Geospark空间查询

小鱼儿 2023-10-04 12:12 11阅读 0赞

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title: ‘模板’  
date: 2021-01-01 00:00:00  
tags: \[scala\]  
published: true  
hideInList: false  
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> Geospark空间查询

## Geospark空间查询 ##

#### GeoSpark空间索引 ####

1.  GeoSpark提供两种空间索引：Quad-Tree和R-Tree
2.  和上一节一样，我们初始化一个SparkContext，并调用GeoSpark的ShapefileReader，将我们的Shape文件导入。

SparkConf conf = new SparkConf();
    conf.setAppName("GeoSpark02");
    conf.setMaster("local[*]");
    conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
    conf.set("spark.kryo.registrator", "org.datasyslab.geospark.serde.GeoSparkKryoRegistrator");
    JavaSparkContext sc = new JavaSparkContext(conf);
    
    // Get SpatialRDD
    String shapeInputLocation = Learn02.class.getResource("/parks").toString();
    SpatialRDD rdd = ShapefileReader.readToGeometryRDD(sc, shapeInputLocation);

#### 构建索引 ####

// 构建索引
    boolean buildOnSpatialPartitionedRDD = false; // 如果只需要在做空间分析的时候构建索引,则设置为true
    rdd.buildIndex(IndexType.QUADTREE, buildOnSpatialPartitionedRDD);

#### 使用索引查询 ####

// 查询
    GeometryFactory geometryFactory = new GeometryFactory();
    Coordinate[] coordinates = new Coordinate[5];
    coordinates[0] = new Coordinate(-123.1,49.2);
    coordinates[1] = new Coordinate(-123.1,49.3);
    coordinates[2] = new Coordinate(-123.2,49.3);
    coordinates[3] = new Coordinate(-123.2,29.2);
    coordinates[4] = coordinates[0]; // The last coordinate is the same as the first coordinate in order to compose a closed ring
    Polygon polygonObject = geometryFactory.createPolygon(coordinates);
    boolean usingIndex = true;  // 使用索引
    JavaRDD<Geometry> queryResult = RangeQuery.SpatialRangeQuery(rdd, polygonObject, false, usingIndex);
    System.out.println(String.format("查询结果总数为: %d",queryResult.count()));

查询结果总数为: 62

##### 3. 输出查询结果 #####

// 遍历查询结果
    queryResult.foreach(new VoidFunction<Geometry>() {
        
        @Override
        public void call(Geometry geometry) throws Exception {
        
            System.out.println(geometry);
        }
    });

POLYGON ((-123.15566057081632 49.26206733490204, -123.15564728017853 49.26241791476514, -123.15548939905344 49.262415429329856, -123.15550257747702 49.26206484963618, -123.15566057081632 49.26206733490204))  1   -9999       Kitsilano           N       
    POLYGON ((-123.15760176703519 49.261936547646954, -123.15718706338478 49.2619299178749, -123.15719832396375 49.26162160945501, -123.15761313807661 49.26162814910161, -123.15760218456263 49.26192530535148, -123.15760176703519 49.261936547646954))   2   208 Rosemary Brown Park Kitsilano   W 11th Avenue   Vine Street N   N   N
    .................................
    POLYGON ((-123.12325003271694 49.290529597005786, -123.12325184999034 
    POLYGON ((-123.11921795166444 49.288179012132034, -123.11889234917355 49.28806261407178, -123.11905901714364 49.28781953241384, -123.11954592548769 49.28796238352621, -123.11921795166444 49.288179012132034)) 80  27  Portal Park Downtown    W Hastings Street   Thurlow Street  N   N   N

#### KNN临近查询 ####

KNN临近查询用于查询距指定点最近的K个Geometry，在本案例中我们指定中心点为（-123.1,49.2），我们来查询距离这个点最近的5个公园的分布。

**注意**：QTREE索引不支持KNN查询，所以在使用KNN的时候，可以选择R-Tree索引。

// 临近查询(KNN)
    rdd.buildIndex(IndexType.RTREE, buildOnSpatialPartitionedRDD);  // QTREE不支持KNN查询
    Point pointObject = geometryFactory.createPoint(new Coordinate(-123.1,49.2));
    int K = 5; // K Nearest Neighbors
    List<Geometry> result = KNNQuery.SpatialKnnQuery(rdd, pointObject, K, usingIndex);

