Getting last rows by date on a large postgresl data base - django

Question

I have a large database ( there are 6000 rows inserted per minute ) on a partitioned table, I was working cool when the database was small, now I have a large database. I was using this solution a previous solutions SQL joined by date but it is using 250MB of hard disk and grows up while my table grows, then I decide on change it to an iteration of simple queries, that works well for 10 rows, but get slow with more than 10 cars ( 15 secods for response ) and uses more than 200MB of hard disk.
My question is how to build a good query faster for resolve this issue
Extra info
Query is called on a django app by ajax
I was thinking on iterative ajax calls instead one call with full items list response
Tables are partitioned by day
My actual query is
CREATE OR REPLACE FUNCTION gps_get_last_positions (
_plates varchar(8)
)
RETURNS TABLE (
plate varchar,
device_id integer,
date_time_process timestamp with time zone,
latitude double precision,
longitude double precision,
course smallint,
speed smallint,
mileage integer,
gps_signal smallint,
gsm_signal smallint,
alarm_status boolean,
gsm_status boolean,
vehicle_status boolean,
alarm_over_speed boolean,
other text,
realtime double precision
) AS $func$
DECLARE
arr varchar[];
BEGIN
arr := regexp_split_to_array(_plates, E'\\s+');
FOR i IN 1..array_length(arr, 1) LOOP
RETURN QUERY SELECT
gpstracking_vehicles.registration,
gpstracking_device_tracks.device_id,
gpstracking_device_tracks.date_time_process,
gpstracking_device_tracks.latitude,
gpstracking_device_tracks.longitude,
gpstracking_device_tracks.course,
gpstracking_device_tracks.speed,
gpstracking_device_tracks.mileage,
gpstracking_device_tracks.gps_signal,
gpstracking_device_tracks.gsm_signal,
gpstracking_device_tracks.alarm_status,
gpstracking_device_tracks.gps_status,
gpstracking_device_tracks.vehicle_status,
gpstracking_device_tracks.alarm_over_speed,
gpstracking_device_tracks.other,
EXTRACT(EPOCH FROM current_timestamp - gpstracking_device_tracks.date_time_process)/60 AS realtime
FROM (
gpstracking_devices INNER JOIN (
gpstracking_vehicles INNER JOIN gpstracking_vehicles_devices ON ( gpstracking_vehicles.id = gpstracking_vehicles_devices.vehicle_id AND gpstracking_vehicles_devices.is_joined = TRUE )
) ON ( gpstracking_devices.id = gpstracking_vehicles_devices.device_id AND gpstracking_vehicles_devices.is_joined = TRUE )
) INNER JOIN gpstracking_device_tracks ON ( gpstracking_devices.id = gpstracking_device_tracks.device_id )
WHERE gpstracking_vehicles.registration = arr[i]::VARCHAR
ORDER BY gpstracking_device_tracks.date_time_process DESC
LIMIT 1;
END LOOP;
RETURN;
END;
$func$
LANGUAGE plpgsql VOLATILE SECURITY DEFINER;
Configuration params
application_name phpPgAdmin_5.0.4 client
constraint_exclusion on configuration file
DateStyle ISO, MDY session
default_text_search_config pg_catalog.english configuration file
external_pid_file /var/run/postgresql/9.1-main.pid configuration file
lc_messages en_US.UTF-8 configuration file
lc_monetary en_US.UTF-8 configuration file
lc_numeric en_US.UTF-8 configuration file
lc_time en_US.UTF-8 configuration file
log_line_prefix %t configuration file
log_timezone localtime environment variable
max_connections 100 configuration file
max_stack_depth 2MB environment variable
port 5432 configuration file
shared_buffers 24MB configuration file
ssl on configuration file
TimeZone localtime environment variable
unix_socket_directory /var/run/postgresql configuration file
My first slow query was:
CREATE OR REPLACE VIEW view_vehicle_devices AS
SELECT
gpstracking_vehicles_devices.id AS id,
gpstracking_devices.id AS device_id,
gpstracking_vehicles.id AS vehicle_id,
gpstracking_drivers.id AS driver_id,
gpstracking_device_protocols.name AS protocol,
