball'");// 表示i basketball之间有一个单词遗漏的匹配query = parse.parse("\"i basketball\"~1");// 加个~就能模糊查询markquery = parse.parse("name:mirk~");// 没有办法匹配数字范围(自己扩展parse)query = parse.parse("attach:[1 TO 3]");sutil.SearchByQueryParse(query, 5);

------------------------------------------------------------
简单分页搜索
------------------------------------------------------------
Lucene通过再查询的方式：将所有数据取出，再进行分段分页
3.5以后使用的是searchAfter
//第一种分页方式（通过取出全部数据，再通过start和end对数据进行分页）

public void searchPage(String query,int pageIndex,int pageSize) {try {Directory dir = FileIndexUtils.getDirectory();IndexSearcher searcher = getSearcher(dir);QueryParser parser = new QueryParser(Version.LUCENE_35,"content",new StandardAnalyzer(Version.LUCENE_35));Query q = parser.parse(query);TopDocs tds = searcher.search(q, 500);ScoreDoc[] sds = tds.scoreDocs;int start = (pageIndex-1)*pageSize;int end = pageIndex*pageSize;for(int i=start;i<end;i++) {Document doc = searcher.doc(sds[i].doc);System.out.println(sds[i].doc+":"+doc.get("path")+"-->"+doc.get("filename"));}searcher.close();} catch (org.apache.lucene.queryParser.ParseException e) {e.printStackTrace();} catch (IOException e) {e.printStackTrace();}}

-----------------------------------------------------------
lucene的搜索_基于searchAfter的实现（Lucene3.5之后）
-----------------------------------------------------------
/**
  * 根据页码和分页大小获取上一次的最后一个ScoreDoc
*/

private ScoreDoc getLastScoreDoc(int pageIndex,int pageSize,Query query,IndexSearcher searcher) throws IOException {if(pageIndex==1)return null;//如果是第一页就返回空int num = pageSize*(pageIndex-1);//获取上一页的数量                                //每次只取上面所有的元素TopDocs tds = searcher.search(query, num);return tds.scoreDocs[num-1];}public void searchPageByAfter(String query,int pageIndex,int pageSize) {try {Directory dir = FileIndexUtils.getDirectory();IndexSearcher searcher = getSearcher(dir);QueryParser parser = new QueryParser(Version.LUCENE_35,"content",new StandardAnalyzer(Version.LUCENE_35));Query q = parser.parse(query);//先获取上一页的最后一个元素ScoreDoc lastSd = getLastScoreDoc(pageIndex, pageSize, q, searcher);//通过最后一个元素搜索下页的pageSize个元素TopDocs tds = searcher.searchAfter(lastSd,q, pageSize);for(ScoreDoc sd:tds.scoreDocs) {Document doc = searcher.doc(sd.doc);System.out.println(sd.doc+":"+doc.get("path")+"-->"+doc.get("filename"));}searcher.close();} catch (org.apache.lucene.queryParser.ParseException e) {e.printStackTrace();} catch (IOException e) {e.printStackTrace();}}

