下面演示的是Lucene-3.6.2中搜索的时候，使用普通Filter和自定义Filter的用法（详见代码注释）
package com.xuanyuv.lucene;
import java.io.File;
import java.io.IOException;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Date;
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.IndexReader;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.IndexWriterConfig;
import org.apache.lucene.queryParser.QueryParser;
import org.apache.lucene.search.Filter;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.util.Version;
import com.xuanyuv.custom.MyFilter;
/**
* Lucene系列第07节之高级搜索之Filter
* Created by 玄玉<https://www.xuanyuv.com/> on 2013/08/19 11:13.
*/
public class AdvancedSearchByFilter {
private Directory directory;
private IndexReader reader;
public AdvancedSearchByFilter(){
/** 文件大小 */
int[] sizes = {90, 10, 20, 10, 60, 50};
/** 文件名 */
String[] names = {"Michael.java", "Scofield.ini", "Tbag.txt", "Jack", "Jade", "Xuanyu"};
/** 文件内容 */
String[] contents = {"my blog is https://www.xuanyuv.com/",
"my github is https://github.com/xuanyuv",
"my name is xuanyu",
"I am a Java Developer",
"I am from Haerbin",
"I like java of Lucene"};
/** 文件日期 */
Date[] dates = new Date[sizes.length];
SimpleDateFormat sdf = new SimpleDateFormat("yyyyMMdd HH:mm:ss");
IndexWriter writer = null;
Document doc = null;
try {
dates[0] = sdf.parse("20130407 15:25:30");
dates[1] = sdf.parse("20130407 16:30:45");
dates[2] = sdf.parse("20130213 11:15:25");
dates[3] = sdf.parse("20130808 09:30:55");
dates[4] = sdf.parse("20130526 13:54:22");
dates[5] = sdf.parse("20130701 17:35:34");
directory = FSDirectory.open(new File("myExample/01_index/"));
writer = new IndexWriter(directory, new IndexWriterConfig(Version.LUCENE_36, new StandardAnalyzer(Version.LUCENE_36)));
writer.deleteAll();
for(int i=0; i<sizes.length; i++){
doc = new Document();
doc.add(new NumericField("size",Field.Store.YES, true).setIntValue(sizes[i]));
doc.add(new Field("name", names[i], Field.Store.YES, Field.Index.ANALYZED_NO_NORMS));
doc.add(new Field("content", contents[i], Field.Store.NO, Field.Index.ANALYZED));
doc.add(new NumericField("date", Field.Store.YES, true).setLongValue(dates[i].getTime()));
//为每个文档添加一个fileID（与ScoreDoc.doc不同），其专门在自定义Filter时使用
doc.add(new Field("fileID", String.valueOf(i), Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS));
writer.addDocument(doc);
}
} catch (Exception e) {
e.printStackTrace();
} finally {
if(null != writer){
try {
writer.close();
} catch (IOException ce) {
ce.printStackTrace();
}
}
}
}
/**
* 获取IndexReader实例
*/
private IndexReader getIndexReader(){
try {
if(reader == null){
reader = IndexReader.open(directory);
}else{
//if the index was changed since the provided reader was opened, open and return a new reader; else,return null
//如果当前reader在打开期间index发生改变，则打开并返回一个新的IndexReader，否则返回null
IndexReader ir = IndexReader.openIfChanged(reader);
if(ir != null){
reader.close(); //关闭原reader
reader = ir; //赋予新reader
}
}
return reader;
}catch(Exception e) {
e.printStackTrace();
}
return null; //发生异常则返回null
}
/**
* 搜索过滤
*/
public void searchByFilter(String expr, Filter filter){
IndexSearcher searcher = new IndexSearcher(this.getIndexReader());
QueryParser parser = new QueryParser(Version.LUCENE_36, "content", new StandardAnalyzer(Version.LUCENE_36));
TopDocs tds = null;
try {
if(null == filter){
tds = searcher.search(parser.parse(expr), 10);
}else{
tds = searcher.search(parser.parse(expr), filter, 10);
}
for(ScoreDoc sd : tds.scoreDocs){