gpstracking_vehicles.registration AS plate,
gpstracking_drivers.firstname as first_name,
gpstracking_drivers.lastname as last_name,
gpstracking_devices.imei,
gpstracking_devices.simcard,
gpstracking_device_tracks.date_time_process,
gpstracking_device_tracks.latitude,
gpstracking_device_tracks.longitude,
gpstracking_device_tracks.course,
gpstracking_device_tracks.speed,
gpstracking_device_tracks.mileage,
gpstracking_device_tracks.gps_signal,
gpstracking_device_tracks.gsm_signal,
gpstracking_device_tracks.alarm_status,
gpstracking_device_tracks.gps_status,
gpstracking_device_tracks.vehicle_status,
gpstracking_device_tracks.alarm_over_speed,
gpstracking_device_tracks.other,
gpstracking_device_tracks.point,
EXTRACT(EPOCH FROM current_timestamp - gpstracking_device_tracks.date_time_process)/60 realtime,
gpstracking_devices.created,
gpstracking_devices.updated,
gpstracking_devices.is_connected
FROM (
gpstracking_vehicles LEFT JOIN (
gpstracking_drivers LEFT JOIN gpstracking_vehicles_drivers ON gpstracking_drivers.id = gpstracking_vehicles_drivers.driver_id AND gpstracking_vehicles_drivers.is_joined = TRUE
) ON gpstracking_vehicles.id = gpstracking_vehicles_drivers.vehicle_id AND gpstracking_vehicles_drivers.is_joined = TRUE
) LEFT JOIN (((
gpstracking_device_protocols RIGHT JOIN gpstracking_devices ON gpstracking_device_protocols.id = gpstracking_devices.device_protocol_id
) LEFT JOIN (
SELECT DISTINCT ON (gpstracking_device_tracks.device_id) gpstracking_device_tracks.device_id,
gpstracking_device_tracks.date_time_process,
gpstracking_device_tracks.latitude,
gpstracking_device_tracks.longitude,
gpstracking_device_tracks.course,
gpstracking_device_tracks.speed,
gpstracking_device_tracks.mileage,
gpstracking_device_tracks.gps_signal,
gpstracking_device_tracks.gsm_signal,
gpstracking_device_tracks.alarm_status,
gpstracking_device_tracks.gps_status,
gpstracking_device_tracks.vehicle_status,
gpstracking_device_tracks.alarm_over_speed,
gpstracking_device_tracks.other,
gpstracking_device_tracks.point
FROM gpstracking_device_tracks
ORDER BY gpstracking_device_tracks.device_id, gpstracking_device_tracks.date_time_process DESC
) AS gpstracking_device_tracks ON gpstracking_devices.id = gpstracking_device_tracks.device_id
) LEFT JOIN gpstracking_vehicles_devices ON ( gpstracking_devices.id = gpstracking_vehicles_devices.device_id AND gpstracking_vehicles_devices.is_joined = TRUE )
) ON ( gpstracking_vehicles.id = gpstracking_vehicles_devices.vehicle_id AND gpstracking_vehicles_devices.is_joined = TRUE )
I have changed it for the loop that is starting my post, my loop rujns faster, however is not enought faster as I need

Answer 1

Your problem is that a planner can not know in which partition is an answer to your query. It only has statistics. So you do not benefit from partitioning your data by a day at all.
To benefit from it you can modify your query so it'll look for latest coordinates from current day, if not found then from yesterday, if not found from a day before an so on. I suppose 99% answers would be found in todays partition only.
Or you can partition by for example device_id % 256 instead.
But even better would be to create an additional table with several recent device coordinates only. It would be maintained with a trigger on gpstracking_device_tracks which will just do (pseudocode):
if random()*64 < 1.0 then
-- statistically once per 64 runs do a cleanup
with todelete as (
-- lock rows in particular order to avoid possible deadlocks
-- if run concurrently
select id from gpstracking_device_tracks_recent where device_id=?
order by id for share;
)
delete from gpstracking_device_tracks_recent
where id in (select id from todelete)
end if;
insert into gpstracking_device_tracks_recent (...) values (...);
And then look for latest coordinates in this much smaller table.