Lucene多线程操作实现
Lucene多线程操作实现<?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" />
对于并发，Lucene 遵循以下规则：
1. 允许任意多的读操作并发，即任意数量用户可同时对同一索引做检索操作。
2. 即便正在进行索引修改操作(索引优化、添加文档、删除文档)，依然允许任意多的检索操作并发执行。
3. 不允许并发修改操作，也就是说同一时间只允许一个索引修改操作。
Lucene内部已经对多线程安全进行了处理，很多操作都使用了 lock 进行多线程同步锁定。只要遵循一定的规则，就可以在多线程环境下安全运行 Lucene。
方案一：
建议：
1. Directotry、Analyzer 都是多线程安全类型，只需建立一个 Singleton 对象即可。
2. 所有线程使用同一个 IndexModifier 对象进行索引修改操作。
3. IndexWriter/IndexReader/IndexModifier/IndexSearcher 最好使用同一个 Directory 对象，否则多线程并发读写时可能引发 FileNotFoundException。
IndexModifier 对象封装了 IndexWriter 和 IndexReader 的常用操作，其内部实现了多线程同步锁定。使用 IndexModifier 可避免同时使用 IndexWriter 和 IndexReader 时需要在多个对象之间进行同步的麻烦。等所有修改操作完成后，记住调用 Close() 方法关闭相关资源。并不是每次操作都需要调用 Optimize()，可以依据特定情况，定期执行优化操作。
--------
以下演示代码简单封装了一个 IndexModifier Signleton 类型，确保多线程使用同一个对象，且只能由最后一个多线程调用 Close 方法关闭。
代码不完善，仅供参考！需要做些修改才能应用于实际项目。
//索引修改器的获取和关闭
import java.io.File;
import java.io.IOException;
import java.io.StringReader;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Map;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.lucene.index.CorruptIndexException;
import org.apache.lucene.index.IndexModifier;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.LockObtainFailedException;
import org.apache.lucene.store.RAMDirectory;
public class MyIndexModifier {
private static Analyzer analyzer = new StandardAnalyzer();
private static IndexModifier modifier;
private static ArrayList<Thread> threadList = new ArrayList<Thread>();
private MyIndexModifier() { }
static final File INDEX_DIR = new File("D:/docindex");
public static IndexModifier GetInstance()
{
synchronized (threadList)
{
if (modifier == null)
{
try {
modifier = new IndexModifier(INDEX_DIR, analyzer, false);
//索引性能测试参数配置
modifier.setMergeFactor(1000);
System.out.println("MergeFactor: " + modifier.getMergeFactor());
System.out.println("MaxBufferedDocs: " + modifier.getMaxBufferedDocs());
} catch (CorruptIndexException e) {
e.printStackTrace();
} catch (LockObtainFailedException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
if (!threadList.contains(Thread.currentThread()))
threadList.add(Thread.currentThread());
return modifier;
}
}
public static void Close()
{
synchronized (threadList)
{
if (threadList.contains(Thread.currentThread()))
threadList.remove(Thread.currentThread());
if (threadList.size() == 0)
{
try {
if (modifier != null)
{
modifier.close();
modifier = null;
}
} catch (CorruptIndexException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
}
}
}
//线程处理类
import java.io.IOException;
import java.util.Date;
import org.apache.log4j.LogManager;
import org.apache.log4j.Logger;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.index.CorruptIndexException;
import org.apache.lucene.index.IndexModifier;
import org.apache.lucene.index.StaleReaderException;
import org.apache.lucene.store.LockObtainFailedException;
import com.miracle.dm.framework.common.TimestampConverter;
public class TestModifer extends Thread{
private static Logger logger = LogManager.getLogger(TestModifer.class);
@Override
public void run() {
IndexModifier writer = MyIndexModifier.GetInstance();
try {
writer.deleteDocument(0);
} catch (StaleReaderException e1) {
// TODO Auto-generated catch block
e1.printStackTrace();
} catch (CorruptIndexException e1) {
// TODO Auto-generated catch block
e1.printStackTrace();
} catch (LockObtainFailedException e1) {
// TODO Auto-generated catch block
e1.printStackTrace();
} catch (IOException e1) {
// TODO Auto-generated catch block
e1.printStackTrace();
}
for (int x = 0; x < 10; x++)
{
Document doc = new Document();
TimestampConverter converter = new TimestampConverter();
Date date = new Date();
String docDate = converter.timestampToShortStr(date);
