Overview
Trajectory data records the continuous location update information about a moving feature, such as a vehicle or a person. Trajectory data is a type of typical spatio-temporal data. You can use trajectory data for in-depth analysis.
GanosBase Trajectory is an extension of AnalyticDB for PostgreSQL. GanosBase Trajectory provides a series of data types, functions, and stored procedures. This allows you to manage, query, and analyze spatio-temporal trajectory data.
Quick start
Create extensions.
Create extension ganos_spatialref; Create extension ganos_geometry; Create Extension Ganos_trajectory;Create an enumeration type for a trajectory.
CREATE TYPE leaftype AS ENUM ('STPOINT', 'STPOLYGON');Create a trajectory table.
Create Table traj_table (id integer, traj trajectory) DISTRIBUTED BY (id);Insert trajectory data into the trajectory table.
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));Create a trajectory index on the trajectory table.
-- Create a trajectory index to accelerate filtering of spatio-temporal data. create index tr_index on traj_table using gist (traj); -- Use the trajectory index to accelerate filtering of spatial data in a query on spatial data. 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))')); -- Use the trajectory index to accelerate filtering of temporal data in a query on temporal data. select id, traj_id from traj_text where st_TContains(traj,'2008-02-02 13:30:44'::timestamp,'2008-02-03 17:30:44'::timestamp); -- Use the trajectory index to accelerate filtering of spatio-temporal data in a query on spatio-temporal data. 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);Create trajectory indexes in specific dimensions on the trajectory table.
-- If you want to analyze trajectory data only from a specific dimension, create a trajectory index in that dimension. For example, if you do not want to analyze trajectory data in the z dimension, create a two-dimensional temporal trajectory index by using trajgist_op_2dt. create index tr_timespan_time_index on traj_table using gist (traj trajgist_op_2dt); -- Perform a query on two-dimensional spatio-temporal data. The query is accelerated. 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); -- Create more trajectory indexes based on your business requirements. If you create multiple trajectory indexes, AnalyticDB for PostgreSQL selects the optimal trajectory index when you perform queries. create index tr_timespan_time_index on trajtab using gist (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))'));Query the start time and end time of trajectories.
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)Query information about the trajectories.
-- Use an interpolation function to query the attributes of trajectory points. Select ST_velocityAtTime(traj, '2010-01-01 12:45') from traj_table where id > 5; st_velocityattime ------------------- 5 5 4.16666666666667 (3 rows)Analyze the proximity among trajectories.
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)Delete extensions.
DROP Extension Ganos_Raster; DROP extension ganos_geometry; Drop Extension Ganos_trajectory;
SQL reference
For more information, see Basic concepts.