1.项目地址

https://github.com/GuardFTC/elasticsearch-test.git

2.创建实体类

  1. import lombok.Data;
  3. /**
  4.  * @author: 冯铁城 [17615007230@163.com]
  5.  * @date: 2022-08-29 09:36:45
  6.  * @describe: 省份信息
  7.  */
  8. @Data
  9. public class Omission {
  11.     /**
  12.      * 省份名称
  13.      */
  14.     private String name;
  16.     /**
  17.      * 经纬度坐标 精度在前 维度在后
  18.      */
  19.     private double[] location;
  20. }
  1. import cn.hutool.json.JSONObject;
  2. import lombok.Data;
  4. /**
  5.  * @author: 冯铁城 [17615007230@163.com]
  6.  * @date: 2022-08-29 10:50:31
  7.  * @describe: 图形信息
  8.  */
  9. @Data
  10. public class TestShape {
  12.     /**
  13.      * 名称
  14.      */
  15.     private String name;
  17.     /**
  18.      * 图形
  19.      */
  20.     private JSONObject location;
  21. }

3.地理位置Api

geoBoundingBox

  1. @Test
  2. @SneakyThrows(IOException.class)
  3. void geoBoundingBox() {
  5.     //1.以宁夏为左上角，台湾为右下角，可以获取到山东，湖南，湖北的相关信息
  6.     SearchResponse<Omission> search = secondaryClient.search(s -> s
  7.             .index(GEO_POINT_INDEX_NAME)
  8.             .query(q -> q.constantScore(c -> c.filter(f -> f.geoBoundingBox(g -> g
  9.                     .field("location")
  10.                     .boundingBox(b -> b.tlbr(t -> t
  11.                             .topLeft(tl -> tl.latlon(l -> l
  12.                                     .lon(104.17)
  13.                                     .lat(35.14)
  14.                             ))
  15.                             .bottomRight(br -> br.latlon(l -> l
  16.                                     .lon(119.18)
  17.                                     .lat(20.45)
  18.                             ))
  19.                     ))
  20.             )))), Omission.class
  21.     );
  23.     //2.校验
  24.     List<Hit<Omission>> hits = search.hits().hits();
  25.     Assert.isTrue(3 == hits.size());
  26.     List<Omission> omissions = CollStreamUtil.toList(search.hits().hits(), Hit::source);
  27.     List<String> names = CollStreamUtil.toList(omissions, Omission::getName);
  28.     Assert.isTrue(names.contains("山东"));
  29.     Assert.isTrue(names.contains("湖北"));
  30.     Assert.isTrue(names.contains("湖南"));
  31. }

geoDistance

  1. @Test
  2. @SneakyThrows(IOException.class)
  3. void geiDistance() {
  5.     //1.以北京为圆心，获取2000km内的省份，理论上应该返回北京，山东，湖北，以及湖南4个省份
  6.     SearchResponse<Omission> search = secondaryClient.search(s -> s
  7.             .index(GEO_POINT_INDEX_NAME)
  8.             .query(q -> q.constantScore(c -> c.filter(f -> f.geoDistance(g -> g
  9.                     .field("location")
  10.                     .location(l -> l.latlon(ll -> ll
  11.                             .lon(116.2)
  12.                             .lat(39.56)
  13.                     ))
  14.                     .distance("2000km")
  15.                     .distanceType(GeoDistanceType.Arc)
  16.             )))), Omission.class
  17.     );
  19.     //2.校验
  20.     Assert.isTrue(4 == search.hits().hits().size());
  21.     List<Omission> omissions = CollStreamUtil.toList(search.hits().hits(), Hit::source);
  22.     List<String> names = CollStreamUtil.toList(omissions, Omission::getName);
  23.     Assert.isTrue(names.contains("北京"));
  24.     Assert.isTrue(names.contains("山东"));
  25.     Assert.isTrue(names.contains("湖北"));
  26.     Assert.isTrue(names.contains("湖南"));
  27. }