doc.add(new Field("docDate", docDate , Field.Store.YES, Field.Index.TOKENIZED));
try {
writer.addDocument(doc);
} catch (CorruptIndexException e) {
// TODO Auto-generated catch block
e.printStackTrace();
} catch (LockObtainFailedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
logger.debug(""+ Thread.currentThread()+","+ writer.docCount());
MyIndexModifier.Close(); // 注意不是调用 IndexModifier.Close() ！
}
}
多线程测试代码
import java.io.Console;
import java.io.IOException;
import java.util.Date;
import org.apache.log4j.LogManager;
import org.apache.log4j.Logger;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.index.CorruptIndexException;
import org.apache.lucene.index.IndexModifier;
import org.apache.lucene.store.LockObtainFailedException;
import com.miracle.dm.framework.common.TimestampConverter;
public class test {
private static Logger logger = LogManager.getLogger(test.class);
public test(){
}
/**
* @param args
*/
public static void main(String[] args) {
for (int i = 0; i < 100; i++)
{
new TestModifer().start();
}
}
}
注意：使用lucene现在的新版本的朋友一定会发现，现在并不推荐使用。而查看API发现IndexModifier已经被IndexWriter代替。再查看IndexWriter，其中提供了新增，删除，更新索引文档的方法。
这里是自己编码来实现，但是我不知道当几千或更多用户在对索引进行操作，那会不会导致close长时间没有运行，而无法检索到最新的更新索引。希望大家帮我考虑一下是否会存在这方面的问题，如果存在该如何解决？
方案二：利用已有的lucene框架，例如compass
它对lucene实现了实时索引。可基于hibernate，当更新数据库时，系统会自动更新索引。
· Compass将lucene、Spring、Hibernate三者结合
转自：http://wemyss.blogbus.com/logs/8014799.html
1.概述
Compass将lucene、Spring、Hibernate三者的起来，以很低很低的成本快速实现企业应用中的搜索功能。
HomePage: http://www.opensymphony.com/compass/
springside里用了compass来做图书搜索，快速建立的流程如下：
1.用简单的compass annotation把Book对象映射到Lucene。
2.配置compass默认提供的基于Spring MVC的Index Controller 和Search Controller。
3.编写查询结果的显示页面，将controller返回的变量显示出来。
2.Object/Search Engine Mapping的 Annotations配置
使用JDK5 的annotation 来进行OSEM(Object/Search Engine Mapping)比用xml文件按简单许多，下面就是简单的搜索类，可见@SearchableID, @SearchableProperty与@SearchableComponent三个标记，分别代表主键、可搜索的属性与关联的，另一个可搜索的对象，另外Compass要求POJO要有默认构造函数，要实现equals()和hashcode():
详细请点击查看springside中的Product.java , Book.java, Category.java
publicclassProduct{
@SearchableId
privateIntegerid;
privateCategorycategory;
privateStringname;
privateDoubleunitprice;
@SearchableProperty(name="name")
publicStringgetName(){
returnthis.name;
}
@SearchableComponent(refAlias="category")
publicCategorygetCategory(){
returnthis.category;
}
publicDoublegetUnitprice(){
returnthis.unitprice;
}
3. 与spring,hibernate集成配置
3.1 spring配置文件
hiberante中的sessionFactory,transactionManager相比大家也是轻车熟路了.这里还是带过(因为不牵扯稿费的问题吗^_^ ).compass已经对对spring集成做了很好的封装，让我们的使用更加简单,我们可以不为compass编写一行代码,就可以做完搜索引擎的检索.下面是compass在spring中的简明配置. 详情点击查看springside中的applicationContext-lucene.xml ：
<?xml:namespace prefix = v ns = "urn:schemas-microsoft-com:vml" /><shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"><stroke joinstyle="miter"></stroke><formulas><f eqn="if lineDrawn pixelLineWidth 0"></f><f eqn="sum @0 1 0"></f><f eqn="sum 0 0 @1"></f><f eqn="prod @2 1 2"></f><f eqn="prod @3 21600 pixelWidth"></f><f eqn="prod @3 21600 pixelHeight"></f><f eqn="sum @0 0 1"></f><f eqn="prod @6 1 2"></f><f eqn="prod @7 21600 pixelWidth"></f><f eqn="sum @8 21600 0"></f><f eqn="prod @7 21600 pixelHeight"></f><f eqn="sum @10 21600 0"></f></formulas><path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></path><lock v:ext="edit" aspectratio="t"></lock></shapetype><shape id="_x0000_i1025" style="WIDTH: 8.25pt; HEIGHT: 12pt" type="#_x0000_t75" alt=""><imagedata src="file:///C:%5CDOCUME~1%5CUSER%5CLOCALS~1%5CTemp%5Cmsohtml1%5C01%5Cclip_image001.gif" o:href="mhtml:file://C:\Documents%20and%20Settings\USER\桌面\本周\Compass将lucene、Spring、Hibernate三者结合%20-%20Wemyss's%20Space%20-%20博客大巴.mht!http://images.csdn.net/syntaxhighlighting/OutliningIndicators/None.gif"></imagedata></shape><beans>
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