Document doc = searcher.doc(sd.doc);
System.out.print("文档编号=" + sd.doc + " 文档权值=" + doc.getBoost() + " 文档评分=" + sd.score + " ");
System.out.print("fileID=" + doc.get("fileID") + " size=" + doc.get("size") + " date=");
System.out.print(new SimpleDateFormat("yyyyMMdd HH:mm:ss").format(new Date(Long.parseLong(doc.get("date")))));
System.out.println(" name=" + doc.get("name"));
}
} catch (Exception e) {
e.printStackTrace();
} finally {
if(searcher != null){
try {
searcher.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}
}
/**
* 测试一下过滤效果
*/
public static void main(String[] args) throws ParseException {
AdvancedSearchByFilter advancedSearch = new AdvancedSearchByFilter();
////过滤文件名首字母从'h'到'n'的记录（注意hn要小写）
//advancedSearch.searchByFilter("Java", new TermRangeFilter("name", "h", "n", true, true));
////过滤文件大小在30到80以内的记录
//advancedSearch.searchByFilter("Java", NumericRangeFilter.newIntRange("size", 30, 80, true, true));
////过滤文件日期在20130701 00:00:00到20130808 23:59:59之间的记录
//Long min = Long.valueOf(new SimpleDateFormat("yyyyMMdd").parse("20130701").getTime());
//Long max = Long.valueOf(new SimpleDateFormat("yyyyMMdd HH:mm:ss").parse("20130808 23:59:59").getTime());
//advancedSearch.searchByFilter("Java", NumericRangeFilter.newLongRange("date", min, max, true, true));
////过滤文件名以'ja'打头的（注意ja要小写）
//advancedSearch.searchByFilter("Java", new QueryWrapperFilter(new WildcardQuery(new Term("name", "ja*"))));
//自定义Filter
advancedSearch.searchByFilter("Java", new MyFilter());
}
}
下面是自定义的MyFilter.java
package com.xuanyuv.custom;
import java.io.IOException;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.TermDocs;
import org.apache.lucene.search.DocIdSet;
import org.apache.lucene.search.Filter;
import org.apache.lucene.util.OpenBitSet;
/**
* 自定义Filter
* -----------------------------------------------------------------------------------------------
* 本例的应用场景
* 假设很多的数据，然后删除了其中的某几条数据，此时在接受搜索请求时为保证不会搜索到已删除的数据
* 那么可以更新索引，但更新索引会消耗很多时间（因为数据量大），而又要保证已删除的数据不会被搜索到
* 此时就可以自定义Filter，原理即搜索过程中，当发现此记录为已删除记录，则不添加到返回的搜索结果集中
* -----------------------------------------------------------------------------------------------
* 自定义Filter步骤如下
* 1)继承Filter类并重写getDocIdSet()方法
* 2)根据实际过滤要求返回新的DocIdSet对象
* -----------------------------------------------------------------------------------------------
* DocIdSet小解
* 这里Filter干的活其实就是创建一个DocIdSet，而DocIdSet其实就是一个数组，可以理解为其中只存放0或1的值
* 每个搜索出来的Document都有一个文档编号，所以搜索出来多少个Document，那么DocIdSet中就会有多少条记录
* 而DocIdSet中每一条记录的索引号与文档编号是一一对应的
* 所以当DocIdSet中的记录为1时，则对应文档编号的Document就会被添加到TopDocs中，为0就会被过滤掉
* -----------------------------------------------------------------------------------------------
* Created by 玄玉<https://www.xuanyuv.com/> on 2013/08/06 19:28.
*/
public class MyFilter extends Filter {
private static final long serialVersionUID = -8955061358165068L;
//假设这是已删除记录的fileID值的集合
private String[] deleteFileIDs = {"1", "3"};
@Override
public DocIdSet getDocIdSet(IndexReader reader) throws IOException {
//创建一个DocIdSet的子类OpenBitSet（创建之后默认所有元素都是0），传的参数就是本次"搜索到的"元素数目
OpenBitSet obs = new OpenBitSet(reader.maxDoc());
//先把元素填满，即全部设置为1
obs.set(0, reader.maxDoc());
//用于保存已删除元素的文档编号
int[] docs = new int[1];
for(String deleteDataID : deleteFileIDs){
//获取已删除元素对应的TermDocs
TermDocs tds = reader.termDocs(new Term("fileID", deleteDataID));
//将已删除元素的文档编号放到docs中，将其出现的频率放到freqs中，最后返回查询出来的元素数目
int count = tds.read(docs, new int[1]);
if(count == 1){
//将这个位置docs[0]的元素删除
obs.clear(docs[0]);
}
}
return obs;
}
}