距离点(-123.1,49.2)最近的五个公园是:
    1: MULTIPOLYGON...  3   141 Tea Swamp Park  Mount Pleasant  E 15th Avenue   Sophia Street   N   N   N
    2: POLYGON ...  23  140 Robson Park Mount Pleasant  Kingsway    St. George Street   N   Y   N
    4: POLYGON...   18  138 Major Matthews Park Mount Pleasant  W 11th Avenue   Manitoba Street N   N   N
    5: POLYGON ...  24  136 Guelph Park Mount Pleasant  E 7th Avenue    Brunswick Street    N   N   N

#### 空间关联查询（Spatial Join Query) ####

空间关联查询：创建一个表联接（类似于SQL语句中的join关联），其中根据两层中特性的相对位置，将一个图层属性表中的字段追加到另一个图层层属性表中。

现在我们有两个图层，一个是公园（polygon），另外一个是公园里一些点（point），现在我们要把这些点所在公园的属性赋给这些点，用到的就是空间关联查询。

![img][]

// 空间关联查询
    shapeInputLocation = Learn02.class.getResource("/point").toString();
    SpatialRDD pointRdd = ShapefileReader.readToGeometryRDD(sc, shapeInputLocation);
    // analyze方法主要用来计算边界
    pointRdd.analyze();
    parkRdd.analyze();
    // spark中的分区操作,空间关联查询前必须进行
    parkRdd.spatialPartitioning(GridType.KDBTREE);
    pointRdd.spatialPartitioning(parkRdd.getPartitioner());
    
    boolean considerBoundaryIntersection = true;  // 因为是以点为基础,因此必须考虑边界
    usingIndex = false;
    JavaPairRDD<Geometry, HashSet<Geometry>> joinResult = JoinQuery.SpatialJoinQuery(parkRdd, pointRdd, usingIndex, considerBoundaryIntersection);
    System.out.println("空间关联查询结果为:");
    joinResult.foreach((kv)->{
        
        System.out.println(String.format("{%s}--{%s}", kv._1.getUserData().toString(), kv._2.toString()));
    });

SpatialJoinQuery返回一个类似于Map集合的RDD，其中Key是SpatialJoinQuery中的第一个RDD，也就是我们的pointRDD，Value是一个Set集合，集合里面每个元素都是来自于SpatialJoinQuery中的第二个RDD，也就是parkRDD，在我们这个案例下，我们的key、value都是一一对应的，但是当我们反过来执行`JoinQuery.SpatialJoinQuery(pointRdd, parkRdd, usingIndex, considerBoundaryIntersection)`，那此时key和value就是一对多关系了，因此一个公园里会有很多个点，但是一个点只会属于一个公园（边界上的点除外）。

{5}--{[POLYGON...   62  201 English Bay Beach Park  West End    Beach Avenue    Bidwell Street  N   Y   Y]}
    {10}--{[POLYGON ... 48  110 Hadden Park Kitsilano   Ogden Avenue    Cypress Street  N   Y   Y]}
    {13}--{[POLYGON ... 76  24  Marina Square   Downtown    Bayshore Drive  Denman Street   N   N   Y]}
    {14}--{[POLYGON...  77  11  Cardero Park    Downtown    Bayshore Drive  Cardero Street  N   N   Y]}
    {3}--{[POLYGON ...  74  206 Stanley Park    West End    W Georgia Street    Chilco Street   N   Y   Y]}
    {2}--{[POLYGON...   61  -9999   Sunset Beach Park   West End            Y       ]}
    {0}--{[POLYGON ...  73  -9999   Nelson Park West End            Y       ]}
    {1}--{[POLYGON ...  74  206 Stanley Park    West End    W Georgia Street    Chilco Street   N   Y   Y]}
    {15}--{[POLYGON ... 75  18  Devonian Harbour Park   Downtown    W Georgia Street    Denman Street   N   N   Y]}
    {19}--{[POLYGON... 35   28  CRAB Park at Portside   Downtown    E Waterfront Road   Main Street Y   Y   N]}
    {8}--{[POLYGON ...  73  -9999   Nelson Park West End            Y       ]}
    {6}--{[POLYGON ...  62  201 English Bay Beach Park  West End    Beach Avenue    Bidwell Street  N   Y   Y]}
    {12}--{[POLYGON ... 79  -9999   Harbour Green Park  Downtown            N       ]}
    {11}--{[POLYGON ... 78  13  Coal Harbour Park   Downtown    W Hastings Street   Broughton Street    N   N   N]}

参考链接：https://www.jianshu.com/p/458f05244479

[img]: https://img-blog.csdnimg.cn/img_convert/df5d689b697d634b36690c66b0f65322.png