使用Lucene-Spatial实现集成地理位置的全文检索

Lucene通过Spatial包提供了对基于地理位置的全文检索的支持，最典型的应用场景就是：“搜索中关村附近1公里内的火锅店，并按远近排序”。使用Lucene-Spatial添加对地理位置的支持，和之前普通文本搜索主要有两点区别：

1. 将坐标信息转化为笛卡尔层，建立索引

private void indexLocation(Document document, JSONObject jo) throws Exception { double longitude = jo.getDouble("longitude"); double latitude = jo.getDouble("latitude"); document.add(new Field("lat", NumericUtils .doubleToPrefixCoded(latitude), Field.Store.YES, Field.Index.NOT_ANALYZED)); document.add(new Field("lng", NumericUtils .doubleToPrefixCoded(longitude), Field.Store.YES, Field.Index.NOT_ANALYZED)); for (int tier = startTier; tier <= endTier; tier++) { ctp = new CartesianTierPlotter(tier, projector, CartesianTierPlotter.DEFALT_FIELD_PREFIX); final double boxId = ctp.getTierBoxId(latitude, longitude); document.add(new Field(ctp.getTierFieldName(), NumericUtils .doubleToPrefixCoded(boxId), Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS)); } }
2. 搜索时，指定使用DistanceQueryFilter

DistanceQueryBuilder dq = new DistanceQueryBuilder(latitude, longitude, miles, "lat", "lng", CartesianTierPlotter.DEFALT_FIELD_PREFIX, true, startTier, endTier); DistanceFieldComparatorSource dsort = new DistanceFieldComparatorSource( dq.getDistanceFilter()); Sort sort = new Sort(new SortField("geo_distance", dsort));
下面是基于Lucene3.2.0和JUnit4.8.2的完整代码。

junit junit 4.8.2 jar test org.apache.lucene lucene-core 3.2.0 jar compile org.apache.lucene lucene-spatial 3.2.0 jar compile org.json json 20100903 jar compile

首先准备测试用的数据：

{"id":12,"title":"时尚码头美容美发热烫特价","longitude":116.3838183,"latitude":39.9629015} {"id":17,"title":"审美个人美容美发套餐","longitude":116.386564,"latitude":39.966102} {"id":23,"title":"海底捞吃300送300","longitude":116.38629,"latitude":39.9629573} {"id":26,"title":"仅98元！享原价335元李老爹","longitude":116.3846175,"latitude":39.9629125} {"id":29,"title":"都美造型烫染美发护理套餐","longitude":116.38629,"latitude":39.9629573} {"id":30,"title":"仅售55元！原价80元的老舍茶馆相声下午场","longitude":116.0799914,"latitude":39.9655391} {"id":33,"title":"仅售55元！原价80元的新笑声客栈早场","longitude":116.0799914,"latitude":39.9655391} {"id":34,"title":"仅售39元（红色礼盒）！原价80元的平谷桃","longitude":116.0799914,"latitude":39.9655391} {"id":46,"title":"仅售38元！原价180元地质礼堂白雪公主","longitude":116.0799914,"latitude":39.9655391} {"id":49,"title":"仅99元！享原价342.7元自助餐","longitude":116.0799914,"latitude":39.9655391} {"id":58,"title":"桑海教育暑期学生报名培训九折优惠券","longitude":116.0799914,"latitude":39.9655391} {"id":59,"title":"全国发货：仅29元！贝玲妃超模粉红高光光","longitude":116.0799914,"latitude":39.9655391} {"id":65,"title":"海之屿生态水族用品店抵用券","longitude":116.0799914,"latitude":39.9655391} {"id":67,"title":"小区东门时尚烫染个人护理美发套餐","longitude":116.3799914,"latitude":39.9655391} {"id":74,"title":"《郭德纲相声专辑》CD套装","longitude":116.0799914,"latitude":39.9655391}
根据上面的测试数据，编写测试用例，分别搜索坐标（ 116.3838183, 39.9629015） 3千米以内的“ 美发”和全部内容，分别得到的结果应该是 4条和 6条。

