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。
- <dependencies>
- <dependency>
- <groupId>junit</groupId>
- <artifactId>junit</artifactId>
- <version>4.8.2</version>
- <type>jar</type>
- <scope>test</scope>
- </dependency>
- <dependency>
- <groupId>org.apache.lucene</groupId>
- <artifactId>lucene-core</artifactId>
- <version>3.2.0</version>
- <type>jar</type>
- <scope>compile</scope>
- </dependency>
- <dependency>
- <groupId>org.apache.lucene</groupId>
- <artifactId>lucene-spatial</artifactId>
- <version>3.2.0</version>
- <type>jar</type>
- <scope>compile</scope>
- </dependency>
- <dependency>
- <groupId>org.json</groupId>
- <artifactId>json</artifactId>
- <version>20100903</version>
- <type>jar</type>
- <scope>compile</scope>
- </dependency>
- </dependencies>
- {"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<String> 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<String> 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<String> search(String keyword, double longitude,
- double latitude, double range) throws Exception {
- List<String> result = new ArrayList<String>();
- 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<Integer, Double> 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):
Lucene Spatial Example