sort

  1. @Test
  2. @SneakyThrows(IOException.class)
  3. void sort() {
  5.     //1.以北京为圆心，获取2000km内的省份，并按照距离倒序 理论上返回顺序为湖南，湖北，山东，北京
  6.     SearchResponse<Omission> search = secondaryClient.search(s -> s
  7.             .index(GEO_POINT_INDEX_NAME)
  8.             .query(q -> q.constantScore(c -> c.filter(f -> f.geoDistance(g -> g
  9.                     .field("location")
  10.                     .location(l -> l.latlon(ll -> ll
  11.                             .lon(116.2)
  12.                             .lat(39.56)
  13.                     ))
  14.                     .distance("2000km")
  15.             ))))
  16.             .sort(sort -> sort.geoDistance(g -> g
  17.                     .field("location")
  18.                     .location(l -> l.latlon(ll -> ll
  19.                             .lon(116.2)
  20.                             .lat(39.56)
  21.                     ))
  22.                     .order(SortOrder.Desc)
  23.                     .unit(DistanceUnit.Kilometers)
  24.             )), Omission.class
  25.     );
  27.     //2.校验
  28.     Assert.isTrue(4 == search.hits().hits().size());
  29.     Assert.isTrue("湖南".equals(search.hits().hits().get(0).source().getName()));
  30.     Assert.isTrue("湖北".equals(search.hits().hits().get(1).source().getName()));
  31.     Assert.isTrue("山东".equals(search.hits().hits().get(2).source().getName()));
  32.     Assert.isTrue("北京".equals(search.hits().hits().get(3).source().getName()));
  33. }

aggregation-GeoDistance

  1. @Test
  2. @SneakyThrows(IOException.class)
  3. void aggregationGeoDistance() {
  5.     //1.统计距离北京（包括北京）0~1000km范围、1000km到2000km范围内的省市数量
  6.     SearchResponse<Omission> search = primaryClient.search(s -> s
  7.             .index(GEO_POINT_INDEX_NAME)
  8.             .aggregations("omissionNumber", a -> a.geoDistance(g -> g
  9.                     .field("location")
  10.                     .origin(o -> o.latlon(l -> l
  11.                             .lon(116.2)
  12.                             .lat(39.56)
  13.                     ))
  14.                     .ranges(
  15.                             AggregationRange.of(ar -> ar.from("0").to("1000")),
  16.                             AggregationRange.of(ar -> ar.from("1000").to("2000"))
  17.                     )
  18.                     .unit(DistanceUnit.Kilometers)
  19.                     .distanceType(GeoDistanceType.Plane)
  20.             )), Omission.class
  21.     );
  23.     //2.校验
  24.     Aggregate omissionNumber = search.aggregations().get("omissionNumber");
  25.     List<RangeBucket> rangeBuckets = omissionNumber.geoDistance().buckets().array();
  26.     Assert.isTrue(2 == rangeBuckets.size());
  27.     for (RangeBucket rangeBucket : rangeBuckets) {
  28.         Assert.isTrue(2 == rangeBucket.docCount());
  29.     }
  30. }

aggregation-GeoHashGrid

  1. @Test
  2. @SneakyThrows(IOException.class)
  3. void aggregationGeoHashGrid() {
  5.     //1.网格聚合，指定geoHash长度为1
  6.     SearchResponse<Omission> search = primaryClient.search(s -> s
  7.             .index(GEO_POINT_INDEX_NAME)
  8.             .aggregations("geoHashData", a -> a.geohashGrid(g -> g
  9.                     .field("location")
  10.                     .precision(p -> p.geohashLength(1))
  11.             )), Omission.class
  12.     );
  14.     //2.校验
  15.     Aggregate geoHashData = search.aggregations().get("geoHashData");
  16.     List<GeoHashGridBucket> geoHashGridBuckets = geoHashData.geohashGrid().buckets().array();
  17.     Assert.isTrue(2 == geoHashGridBuckets.size());
  18. }

