如何为 lucene 添加多个 AND 布尔查询

本文关键字：AND 布尔 查询 添加 lucene | 更新日期: 2023-09-27 18:35:35

我有1000万个lucene文档，看起来像这样：

{
     "0": 230,
     "1": 12,
     "2": 611,
     "3": 800
}

我试图找到所有文档，所有字段都小于 10。这是我拥有的 lucene 代码：

BooleanQuery bq = new BooleanQuery();
bq.Add(NumericRangeQuery.NewIntRange("0", 1, 10, true, true), Occur.MUST);
bq.Add(NumericRangeQuery.NewIntRange("1", 1, 10 , true, true), Occur.MUST);
bq.Add(NumericRangeQuery.NewIntRange("2", 1, 10, true, true), Occur.MUST);
//bq.Add(NumericRangeQuery.NewIntRange("3", 1, 1000, true, true), Occur.MUST);
TopDocs hits = searcher.Search(bq, 10);
int counter = 0;
foreach (ScoreDoc scoreDoc in hits.ScoreDocs)
{
   Lucene.Net.Documents.Document doc = searcher.Doc(scoreDoc.Doc);
   Console.WriteLine("3: " + doc.Get("3"));
   counter++;
}

我遇到的问题是，当我检查所有 4 个属性以查看所有 4 个属性是否都在 1 到 10 之间时，我没有得到任何结果。当我检查前 3 个属性时，我得到了正确的结果。但是当我添加第四个时，我什么也得不到。如您所见，第四个布尔子句被注释掉了，因为它不会产生任何结果。我什至在 1 到 1000 之间的整个范围内进行了第四次属性检查，但仍然没有得到任何结果。我做错了什么吗？以下是我构建索引的方法。

public static void BuildIndex()
{
    Directory directory = FSDirectory.Open(new System.IO.DirectoryInfo("C:''Users''Luke''Desktop''1"));
    Analyzer analyzer = new Lucene.Net.Analysis.Standard.StandardAnalyzer(Lucene.Net.Util.Version.LUCENE_30);
    IndexWriter writer = new IndexWriter(directory, analyzer, new IndexWriter.MaxFieldLength(100000));

    for (int x = 0; x < 10000000; x++)
    {
        Document doc = new Document();
        doc.Add(new NumericField("id", 100000, Field.Store.YES, true).SetIntValue(x));
        for (int i = 0; i < 5; i++)
        {
            doc.Add(new NumericField(i.ToString(), 100000, Field.Store.YES, true).SetIntValue(rand.Next(1, 1000)));
        }
        writer.AddDocument(doc);
        if (x % 500 == 0)
        {
            Console.WriteLine(x);
        }
    }
    writer.Optimize();
    writer.Flush(true, true, true);
    writer.Dispose();
    directory.Dispose();
    Console.WriteLine("done");
    Console.Read();
}

如何为 lucene 添加多个 AND 布尔查询

我刚刚在 Java Lucene （4.4） 中重新创建了这个程序，我在数字范围查询中没有看到任何问题。

1） 3 文件

field:0 - value:137
field:1 - value:41
field:2 - value:908
field:3 - value:871
field:4 - value:686
field:0 - value:598
field:1 - value:623
field:2 - value:527
field:3 - value:364
field:4 - value:800
field:0 - value:96
field:1 - value:301
field:2 - value:323
field:3 - value:94
field:4 - value:653

