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

    --创建轨迹索引,加速时空过滤效率。
    create index tr_index on trajtab using trajgist (traj);
    
    --空间查询时,加速空间过滤。
    select id, traj_id from traj_test where st_3dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'));
    
    --时间查询时,加速时间过滤。
    select id, traj_id from traj_text where st_TWithin(traj, ST_ToBox('2008-02-02 13:30:44'::timestamp,'2008-02-03 17:30:44'::timestamp));
    
    --时空查询时,加速时空过滤。
    select id, traj_id from traj_test where st_3dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'),'2008-02-02 13:30:44'::timestamp,'2008-02-03 17:30:44'::timestamp);
  • 创建特定维度轨迹索引
    --当我们只需要对轨迹进行特定维度分析时,可以只建立特定维度的索引。如我们不关心轨迹的z维时,可以使用trajgist_op_2dt建立二维+时间索引。
    create index tr_timespan_time_index on trajtab using trajgist (traj trajgist_op_2dt);
    
    --建立特定维度索引后对2维+时间查询效果会更快。
    select id, traj_id from traj_test where st_2dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'),'2008-02-02 13:30:44'::timestamp,'2008-02-03 17:30:44'::timestamp);
    
    --可以同时有多个索引存在,建立任意一个即可支持所有查询,当有多个时将自动选择最优的索引。
    create index tr_timespan_time_index on trajtab using trajgist (traj trajgist_op_2d);
    select id, traj_id from traj_test where st_2dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'));
  • 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

    --创建轨迹索引,加速时空过滤效率。
    create index tr_index on trajtab using trajgist (traj);
    
    --空间查询时,加速空间过滤。
    select id, traj_id from traj_test where st_3dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'));
    
    --时间查询时,加速时间过滤。
    select id, traj_id from traj_text where st_TWithin(traj, ST_ToBox('2008-02-02 13:30:44'::timestamp,'2008-02-03 17:30:44'::timestamp));
    
    --时空查询时,加速时空过滤。
    select id, traj_id from traj_test where st_3dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'),'2008-02-02 13:30:44'::timestamp,'2008-02-03 17:30:44'::timestamp);
  • 创建特定维度轨迹索引
    --当我们只需要对轨迹进行特定维度分析时,可以只建立特定维度的索引。如我们不关心轨迹的z维时,可以使用trajgist_op_2dt建立二维+时间索引。
    create index tr_timespan_time_index on trajtab using trajgist (traj trajgist_op_2dt);
    
    --建立特定维度索引后对2维+时间查询效果会更快。
    select id, traj_id from traj_test where st_2dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'),'2008-02-02 13:30:44'::timestamp,'2008-02-03 17:30:44'::timestamp);
    
    --可以同时有多个索引存在,建立任意一个即可支持所有查询,当有多个时将自动选择最优的索引。
    create index tr_timespan_time_index on trajtab using trajgist (traj trajgist_op_2d);
    select id, traj_id from traj_test where st_2dintersects(traj, ST_GeomFromText('POLYGON((116.46747851805917 39.92317964155052,116.4986540687358 39.92317964155052,116.4986540687358 39.94452401711516,116.46747851805917 39.94452401711516,116.46747851805917 39.92317964155052))'));
  • 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