aggregation-GeoBounds

  1. @Test
  2. @SneakyThrows(IOException.class)
  3. void aggregationGeoBounds() {
  5.     //1.得到一个可以包含所有已存储数据的矩形
  6.     SearchResponse<Omission> search = primaryClient.search(s -> s
  7.             .index(GEO_POINT_INDEX_NAME)
  8.             .aggregations("box", a -> a.geoBounds(g -> g
  9.                     .field("location")
  10.             )), Omission.class
  11.     );
  13.     //2.校验
  14.     Aggregate box = search.aggregations().get("box");
  15.     GeoBounds bounds = box.geoBounds().bounds();
  16.     Assert.isTrue(bounds.isTlbr());
  17.     double topLeftLon = bounds.tlbr().topLeft().latlon().lon();
  18.     double topLeftLat = bounds.tlbr().topLeft().latlon().lat();
  19.     double bottomRightLon = bounds.tlbr().bottomRight().latlon().lon();
  20.     double bottomRightLat = bounds.tlbr().bottomRight().latlon().lat();
  21.     Assert.isTrue(86.36999999172986 == topLeftLon);
  22.     Assert.isTrue(42.44999995920807 == topLeftLat);
  23.     Assert.isTrue(116.19999996386468 == bottomRightLon);
  24.     Assert.isTrue(21.79999998304993 == bottomRightLat);
  25. }

geoShape

  1. @Test
  2. @SneakyThrows(IOException.class)
  3. void geoShape() {
  5.     //1.创建索引
  6.     createIndexAndSaveShape();
  8.     //2.查询甘肃黑龙江台湾三角形完全包含的，理论上返回北京点
  9.     SearchResponse<TestShape> search = primaryClient.search(s -> s
  10.             .index(GEO_SHAPE_INDEX_NAME)
  11.             .query(q -> q.geoShape(g -> g
  12.                     .field("location")
  13.                     .shape(sh -> sh
  14.                             .indexedShape(f -> f
  15.                                     .index(GEO_SHAPE_INDEX_NAME)
  16.                                     .id("ghtTriangleShape")
  17.                                     .path("location")
  18.                             )
  19.                             .relation(GeoShapeRelation.Within)
  20.                     )
  21.             )), TestShape.class
  22.     );
  24.     //3.校验
  25.     Assert.isTrue(1 == search.hits().hits().size());
  26. }
  28. @SneakyThrows(IOException.class)
  29. void createIndexAndSaveShape() {
  31.     //1.判定索引是否存在
  32.     boolean exist = primaryClient.indices().exists(e -> e.index(GEO_SHAPE_INDEX_NAME)).value();
  34.     //2.不存在创建索引
  35.     if (!exist) {
  37.         //3.创建索引
  38.         CreateIndexResponse createIndexResponse = primaryClient
  39.                 .indices()
  40.                 .create(c -> c
  41.                         .index(GEO_SHAPE_INDEX_NAME)
  42.                         .mappings(m -> m
  43.                                 .properties("name", p -> p.keyword(k -> k))
  44.                                 .properties("location", p -> p.geoShape(gs -> gs))
  45.                                 .dynamic(DynamicMapping.False)
  46.                         )
  47.                 );
  49.         //4.校验
  50.         Assert.isTrue(Boolean.TRUE.equals(createIndexResponse.acknowledged()));
  51.     }
  53.     //5.清空数据
  54.     DeleteByQueryResponse deleteByQueryResponse = primaryClient.deleteByQuery(d -> d
  55.             .index(GEO_SHAPE_INDEX_NAME)
  56.             .query(q -> q.matchAll(m -> m))
  57.             .refresh(Boolean.TRUE)
  58.     );
  59.     Assert.isTrue(0 == deleteByQueryResponse.failures().size());
  61.     //6.准备数据(北京坐标点、甘肃黑龙江台湾三角形、宁夏新疆西藏三角形)
  62.     GeoJsonPoint point = GeoJsonPoint.of(116.20, 39.56);
  63.     TestShape beijingShape = new TestShape();
  64.     beijingShape.setName("北京点");
  65.     beijingShape.setLocation(JSONUtil.parseObj(point.toJson()));
  67.     GeoJsonPolygon ghtTriangle = GeoJsonPolygon.of(CollUtil.newArrayList(
  68.             new Point(92.13, 32.31),
  69.             new Point(125.03, 50.49),
  70.             new Point(119.18, 20.45),
  71.             new Point(92.13, 32.31)
  72.     ));
  73.     TestShape ghtTriangleShape = new TestShape();
  74.     ghtTriangleShape.setName("甘肃黑龙江台湾三角形");
  75.     ghtTriangleShape.setLocation(JSONUtil.parseObj(ghtTriangle.toJson()));
  77.     GeoJsonPolygon nxxTriangle = GeoJsonPolygon.of(CollUtil.newArrayList(
  78.             new Point(105.49, 38.08),
  79.             new Point(96.37, 42.45),
  80.             new Point(80.24, 31.29),
  81.             new Point(105.49, 38.08)
  82.     ));
  83.     TestShape nxxTriangleShape = new TestShape();
  84.     nxxTriangleShape.setName("宁夏新疆西藏三角形");
  85.     nxxTriangleShape.setLocation(JSONUtil.parseObj(nxxTriangle.toJson()));
  87.     //7.存入数据
  88.     BulkResponse bulk = primaryClient.bulk(b -> b
  89.             .index(GEO_SHAPE_INDEX_NAME)
  90.             .operations(o -> o.create(c -> c.document(beijingShape).id("beijingShape")))
  91.             .operations(o -> o.create(c -> c.document(ghtTriangleShape).id("ghtTriangleShape")))
  92.             .operations(o -> o.create(c -> c.document(nxxTriangleShape).id("nxxTriangleShape")))
  93.             .refresh(Refresh.True)
  94.     );
  95.     Assert.isFalse(bulk.errors());
  96. }