2） 索引器 

package com.numericrange;
import java.io.File;
import java.io.IOException;
import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.document.IntField;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.IndexWriterConfig;
import org.apache.lucene.index.IndexWriterConfig.OpenMode;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.util.Version;
public class IndexBuilder
{
    /**
     * @param args
     * @throws IOException 
     */
    public static void main(String[] args) throws IOException
    {
        Directory dir = FSDirectory.open(new File("/Users/Lucene/indexes"));
        IndexWriterConfig iwc = new IndexWriterConfig(Version.LUCENE_44, new StandardAnalyzer(Version.LUCENE_44));
        iwc.setOpenMode(OpenMode.CREATE);
        IndexWriter writer = new IndexWriter(dir, iwc);
        for (int x = 0; x < 3; x++)
        {
            Document doc = new Document();
            IntField iFldOut = new IntField("id", 6, Field.Store.YES);
            iFldOut.setIntValue(x);
            doc.add(iFldOut);
            for (int i = 0; i < 5; i++)
            {
                int randomVal = (int)(Math.random() * 1000) + 1;
                IntField iFld = new IntField(Integer.toString(i), 6, Field.Store.YES);
                iFld.setIntValue(randomVal);
                doc.add(iFld);
                System.out.println("i:" + i + " - Random Value:" + randomVal);
            }
            writer.addDocument(doc);
        }
        int newNumDocs = writer.numDocs();
        System.out.println("************************");
        System.out.println(newNumDocs + " documents added.");
        System.out.println("************************");
        writer.close();
    }
}

3） 搜索

package com.numericrange;
import java.io.File;
import java.io.IOException;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.search.BooleanClause.Occur;
import org.apache.lucene.search.BooleanQuery;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.NumericRangeQuery;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TopScoreDocCollector;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.util.Version;
public class NumericQueryDemo
{
    public static void main(String[] args) throws IOException, Exception
    {
        // Use Indexes from existing folder
        String dirPath = "/Users/Lucene/indexes";
        IndexReader reader = DirectoryReader.open(FSDirectory.open(new File(dirPath)));
        IndexSearcher searcher = new IndexSearcher(reader);
        Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_44);
        BooleanQuery bq = new BooleanQuery();
        bq.add(NumericRangeQuery.newIntRange("0", 100, 600, true, true), Occur.MUST);
        bq.add(NumericRangeQuery.newIntRange("1", 40, 700, true, true), Occur.MUST);
        bq.add(NumericRangeQuery.newIntRange("2", 500, 1000, true, true), Occur.MUST);
        bq.add(NumericRangeQuery.newIntRange("3", 300, 900, true, true), Occur.MUST);
        bq.add(NumericRangeQuery.newIntRange("4", 600, 800, true, true), Occur.MUST);
        System.out.println("Query Data:" + bq.toString());
        TopScoreDocCollector collector = TopScoreDocCollector.create(500, true);
        long startTime = System.currentTimeMillis();
        searcher.search(bq, collector);
        System.out.println("Search Time: "+(System.currentTimeMillis() - startTime)+"ms");
        // Display Results
        ScoreDoc[] hits = collector.topDocs().scoreDocs;
        System.out.println("Found " + hits.length + " hits.");
        for(int i=0; i < hits.length; ++i) 
        {
            int docId = hits[i].doc;
            Document d = searcher.doc(docId);
            System.out.println((i + 1) + ". " + hits[i].score + " "+ d.get("id") + " ==== " + d.get("0") +
                    " ==== " + d.get("1") + " ==== " + d.get("2") + " ==== " + d.get("3") + " ==== " + d.get("4"));
        }
    }
}

4） 搜索结果

Query Data:+0:[100 TO 600] +1:[40 TO 700] +2:[500 TO 1000] +3:[300 TO 900] +4:[600 TO 800]
Search Time: 27ms
Found 2 hits.
1. 2.236068 0 ==== 137 ==== 41 ==== 908 ==== 871 ==== 686
2. 2.236068 1 ==== 598 ==== 623 ==== 527 ==== 364 ==== 800

如您所见，我将精度步长值用作"6"。我验证了文档通过卢克正确索引，并通过卢克触发了相同的查询。

您可以尝试通过 Luke 界面触发查询吗？ 根据您的文档更改值。

+0：[100 到 600] +1：[40 到 700] +2：[500 到 1000] +3：[

300 到 900] +4：[600 到 800]

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