代码片段

package test.lucene.index;import java.io.IOException;import java.util.Date;import java.util.HashMap;import java.util.Map;import org.apache.lucene.analysis.standard.StandardAnalyzer;import org.apache.lucene.document.Document;import org.apache.lucene.document.Field;import org.apache.lucene.document.NumericField;import org.apache.lucene.index.CorruptIndexException;import org.apache.lucene.index.IndexReader;import org.apache.lucene.index.IndexWriter;import org.apache.lucene.index.IndexWriterConfig;import org.apache.lucene.index.Term;import org.apache.lucene.search.BooleanQuery;import org.apache.lucene.search.FuzzyQuery;import org.apache.lucene.search.IndexSearcher;import org.apache.lucene.search.NumericRangeQuery;import org.apache.lucene.search.PhraseQuery;import org.apache.lucene.search.PrefixQuery;import org.apache.lucene.search.Query;import org.apache.lucene.search.ScoreDoc;import org.apache.lucene.search.TermQuery;import org.apache.lucene.search.TermRangeFilter;import org.apache.lucene.search.TermRangeQuery;import org.apache.lucene.search.TopDocs;import org.apache.lucene.search.WildcardQuery;import org.apache.lucene.search.BooleanClause.Occur;import org.apache.lucene.store.Directory;import org.apache.lucene.store.RAMDirectory;import org.apache.lucene.util.Version;public class SearchUtil {/* * 假设6个文档 */private String[] ids = { "1", "2", "3", "4", "5", "6" };private String[] emails = { "[e-mail]", "[e-mail]", "[e-mail]","[e-mail]", "[e-mail]", "[e-mail]" };private String[] contents = { "hello boy,i like pingpang", "like boy","xx bye i like swim", "hehe, i like basketball","dd fsfs, i like movie", "hello xxx,i like game" };private int[] attachs = { 2, 3, 1, 4, 5, 5 };private String[] names = { "lili", "wangwu", "lisi", "jack", "tom", "mark" };// 设置加权mapprivate Map<String, Float> scores = new HashMap<String, Float>();private Directory directory;private IndexReader reader;public SearchUtil() {directory = new RAMDirectory();}/* * 添加索引 */public void index() {IndexWriter writer = null;try {writer = new IndexWriter(directory, new IndexWriterConfig(Version.LUCENE_35, new StandardAnalyzer(Version.LUCENE_35)));writer.deleteAll();// 创建documentsDocument document = null;for (int i = 0; i < ids.length; i++) {document = new Document();document.add(new Field("id", ids[i], Field.Store.YES,Field.Index.NOT_ANALYZED_NO_NORMS));document.add(new Field("email", emails[i], Field.Store.YES,Field.Index.NOT_ANALYZED)); // 不分词document.add(new Field("content", contents[i], Field.Store.NO,Field.Index.ANALYZED));document.add(new Field("name", names[i], Field.Store.YES,Field.Index.NOT_ANALYZED));// 为数字添加索引document.add(new NumericField("attach", Field.Store.YES, true).setIntValue(attachs[i]));/* * document.setBoost(float) 设置评级 */String et = emails[i].substring(emails[i].lastIndexOf("@") + 1);// System.out.println(et);if (scores.containsKey(et)) {document.setBoost(scores.get(et));} else {document.setBoost(0.5f);}writer.addDocument(document);}} catch (IOException e) {e.printStackTrace();} finally {if (writer != null) {try {writer.close();writer = null;} catch (IOException e) {e.printStackTrace();}}}}/* * 创建IndexSearch的方法 */public IndexSearcher getSearch() {try {if (reader == null) {reader = IndexReader.open(directory);} else {IndexReader read = IndexReader.openIfChanged(reader);if (read != null) {reader.close();reader = read;}}return new IndexSearcher(reader);} catch (CorruptIndexException e) {e.printStackTrace();} catch (IOException e) {e.printStackTrace();}return null;}// 精确匹配查询public void SearchByTerm(String field, String name, int num) {try {IndexSearcher search = getSearch();Query query = new TermQuery(new Term(field, name));TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}// 基于字符串的范围的查询public void SearchByTermRange(String field, String start, String end,int num) {try {IndexSearcher search = getSearch();// 范围查询// true表示闭区间Query query = new TermRangeQuery(field, start, end, true, true);TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}// 基于数字的范围的查询public void SearchByNumricRange(String field, int start, int end, int num) {try {IndexSearcher search = getSearch();// 范围查询// true表示闭区间Query query = NumericRangeQuery.newIntRange(field, start, end,true, true);TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}// 前缀搜索public void SearchByPrefix(String field, String value, int num) {try {IndexSearcher search = getSearch();Query query = new PrefixQuery(new Term(field, value));TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}// 通配符搜索public void SearchByWildCard(String field, String value, int num) {try {IndexSearcher search = getSearch();Query query = new WildcardQuery(new Term(field, value));TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}// 多个条件搜索public void SearchByBoolean(int num) {try {IndexSearcher search = getSearch();BooleanQuery query = new BooleanQuery();// Occur.Must表必须 Occur.SHOULD表示可有可无 Occur.MUST_NOT表示必须没有query.add(new TermQuery(new Term("name", "lili")), Occur.MUST);query.add(new TermQuery(new Term("content", "hello")), Occur.MUST);TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}// 短语查询public void SearchByPhrase(int num) {try {IndexSearcher search = getSearch();PhraseQuery query = new PhraseQuery();// setSlop()设置跳数,及两个单词之间有几个单词query.setSlop(1);// 设置field字段，即哪两个单词query.add(new Term("content", "i"));query.add(new Term("content", "basketball"));TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}// 模糊查询public void SearchByFuzzy(int num) {try {IndexSearcher search = getSearch();Query query=new FuzzyQuery(new Term("name", "mirk"));TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}//基于字符串操作public void SearchByQueryParse(Query query,int num){try {IndexSearcher search = getSearch();TopDocs tds = search.search(query, num);System.out.println("一共查询了：" + tds.totalHits);for (ScoreDoc sdc : tds.scoreDocs) {Document doc = search.doc(sdc.doc);System.out.println(sdc.doc + doc.get("name") + "["+ doc.get("email") + "," + doc.get("id") + ","+ doc.get("attach") + "]");}search.close();} catch (IOException e) {e.printStackTrace();}}}