4.完成版单元测试

  1. import cn.hutool.core.collection.CollStreamUtil;
  2. import cn.hutool.core.collection.CollUtil;
  3. import cn.hutool.core.lang.Assert;
  4. import cn.hutool.json.JSONUtil;
  5. import co.elastic.clients.elasticsearch.ElasticsearchClient;
  6. import co.elastic.clients.elasticsearch._types.*;
  7. import co.elastic.clients.elasticsearch._types.aggregations.Aggregate;
  8. import co.elastic.clients.elasticsearch._types.aggregations.AggregationRange;
  9. import co.elastic.clients.elasticsearch._types.aggregations.GeoHashGridBucket;
  10. import co.elastic.clients.elasticsearch._types.aggregations.RangeBucket;
  11. import co.elastic.clients.elasticsearch._types.mapping.DynamicMapping;
  12. import co.elastic.clients.elasticsearch.core.BulkRequest;
  13. import co.elastic.clients.elasticsearch.core.BulkResponse;
  14. import co.elastic.clients.elasticsearch.core.DeleteByQueryResponse;
  15. import co.elastic.clients.elasticsearch.core.SearchResponse;
  16. import co.elastic.clients.elasticsearch.core.search.Hit;
  17. import co.elastic.clients.elasticsearch.indices.CreateIndexResponse;
  18. import com.ftc.elasticsearchtest.entity.Omission;
  19. import com.ftc.elasticsearchtest.entity.TestShape;
  20. import lombok.SneakyThrows;
  21. import org.junit.jupiter.api.BeforeEach;
  22. import org.junit.jupiter.api.Test;
  23. import org.springframework.beans.factory.annotation.Qualifier;
  24. import org.springframework.boot.test.context.SpringBootTest;
  25. import org.springframework.data.elasticsearch.core.geo.GeoJsonPoint;
  26. import org.springframework.data.elasticsearch.core.geo.GeoJsonPolygon;
  27. import org.springframework.data.geo.Point;
  29. import javax.annotation.Resource;
  30. import java.io.IOException;
  31. import java.util.List;
  33. /**
  34.  * @author: 冯铁城 [17615007230@163.com]
  35.  * @date: 2022-08-29 09:35:30
  36.  * @describe: ElasticSearch地理位置API单元测试
  37.  */
  38. @SpringBootTest
  39. public class ElasticSearchGeoTest {
  41.     @Resource
  42.     @Qualifier("primaryElasticsearchClient")
  43.     private ElasticsearchClient primaryClient;
  45.     @Resource
  46.     @Qualifier("secondaryElasticsearchClient")
  47.     private ElasticsearchClient secondaryClient;
  49.     /**
  50.      * geo_point索引名称
  51.      */
  52.     private static final String GEO_POINT_INDEX_NAME = "omission";
  54.     /**
  55.      * geo_shape索引名称
  56.      */
  57.     private static final String GEO_SHAPE_INDEX_NAME = "geo_shape";
  59.     /**
  60.      * GEO_POINT数据
  61.      */
  62.     private static final String GEO_POINT_DATA_STR = "[{\"name\":\"北京\",\"location\":[116.2,39.56]},{\"name\":\"山东\",\"location\":[114.19,34.22]},{\"name\":\"湖北\",\"location\":[108.21,29.01]},{\"name\":\"湖南\",\"location\":[108.47,24.38]},{\"name\":\"云南\",\"location\":[97.31,21.8]},{\"name\":\"新疆\",\"location\":[86.37,42.45]}]";
  64.     @BeforeEach
  65.     @SneakyThrows(IOException.class)
  66.     void createIndexAndSaveData() {
  68.         //1.判定索引是否存在
  69.         boolean exist = primaryClient.indices().exists(e -> e.index(GEO_POINT_INDEX_NAME)).value();
  71.         //2.不存在创建索引
  72.         if (!exist) {
  74.             //3.创建索引
  75.             CreateIndexResponse createIndexResponse = primaryClient
  76.                     .indices()
  77.                     .create(c -> c
  78.                             .index(GEO_POINT_INDEX_NAME + "_1")
  79.                             .aliases(GEO_POINT_INDEX_NAME, a -> a)