import static org.junit.Assert.assertEquals; import static org.junit.Assert.fail; import java.util.List; import org.junit.Test; public class LuceneSpatialTest { private static LuceneSpatial spatialSearcher = new LuceneSpatial(); @Test public void testSearch() { try { long start = System.currentTimeMillis(); List results = spatialSearcher.search("美发", 116.3838183, 39.9629015, 3.0); System.out.println(results.size() + "个匹配结果，共耗时 " + (System.currentTimeMillis() - start) + "毫秒。\n"); assertEquals(4, results.size()); } catch (Exception e) { fail("Exception occurs..."); e.printStackTrace(); } } @Test public void testSearchWithoutKeyword() { try { long start = System.currentTimeMillis(); List results = spatialSearcher.search(null, 116.3838183, 39.9629015, 3.0); System.out.println( results.size() + "个匹配结果，共耗时 " + (System.currentTimeMillis() - start) + "毫秒.\n"); assertEquals(6, results.size()); } catch (Exception e) { fail("Exception occurs..."); e.printStackTrace(); } } }
下面是LuceneSpatial类，在构造函数中初始化变量和创建索引：

public class LuceneSpatial { private Analyzer analyzer; private IndexWriter writer; private FSDirectory indexDirectory; private IndexSearcher indexSearcher; private IndexReader indexReader; private String indexPath = "c:/lucene-spatial"; // Spatial private IProjector projector; private CartesianTierPlotter ctp; public static final double RATE_MILE_TO_KM = 1.609344; //英里和公里的比率 public static final String LAT_FIELD = "lat"; public static final String LON_FIELD = "lng"; private static final double MAX_RANGE = 15.0; // 索引支持的最大范围，单位是千米 private static final double MIN_RANGE = 3.0; // 索引支持的最小范围，单位是千米 private int startTier; private int endTier; public LuceneSpatial() { try { init(); } catch (Exception e) { e.printStackTrace(); } } private void init() throws Exception { initializeSpatialOptions(); analyzer = new StandardAnalyzer(Version.LUCENE_32); File path = new File(indexPath); boolean isNeedCreateIndex = false; if (path.exists() && !path.isDirectory()) throw new Exception("Specified path is not a directory"); if (!path.exists()) { path.mkdirs(); isNeedCreateIndex = true; } indexDirectory = FSDirectory.open(new File(indexPath)); //建立索引 if (isNeedCreateIndex) { IndexWriterConfig indexWriterConfig = new IndexWriterConfig( Version.LUCENE_32, analyzer); indexWriterConfig.setOpenMode(OpenMode.CREATE_OR_APPEND); writer = new IndexWriter(indexDirectory, indexWriterConfig); buildIndex(); } indexReader = IndexReader.open(indexDirectory, true); indexSearcher = new IndexSearcher(indexReader); } @SuppressWarnings("deprecation") private void initializeSpatialOptions() { projector = new SinusoidalProjector(); ctp = new CartesianTierPlotter(0, projector, CartesianTierPlotter.DEFALT_FIELD_PREFIX); startTier = ctp.bestFit(MAX_RANGE / RATE_MILE_TO_KM); endTier = ctp.bestFit(MIN_RANGE / RATE_MILE_TO_KM); } private int mile2Meter(double miles) { double dMeter = miles * RATE_MILE_TO_KM * 1000; return (int) dMeter; } private double km2Mile(double km) { return km / RATE_MILE_TO_KM; }

