轨迹模型_模型_时空数据库_云数据库PolarDB_阿里云技术文档

轨迹数据是针对移动对象（Moving Feature）所记录的连续位置变化信息，例如车辆的轨迹、人的轨迹等。轨迹数据是一类典型的时空数据，分析和理解这些轨迹数据能帮助人们研究许多重要问题。

概述

Ganos Trajectory是云原生关系型数据库POLARDB的一个扩展，提供了一组数据类型、函数和存储过程，帮助用户高效地管理、查询和分析时空轨迹数据。

快速入门

创建扩展

Create Extension Ganos_trajectory cascade;

轨迹的枚举类型

CREATE TYPE leaftype AS ENUM ('STPOINT', 'STPOLYGON');

创建轨迹表

Create Table traj_table (id integer, traj trajectory);

插入轨迹数据

insert into traj_table values (1, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326), '[2010-01-01 14:30, 2010-01-01 15:30)'::tsrange, '{"leafcount": 3,"attributes" : {"velocity" : {"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"accuracy":{"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"bearing":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]},"acceleration":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]}}}')), (2, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326), '2010-01-01 14:30'::timestamp, '2010-01-01 15:30'::timestamp, '{"leafcount": 3,"attributes" : {"velocity" : {"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"accuracy":{"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"bearing":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]},"acceleration":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]}}}')), (3, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326),ARRAY['2010-01-01 14:30'::timestamp, '2010-01-01 15:00'::timestamp, '2010-01-01 15:30'::timestamp], '{"leafcount": 3,"attributes" : {"velocity" : {"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"accuracy":{"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"bearing":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]},"acceleration":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]}}}')), (4, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326), '[2010-01-01 14:30, 2010-01-01 15:30)'::tsrange, null));

创建轨迹空间索引

--创建基于函数的空间索引，加速空间过滤
create index tr_spatial_geometry_index on traj_table using gist (st_trajectoryspatial(traj));

--空间查询时，加速空间过滤
select id, traj_id from traj_test where st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))')) = true and st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.5172424485498 39.904984732832744,116.5543342491403 39.904984732832744,116.5543342491403 39.93294918082651,116.5172424485498 39.93294918082651,116.5172424485498 39.904984732832744))')) = true;

创建轨迹时间索引

--创建基于函数的时间段索引，加速时间过滤
create index tr_timespan_time_index on traj_table using gist (st_timespan(traj));

--创建基于函数的轨迹起止时间
create index tr_starttime_index on traj_table using btree (st_starttime(traj));
create index tr_endtime_index on traj_table using btree (st_endtime(traj));

--查询时，加速时间过滤
select id, traj_id from traj_split where st_starttime(traj) > '2008-02-02 13:30:44'::timestamp and st_endtime(traj) < '2008-02-03 17:30:44'::timestamp;

创建轨迹时间+空间复合索引(btree_gist)

btree_gist支持时间+空间的复合索引，适合轨迹查询条件中既有时间过滤，又有空间过滤的情况，使得时空复合查询SQL语法简单，且查询效率高。

--建立btree_gist 起始时间、终止时间、空间复合索引
create index tr_traj_test_stm_etm_sp_index on traj_test using gist (st_starttime(traj),st_endtime(traj),st_trajectoryspatial(traj));

--时空查询
select id,traj_id from traj_test where st_starttime(traj) > '2008-02-02 13:30:44'::timestamp and st_endtime(traj) < '2008-02-03 17:30:44'::timestamp and st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))')) = true and st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.5172424485498 39.904984732832744,116.5543342491403 39.904984732832744,116.5543342491403 39.93294918082651,116.5172424485498 39.93294918082651,116.5172424485498 39.904984732832744))')) = true;

查询轨迹起、止时间

select st_startTime(traj), st_endTime(traj) from traj_table ;
    st_starttime     |     st_endtime      
---------------------+---------------------
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 11:30:00 | 2010-01-01 15:00:00
 2010-01-01 11:30:00 | 2010-01-01 15:00:00
 2010-01-01 11:30:00 | 2010-01-01 15:00:00
(8 rows)

轨迹查询

--通过插值函数查询轨迹点的属性
Select ST_velocityAtTime(traj, '2010-01-01 12:45') from traj_table  where id > 5; 
st_velocityattime 
-------------------                 
5                 
5  
4.16666666666667
(3 rows)

分析轨迹间的相近性

postgres=# Select ST_euclideanDistance((Select traj From traj_table Where id = 6), (Select traj From traj_table Where id = 7));
 st_euclideandistance 
----------------------
   0.0334968923954815
(1 row)

删除扩展

Drop Extension Ganos_trajectory cascade;

快速入门

创建扩展

Create Extension Ganos_trajectory cascade;