  80.                             .mappings(m -> m
  81.                                     .properties("name", p -> p.keyword(k -> k))
  82.                                     .properties("location", p -> p.geoPoint(g -> g))
  83.                             )
  84.                             .settings(s -> s
  85.                                     .refreshInterval(r -> r.time("1s"))
  86.                                     .numberOfShards("3")
  87.                                     .numberOfReplicas("1")
  88.                             )
  89.                     );
  91.             //4.校验是否异常
  92.             Assert.isTrue(Boolean.TRUE.equals(createIndexResponse.acknowledged()));
  93.         }
  95.         //5.清空数据
  96.         DeleteByQueryResponse deleteByQueryResponse = primaryClient.deleteByQuery(d -> d
  97.                 .index(GEO_POINT_INDEX_NAME)
  98.                 .query(q -> q.matchAll(m -> m))
  99.                 .refresh(Boolean.TRUE)
  100.         );
  101.         Assert.isTrue(0 == deleteByQueryResponse.failures().size());
  103.         //6.构建新增数据
  104.         List<Omission> omissions = JSONUtil.toList(GEO_POINT_DATA_STR, Omission.class);
  105.         BulkRequest.Builder builder = new BulkRequest.Builder();
  106.         builder.index(GEO_POINT_INDEX_NAME);
  107.         omissions.forEach(om -> builder.operations(o -> o.create(c -> c.document(om))));
  108.         builder.refresh(Refresh.True);
  110.         //7.新增数据
  111.         BulkResponse bulk = primaryClient.bulk(builder.build());
  112.         Assert.isFalse(bulk.errors());
  113.     }
  115.     @Test
  116.     @SneakyThrows(IOException.class)
  117.     void geoBoundingBox() {
  119.         //1.以宁夏为左上角，台湾为右下角，可以获取到山东，湖南，湖北的相关信息
  120.         SearchResponse<Omission> search = secondaryClient.search(s -> s
  121.                 .index(GEO_POINT_INDEX_NAME)
  122.                 .query(q -> q.constantScore(c -> c.filter(f -> f.geoBoundingBox(g -> g
  123.                         .field("location")
  124.                         .boundingBox(b -> b.tlbr(t -> t
  125.                                 .topLeft(tl -> tl.latlon(l -> l
  126.                                         .lon(104.17)
  127.                                         .lat(35.14)
  128.                                 ))
  129.                                 .bottomRight(br -> br.latlon(l -> l
  130.                                         .lon(119.18)
  131.                                         .lat(20.45)
  132.                                 ))
  133.                         ))
  134.                 )))), Omission.class
  135.         );
  137.         //2.校验
  138.         List<Hit<Omission>> hits = search.hits().hits();
  139.         Assert.isTrue(3 == hits.size());
  140.         List<Omission> omissions = CollStreamUtil.toList(search.hits().hits(), Hit::source);
  141.         List<String> names = CollStreamUtil.toList(omissions, Omission::getName);
  142.         Assert.isTrue(names.contains("山东"));
  143.         Assert.isTrue(names.contains("湖北"));
  144.         Assert.isTrue(names.contains("湖南"));
  145.     }
  147.     @Test
  148.     @SneakyThrows(IOException.class)
  149.     void geoDistance() {
  151.         //1.以北京为圆心，获取2000km内的省份，理论上应该返回北京，山东，湖北，以及湖南4个省份
  152.         SearchResponse<Omission> search = secondaryClient.search(s -> s
  153.                 .index(GEO_POINT_INDEX_NAME)