package test.lucene.index;import org.apache.lucene.analysis.standard.StandardAnalyzer;import org.apache.lucene.queryParser.ParseException;import org.apache.lucene.queryParser.QueryParser;import org.apache.lucene.queryParser.QueryParser.Operator;import org.apache.lucene.search.Query;import org.apache.lucene.util.Version;import org.junit.Before;import org.junit.Test;public class SearchTest {private SearchUtil sutil;@Beforepublic void init() throws Exception {sutil = new SearchUtil();}@Testpublic void searchByterm() {sutil.index();sutil.SearchByTerm("name", "mark", 3);}@Testpublic void searchByRangeTerm() {sutil.index();sutil.SearchByTermRange("id", "1", "3", 10);// 查询name以a开头和s结尾的sutil.SearchByTermRange("name", "a", "s", 10);// 由于attach是数字类型，使用termrange无法查询sutil.SearchByTermRange("attach", "1", "5", 10);}@Testpublic void searchByNumricRange() {sutil.index();// 由于attach是数字类型，使用NumricRange进行查询sutil.SearchByNumricRange("attach", 2, 5, 10);}@Testpublic void searchByPrefix() {sutil.index();// 前缀搜索sutil.SearchByPrefix("name", "l", 3);}@Testpublic void searchByWildCard() {sutil.index();// 通配符搜索sutil.SearchByWildCard("name", "l*", 3);}@Testpublic void searchByBoolean() {sutil.index();// 多条件查询sutil.SearchByBoolean(3);}@Testpublic void searchByPhrase() {sutil.index();// 短语查询sutil.SearchByPhrase(5);}@Testpublic void searchByFuzzy() {sutil.index();// 模糊查询sutil.SearchByFuzzy(5);}@Testpublic void searchByqueryParse() throws Exception {sutil.index();// 1.创建Parse对象(设置默认搜索域为content)QueryParser parse = new QueryParser(Version.LUCENE_35, "content",new StandardAnalyzer(Version.LUCENE_35));// 改变空格的默认操作(改为AND型)parse.setDefaultOperator(Operator.AND);// 开启第一个字符的通配符匹配(*xxx,?xxx),默认关闭,因为效率比较低parse.setAllowLeadingWildcard(true);// 2.通过parse生成query(搜索content域中包含有like的)Query query = parse.parse("like");// 能够一直加条件(空格默认就是OR)query = parse.parse("basketball i");// 改变搜索域(域:值)query = parse.parse("name:mark");// 同样能进行*或？的通配符匹配(通配符默认不能放在首位)query = parse.parse("name:*i");// name中不包含mark,但是content中包含basketball(-和+必须放在域说明的前面)query = parse.parse("- name:mark + basketball");// id的1~3(TO表示一个闭区间,TO必须是大写的)query = parse.parse("id:[1 TO 3]");// {}表示1~3的开区间匹配query = parse.parse("id:{1 TO 3}");// name域值是lili或mark,默认域值是gamequery = parse.parse("name:(lili OR mark) AND game");// 两个‘’号表示短语匹配query = parse.parse("'i like basketball'");// 表示i basketball之间有一个单词遗漏的匹配query = parse.parse("\"i basketball\"~1");// 加个~就能模糊查询markquery = parse.parse("name:mirk~");// 没有办法匹配数字范围(自己扩展parse)query = parse.parse("attach:[1 TO 3]");sutil.SearchByQueryParse(query, 5);}}