轨迹的枚举类型

CREATE TYPE leaftype AS ENUM ('STPOINT', 'STPOLYGON');

创建轨迹表

Create Table traj_table (id integer, traj trajectory);

插入轨迹数据

insert into traj_table values (1, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326), '[2010-01-01 14:30, 2010-01-01 15:30)'::tsrange, '{"leafcount": 3,"attributes" : {"velocity" : {"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"accuracy":{"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"bearing":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]},"acceleration":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]}}}')), (2, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326), '2010-01-01 14:30'::timestamp, '2010-01-01 15:30'::timestamp, '{"leafcount": 3,"attributes" : {"velocity" : {"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"accuracy":{"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"bearing":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]},"acceleration":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]}}}')), (3, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326),ARRAY['2010-01-01 14:30'::timestamp, '2010-01-01 15:00'::timestamp, '2010-01-01 15:30'::timestamp], '{"leafcount": 3,"attributes" : {"velocity" : {"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"accuracy":{"type":"integer","length":4,"nullable":false,"value":[120, 130, 140]},"bearing":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]},"acceleration":{"type":"float","length":4,"nullable":false,"value":[120, 130, 140]}}}')), (4, ST_MakeTrajectory('STPOINT'::leaftype, st_geomfromtext('LINESTRING (114 35, 115 36, 116 37)', 4326), '[2010-01-01 14:30, 2010-01-01 15:30)'::tsrange, null));

创建轨迹空间索引

--创建基于函数的空间索引，加速空间过滤
create index tr_spatial_geometry_index on traj_table using gist (st_trajectoryspatial(traj));

--空间查询时，加速空间过滤
select id, traj_id from traj_test where st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))')) = true and st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.5172424485498 39.904984732832744,116.5543342491403 39.904984732832744,116.5543342491403 39.93294918082651,116.5172424485498 39.93294918082651,116.5172424485498 39.904984732832744))')) = true;

创建轨迹时间索引

--创建基于函数的时间段索引，加速时间过滤
create index tr_timespan_time_index on traj_table using gist (st_timespan(traj));

--创建基于函数的轨迹起止时间
create index tr_starttime_index on traj_table using btree (st_starttime(traj));
create index tr_endtime_index on traj_table using btree (st_endtime(traj));

--查询时，加速时间过滤
select id, traj_id from traj_split where st_starttime(traj) > '2008-02-02 13:30:44'::timestamp and st_endtime(traj) < '2008-02-03 17:30:44'::timestamp;

创建轨迹时间+空间复合索引(btree_gist)

btree_gist支持时间+空间的复合索引，适合轨迹查询条件中既有时间过滤，又有空间过滤的情况，使得时空复合查询SQL语法简单，且查询效率高。

--建立btree_gist 起始时间、终止时间、空间复合索引
create index tr_traj_test_stm_etm_sp_index on traj_test using gist (st_starttime(traj),st_endtime(traj),st_trajectoryspatial(traj));

--时空查询
select id,traj_id from traj_test where st_starttime(traj) > '2008-02-02 13:30:44'::timestamp and st_endtime(traj) < '2008-02-03 17:30:44'::timestamp and st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))')) = true and st_intersects(st_trajectoryspatial(traj), ST_GeomFromText('POLYGON((116.5172424485498 39.904984732832744,116.5543342491403 39.904984732832744,116.5543342491403 39.93294918082651,116.5172424485498 39.93294918082651,116.5172424485498 39.904984732832744))')) = true;

查询轨迹起、止时间

select st_startTime(traj), st_endTime(traj) from traj_table ;
    st_starttime     |     st_endtime      
---------------------+---------------------
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 14:30:00 | 2010-01-01 15:30:00
 2010-01-01 11:30:00 | 2010-01-01 15:00:00
 2010-01-01 11:30:00 | 2010-01-01 15:00:00
 2010-01-01 11:30:00 | 2010-01-01 15:00:00
(8 rows)

轨迹查询

--通过插值函数查询轨迹点的属性
Select ST_velocityAtTime(traj, '2010-01-01 12:45') from traj_table  where id > 5; 
st_velocityattime 
-------------------                 
5                 
5  
4.16666666666667
(3 rows)

分析轨迹间的相近性

postgres=# Select ST_euclideanDistance((Select traj From traj_table Where id = 6), (Select traj From traj_table Where id = 7));
 st_euclideandistance 
----------------------
   0.0334968923954815
(1 row)

删除扩展

Drop Extension Ganos_trajectory cascade;

SQL参考

详细SQL手册请参见Trajectory SQL参考。

轨迹模型_模型_时空数据库_云数据库PolarDB

轨迹模型

概述

快速入门

快速入门

SQL参考

版权声明

评论