  154.                 .query(q -> q.constantScore(c -> c.filter(f -> f.geoDistance(g -> g
  155.                         .field("location")
  156.                         .location(l -> l.latlon(ll -> ll
  157.                                 .lon(116.2)
  158.                                 .lat(39.56)
  159.                         ))
  160.                         .distance("2000km")
  161.                         .distanceType(GeoDistanceType.Arc)
  162.                 )))), Omission.class
  163.         );
  165.         //2.校验
  166.         Assert.isTrue(4 == search.hits().hits().size());
  167.         List<Omission> omissions = CollStreamUtil.toList(search.hits().hits(), Hit::source);
  168.         List<String> names = CollStreamUtil.toList(omissions, Omission::getName);
  169.         Assert.isTrue(names.contains("北京"));
  170.         Assert.isTrue(names.contains("山东"));
  171.         Assert.isTrue(names.contains("湖北"));
  172.         Assert.isTrue(names.contains("湖南"));
  173.     }
  175.     @Test
  176.     @SneakyThrows(IOException.class)
  177.     void sort() {
  179.         //1.以北京为圆心，获取2000km内的省份，并按照距离倒序 理论上返回顺序为湖南，湖北，山东，北京
  180.         SearchResponse<Omission> search = secondaryClient.search(s -> s
  181.                 .index(GEO_POINT_INDEX_NAME)
  182.                 .query(q -> q.constantScore(c -> c.filter(f -> f.geoDistance(g -> g
  183.                         .field("location")
  184.                         .location(l -> l.latlon(ll -> ll
  185.                                 .lon(116.2)
  186.                                 .lat(39.56)
  187.                         ))
  188.                         .distance("2000km")
  189.                 ))))
  190.                 .sort(sort -> sort.geoDistance(g -> g
  191.                         .field("location")
  192.                         .location(l -> l.latlon(ll -> ll
  193.                                 .lon(116.2)
  194.                                 .lat(39.56)
  195.                         ))
  196.                         .order(SortOrder.Desc)
  197.                         .unit(DistanceUnit.Kilometers)
  198.                 )), Omission.class
  199.         );
  201.         //2.校验
  202.         Assert.isTrue(4 == search.hits().hits().size());
  203.         Assert.isTrue("湖南".equals(search.hits().hits().get(0).source().getName()));
  204.         Assert.isTrue("湖北".equals(search.hits().hits().get(1).source().getName()));
  205.         Assert.isTrue("山东".equals(search.hits().hits().get(2).source().getName()));
  206.         Assert.isTrue("北京".equals(search.hits().hits().get(3).source().getName()));
  207.     }
  209.     @Test
  210.     @SneakyThrows(IOException.class)
  211.     void aggregationGeoDistance() {
  213.         //1.统计距离北京（包括北京）0~1000km范围、1000km到2000km范围内的省市数量
  214.         SearchResponse<Omission> search = primaryClient.search(s -> s
  215.                 .index(GEO_POINT_INDEX_NAME)
  216.                 .aggregations("omissionNumber", a -> a.geoDistance(g -> g
  217.                         .field("location")
  218.                         .origin(o -> o.latlon(l -> l
  219.                                 .lon(116.2)
  220.                                 .lat(39.56)
  221.                         ))
  222.                         .ranges(
  223.                                 AggregationRange.of(ar -> ar.from("0").to("1000")),
  224.                                 AggregationRange.of(ar -> ar.from("1000").to("2000"))
