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geo_geohash_neighbors()
适用于:✅Microsoft Fabric✅Azure 数据资源管理器Azure Monitor✅Microsoft✅ Sentinel
计算 Geohash 邻居。
阅读有关 geohash
的详细信息。
语法
geo_geohash_neighbors(
geohash)
详细了解语法约定。
参数
客户 | 类型 | 必需 | 说明 |
---|---|---|---|
geohash | string |
✔️ | 由 geo_point_to_geohash() 计算得出的 geohash 值。 geohash 字符串必须介于 1 到 18 个字符之间。 |
返回
Geohash 邻居的数组。 如果 Geohash 无效,则查询会生成 null 结果。
示例
以下示例计算 Geohash 邻居。
print neighbors = geo_geohash_neighbors('sunny')
输出
neighbors |
---|
["sunnt","sunpj","sunnx","sunpn","sunnv","sunpp","sunnz","sunnw"] |
以下示例计算包含其邻居的输入 Geohash 的数组。
let geohash = 'sunny';
print cells = array_concat(pack_array(geohash), geo_geohash_neighbors(geohash))
输出
单元格 |
---|
["sunny","sunnt","sunpj","sunnx","sunpn","sunnv","sunpp","sunnz","sunnw"] |
以下示例计算 Geohash 多边形 GeoJSON 几何图形集合。
let geohash = 'sunny';
print cells = array_concat(pack_array(geohash), geo_geohash_neighbors(geohash))
| mv-expand cells to typeof(string)
| project polygons = geo_geohash_to_polygon(cells)
| summarize arr = make_list(polygons)
| project geojson = bag_pack("type", "Feature","geometry", bag_pack("type", "GeometryCollection", "geometries", arr), "properties", bag_pack("name", "polygons"))
输出
geojson |
---|
{"type": "Feature","geometry": {"type": "GeometryCollection","geometries": [ {"type":"Polygon","coordinates":[[[42.451171875,23.6865234375],[42.4951171875,23.6865234375],[42.4951171875,23.73046875],[42.451171875,23.73046875],[42.451171875,23.6865234375]]]}, {"type":"Polygon","coordinates":[[[42.4072265625,23.642578125],[42.451171875,23.642578125],[42.451171875,23.6865234375],[42.4072265625,23.6865234375],[42.4072265625,23.642578125]]]}, {"type":"Polygon","coordinates":[[[42.4072265625,23.73046875],[42.451171875,23.73046875],[42.451171875,23.7744140625],[42.4072265625,23.7744140625],[42.4072265625,23.73046875]]]}, {"type":"Polygon","coordinates":[[[42.4951171875,23.642578125],[42.5390625,23.642578125],[42.5390625,23.6865234375],[42.4951171875,23.6865234375],[42.4951171875,23.642578125]]]}, {"type":"Polygon","coordinates":[[[42.451171875,23.73046875],[42.4951171875,23.73046875],[42.4951171875,23.7744140625],[42.451171875,23.7744140625],[42.451171875,23.73046875]]]}, {"type":"Polygon","coordinates":[[[42.4072265625,23.6865234375],[42.451171875,23.6865234375],[42.451171875,23.73046875],[42.4072265625,23.73046875],[42.4072265625,23.6865234375]]]}, {"type":"Polygon","coordinates":[[[42.4951171875,23.73046875],[42.5390625,23.73046875],[42.5390625,23.7744140625],[42.4951171875,23.7744140625],[42.4951171875,23.73046875]]]}, {"type":"Polygon","coordinates":[[[42.4951171875,23.6865234375],[42.5390625,23.6865234375],[42.5390625,23.73046875],[42.4951171875,23.73046875],[42.4951171875,23.6865234375]]]}, {"type":"Polygon","coordinates":[[[42.451171875,23.642578125],[42.4951171875,23.642578125],[42.4951171875,23.6865234375],[42.451171875,23.6865234375],[42.451171875,23.642578125]]]}]}, "properties": {"name": "polygons"}} |
以下示例计算表示 Geohash 及其邻居的多边形联合。
let h3cell = 'sunny';
print cells = array_concat(pack_array(h3cell), geo_geohash_neighbors(h3cell))
| mv-expand cells to typeof(string)
| project polygons = geo_geohash_to_polygon(cells)
| summarize arr = make_list(polygons)
| project polygon = geo_union_polygons_array(arr)
输出
polygon |
---|
{"type":"Polygon","coordinates":[[[42.4072265625,23.642578125],[42.451171875,23.642578125],[42.4951171875,23.642578125],[42.5390625,23.642578125],[42.5390625,23.686523437500004],[42.5390625,23.730468750000004],[42.5390625,23.7744140625],[42.4951171875,23.7744140625],[42.451171875,23.7744140625],[42.407226562499993,23.7744140625],[42.4072265625,23.73046875],[42.4072265625,23.6865234375],[42.4072265625,23.642578125]]]} |
以下示例由于 Geohash 令牌输入无效而返回 true。
print invalid = isnull(geo_geohash_neighbors('a'))
输出
无效 |
---|
1 |