创建索引的具体实现：

private void buildIndex() { BufferedReader br = null; try { //逐行添加测试数据到索引中，测试数据文件和源文件在同一个目录下 br = new BufferedReader(new InputStreamReader( LuceneSpatial.class.getResourceAsStream("data"))); String line = null; while ((line = br.readLine()) != null) { index(new JSONObject(line)); } writer.commit(); } catch (Exception e) { e.printStackTrace(); } finally { if (br != null) { try { br.close(); } catch (IOException e) { e.printStackTrace(); } } } } private void index(JSONObject jo) throws Exception { Document doc = new Document(); doc.add(new Field("id", jo.getString("id"), Field.Store.YES, Field.Index.ANALYZED)); doc.add(new Field("title", jo.getString("title"), Field.Store.YES, Field.Index.ANALYZED)); //将位置信息添加到索引中 indexLocation(doc, jo); writer.addDocument(doc); } private void indexLocation(Document document, JSONObject jo) throws Exception { double longitude = jo.getDouble("longitude"); double latitude = jo.getDouble("latitude"); document.add(new Field("lat", NumericUtils .doubleToPrefixCoded(latitude), Field.Store.YES, Field.Index.NOT_ANALYZED)); document.add(new Field("lng", NumericUtils .doubleToPrefixCoded(longitude), Field.Store.YES, Field.Index.NOT_ANALYZED)); for (int tier = startTier; tier <= endTier; tier++) { ctp = new CartesianTierPlotter(tier, projector, CartesianTierPlotter.DEFALT_FIELD_PREFIX); final double boxId = ctp.getTierBoxId(latitude, longitude); document.add(new Field(ctp.getTierFieldName(), NumericUtils .doubleToPrefixCoded(boxId), Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS)); } }
搜索的具体实现：

public List search(String keyword, double longitude, double latitude, double range) throws Exception { List result = new ArrayList(); double miles = km2Mile(range); DistanceQueryBuilder dq = new DistanceQueryBuilder(latitude, longitude, miles, "lat", "lng", CartesianTierPlotter.DEFALT_FIELD_PREFIX, true, startTier, endTier); //按照距离排序 DistanceFieldComparatorSource dsort = new DistanceFieldComparatorSource( dq.getDistanceFilter()); Sort sort = new Sort(new SortField("geo_distance", dsort)); Query query = buildQuery(keyword); //搜索结果 TopDocs hits = indexSearcher.search(query, dq.getFilter(), Integer.MAX_VALUE, sort); //获得各条结果相对应的距离 Map distances = dq.getDistanceFilter() .getDistances(); for (int i = 0; i < hits.totalHits; i++) { final int docID = hits.scoreDocs[i].doc; final Document doc = indexSearcher.doc(docID); final StringBuilder builder = new StringBuilder(); builder.append("找到了: ") .append(doc.get("title")) .append("， 距离: ") .append(mile2Meter(distances.get(docID))) .append("米。"); System.out.println(builder.toString()); result.add(builder.toString()); } return result; } private Query buildQuery(String keyword) throws Exception { //如果没有指定关键字，则返回范围内的所有结果 if (keyword == null || keyword.isEmpty()) { return new MatchAllDocsQuery(); } QueryParser parser = new QueryParser(Version.LUCENE_32, "title", analyzer); parser.setDefaultOperator(Operator.AND); return parser.parse(keyword.toString()); }

执行测试用例，可以得到下面的结果：

找到了: 时尚码头美容美发热烫特价， 距离: 0米。 找到了: 都美造型烫染美发护理套餐， 距离: 210米。 找到了: 审美个人美容美发套餐， 距离: 426米。 找到了: 小区东门时尚烫染个人护理美发套餐， 距离: 439米。 4个匹配结果，共耗时 119毫秒。 找到了: 时尚码头美容美发热烫特价， 距离: 0米。 找到了: 仅98元！享原价335元李老爹， 距离: 68米。 找到了: 海底捞吃300送300， 距离: 210米。 找到了: 都美造型烫染美发护理套餐， 距离: 210米。 找到了: 审美个人美容美发套餐， 距离: 426米。 找到了: 小区东门时尚烫染个人护理美发套餐， 距离: 439米。 6个匹配结果，共耗时 3毫秒.
参考文献：

Lucene-Spatial的原理介绍：http://www.nsshutdown.com/projects/lucene/whitepaper/locallucene.htm

GeoHash：http://en.wikipedia.org/wiki/Geohash

两篇示例（其中大部分代码就来自于这里）：

Spatial search with Lucene

Lucene Spatial Example

使用 Apache Lucene 和 Solr 进行位置感知搜索