  225.                         )
  226.                         .unit(DistanceUnit.Kilometers)
  227.                         .distanceType(GeoDistanceType.Plane)
  228.                 )), Omission.class
  229.         );
  231.         //2.校验
  232.         Aggregate omissionNumber = search.aggregations().get("omissionNumber");
  233.         List<RangeBucket> rangeBuckets = omissionNumber.geoDistance().buckets().array();
  234.         Assert.isTrue(2 == rangeBuckets.size());
  235.         for (RangeBucket rangeBucket : rangeBuckets) {
  236.             Assert.isTrue(2 == rangeBucket.docCount());
  237.         }
  238.     }
  240.     @Test
  241.     @SneakyThrows(IOException.class)
  242.     void aggregationGeoHashGrid() {
  244.         //1.网格聚合，指定geoHash长度为1
  245.         SearchResponse<Omission> search = primaryClient.search(s -> s
  246.                 .index(GEO_POINT_INDEX_NAME)
  247.                 .aggregations("geoHashData", a -> a.geohashGrid(g -> g
  248.                         .field("location")
  249.                         .precision(p -> p.geohashLength(1))
  250.                 )), Omission.class
  251.         );
  253.         //2.校验
  254.         Aggregate geoHashData = search.aggregations().get("geoHashData");
  255.         List<GeoHashGridBucket> geoHashGridBuckets = geoHashData.geohashGrid().buckets().array();
  256.         Assert.isTrue(2 == geoHashGridBuckets.size());
  257.     }
  259.     @Test
  260.     @SneakyThrows(IOException.class)
  261.     void aggregationGeoBounds() {
  263.         //1.得到一个可以包含所有已存储数据的矩形
  264.         SearchResponse<Omission> search = primaryClient.search(s -> s
  265.                 .index(GEO_POINT_INDEX_NAME)
  266.                 .aggregations("box", a -> a.geoBounds(g -> g
  267.                         .field("location")
  268.                 )), Omission.class
  269.         );
  271.         //2.校验
  272.         Aggregate box = search.aggregations().get("box");
  273.         GeoBounds bounds = box.geoBounds().bounds();
  274.         Assert.isTrue(bounds.isTlbr());
  275.         double topLeftLon = bounds.tlbr().topLeft().latlon().lon();
  276.         double topLeftLat = bounds.tlbr().topLeft().latlon().lat();
  277.         double bottomRightLon = bounds.tlbr().bottomRight().latlon().lon();
  278.         double bottomRightLat = bounds.tlbr().bottomRight().latlon().lat();
  279.         Assert.isTrue(86.36999999172986 == topLeftLon);
  280.         Assert.isTrue(42.44999995920807 == topLeftLat);
  281.         Assert.isTrue(116.19999996386468 == bottomRightLon);
  282.         Assert.isTrue(21.79999998304993 == bottomRightLat);
  283.     }
  285.     @Test
  286.     @SneakyThrows(IOException.class)
  287.     void geoShape() {
  289.         //1.创建索引
  290.         createIndexAndSaveShape();
  292.         //2.查询甘肃黑龙江台湾三角形完全包含的，理论上返回北京点
  293.         SearchResponse<TestShape> search = primaryClient.search(s -> s
  294.                 .index(GEO_SHAPE_INDEX_NAME)
  295.                 .query(q -> q.geoShape(g -> g
  296.                         .field("location")
  297.                         .shape(sh -> sh
  298.                                 .indexedShape(f -> f
  299.                                         .index(GEO_SHAPE_INDEX_NAME)
  300.                                         .id("ghtTriangleShape")
  301.                                         .path("location")
  302.                                 )
  303.                                 .relation(GeoShapeRelation.Within)
  304.                         )
  305.                 )), TestShape.class
  306.         );
  308.         //3.校验
  309.         Assert.isTrue(1 == search.hits().hits().size());
  310.     }
  312.     @SneakyThrows(IOException.class)
  313.     void createIndexAndSaveShape() {
  315.         //1.判定索引是否存在
  316.         boolean exist = primaryClient.indices().exists(e -> e.index(GEO_SHAPE_INDEX_NAME)).value();
  318.         //2.不存在创建索引
  319.         if (!exist) {
  321.             //3.创建索引
  322.             CreateIndexResponse createIndexResponse = primaryClient
  323.                     .indices()
  324.                     .create(c -> c
  325.                             .index(GEO_SHAPE_INDEX_NAME)
  326.                             .mappings(m -> m
  327.                                     .properties("name", p -> p.keyword(k -> k))
  328.                                     .properties("location", p -> p.geoShape(gs -> gs))
  329.                                     .dynamic(DynamicMapping.False)
  330.                             )
  331.                     );
  333.             //4.校验
  334.             Assert.isTrue(Boolean.TRUE.equals(createIndexResponse.acknowledged()));
  335.         }
  337.         //5.清空数据
  338.         DeleteByQueryResponse deleteByQueryResponse = primaryClient.deleteByQuery(d -> d
  339.                 .index(GEO_SHAPE_INDEX_NAME)
  340.                 .query(q -> q.matchAll(m -> m))
  341.                 .refresh(Boolean.TRUE)
  342.         );
  343.         Assert.isTrue(0 == deleteByQueryResponse.failures().size());
  345.         //6.准备数据(北京坐标点、甘肃黑龙江台湾三角形、宁夏新疆西藏三角形)
  346.         GeoJsonPoint point = GeoJsonPoint.of(116.20, 39.56);
  347.         TestShape beijingShape = new TestShape();
  348.         beijingShape.setName("北京点");
  349.         beijingShape.setLocation(JSONUtil.parseObj(point.toJson()));
  351.         GeoJsonPolygon ghtTriangle = GeoJsonPolygon.of(CollUtil.newArrayList(
  352.                 new Point(92.13, 32.31),
  353.                 new Point(125.03, 50.49),
  354.                 new Point(119.18, 20.45),
  355.                 new Point(92.13, 32.31)
  356.         ));
  357.         TestShape ghtTriangleShape = new TestShape();
  358.         ghtTriangleShape.setName("甘肃黑龙江台湾三角形");
  359.         ghtTriangleShape.setLocation(JSONUtil.parseObj(ghtTriangle.toJson()));
  361.         GeoJsonPolygon nxxTriangle = GeoJsonPolygon.of(CollUtil.newArrayList(
  362.                 new Point(105.49, 38.08),
  363.                 new Point(96.37, 42.45),
  364.                 new Point(80.24, 31.29),
  365.                 new Point(105.49, 38.08)
  366.         ));
  367.         TestShape nxxTriangleShape = new TestShape();
  368.         nxxTriangleShape.setName("宁夏新疆西藏三角形");
  369.         nxxTriangleShape.setLocation(JSONUtil.parseObj(nxxTriangle.toJson()));
  371.         //7.存入数据
  372.         BulkResponse bulk = primaryClient.bulk(b -> b
  373.                 .index(GEO_SHAPE_INDEX_NAME)
  374.                 .operations(o -> o.create(c -> c.document(beijingShape).id("beijingShape")))
  375.                 .operations(o -> o.create(c -> c.document(ghtTriangleShape).id("ghtTriangleShape")))
  376.                 .operations(o -> o.create(c -> c.document(nxxTriangleShape).id("nxxTriangleShape")))
  377.                 .refresh(Refresh.True)
  378.         );
  379.         Assert.isFalse(bulk.errors());
  380.     }
  381. }