model adjustments

libs/common/src/sql/procedures/fact_daily_space_occupancy_duration/procedure_insert_all_daily_spacy_occupancy_duration.sql

@@ -1,100 +1,93 @@
--- Step 1: Get device presence events with previous timestamps
-WITH start_date AS (
-    SELECT 
-        d.uuid AS device_id,
-        d.space_device_uuid AS space_id,
-        l.value,
-        l.event_time::timestamp AS event_time,
-        LAG(l.event_time::timestamp) OVER (PARTITION BY d.uuid ORDER BY l.event_time) AS prev_timestamp
-    FROM device d
-    LEFT JOIN "device-status-log" l
-        ON d.uuid = l.device_id
-    LEFT JOIN product p
-        ON p.uuid = d.product_device_uuid
-    WHERE p.cat_name = 'hps'
-      AND l.code = 'presence_state'
+WITH presence_logs AS (
+  SELECT 
+    d.space_device_uuid AS space_id,
+    l.device_id,
+    l.event_time,
+    l.value,
+    LAG(l.event_time) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_time
+  FROM device d
+  JOIN "device-status-log" l ON d.uuid = l.device_id
+  JOIN product p ON p.uuid = d.product_device_uuid
+  WHERE l.code = 'presence_state'
+    AND p.cat_name = 'hps'
 ),
 
--- Step 2: Identify periods when device reports "none"
-device_none_periods AS ( 
-    SELECT 
-        space_id,
-        device_id,
-        event_time AS empty_from,
-        LEAD(event_time) OVER (PARTITION BY device_id ORDER BY event_time) AS empty_until
-    FROM start_date
-    WHERE value = 'none'
+-- Intervals when device was in 'presence' (between prev_time and event_time when value='none')
+presence_intervals AS (
+  SELECT 
+    space_id,
+    prev_time AS start_time,
+    event_time AS end_time
+  FROM presence_logs
+  WHERE value = 'none' 
+    AND prev_value = 'presence'
+    AND prev_time IS NOT NULL
 ),
 
--- Step 3: Clip the "none" periods to the edges of each day
-clipped_device_none_periods AS (
-    SELECT 
-        space_id,
-        GREATEST(empty_from, DATE_TRUNC('day', empty_from)) AS clipped_from,
-        LEAST(empty_until, DATE_TRUNC('day', empty_until) + INTERVAL '1 day') AS clipped_until
-    FROM device_none_periods
-    WHERE empty_until IS NOT NULL
+-- Split intervals across days
+split_intervals AS (
+  SELECT 
+    space_id,
+    generate_series(
+      date_trunc('day', start_time),
+      date_trunc('day', end_time),
+      interval '1 day'
+    )::date AS event_date,
+    GREATEST(start_time, date_trunc('day', start_time)) AS interval_start,
+    LEAST(end_time, date_trunc('day', end_time) + interval '1 day') AS interval_end
+  FROM presence_intervals
 ),
 
--- Step 4: Break multi-day periods into daily intervals
-generated_daily_intervals AS (
-    SELECT 
-        space_id,
-        gs::date AS day,
-        GREATEST(clipped_from, gs) AS interval_start,
-        LEAST(clipped_until, gs + INTERVAL '1 day') AS interval_end
-    FROM clipped_device_none_periods,
-    LATERAL generate_series(DATE_TRUNC('day', clipped_from), DATE_TRUNC('day', clipped_until), INTERVAL '1 day') AS gs
+-- Mark and group overlapping intervals per space per day
+ordered_intervals AS (
+  SELECT 
+    space_id,
+    event_date,
+    interval_start,
+    interval_end,
+    LAG(interval_end) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS prev_end
+  FROM split_intervals
 ),
 
--- Step 5: Merge overlapping or adjacent intervals per day
+grouped_intervals AS (
+  SELECT *,
+    SUM(CASE 
+          WHEN prev_end IS NULL OR interval_start > prev_end THEN 1 
+          ELSE 0 
+        END) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS grp
+  FROM ordered_intervals
+),
+
+-- Merge overlapping intervals per group
 merged_intervals AS (
-    SELECT 
-        space_id,
-        day,
-        interval_start,
-        interval_end
-    FROM (
-        SELECT 
-            space_id,
-            day,
-            interval_start,
-            interval_end,
-            LAG(interval_end) OVER (PARTITION BY space_id, day ORDER BY interval_start) AS prev_end
-        FROM generated_daily_intervals
-    ) sub
-    WHERE prev_end IS NULL OR interval_start > prev_end
+  SELECT 
+    space_id,
+    event_date,
+    MIN(interval_start) AS merged_start,
+    MAX(interval_end) AS merged_end
+  FROM grouped_intervals
+  GROUP BY space_id, event_date, grp
 ),
 
--- Step 6: Sum up total missing seconds (device reported "none") per day
-missing_seconds_per_day AS (
-    SELECT 
-        space_id,
-        day AS missing_date,
-        SUM(EXTRACT(EPOCH FROM (interval_end - interval_start))) AS total_missing_seconds
-    FROM merged_intervals
-    GROUP BY space_id, day
-),
+-- Sum durations of merged intervals
+summed_intervals AS (
+  SELECT
+    space_id,
+    event_date,
+    SUM(EXTRACT(EPOCH FROM (merged_end - merged_start))) AS raw_occupied_seconds
+  FROM merged_intervals
+  GROUP BY space_id, event_date
+  ),
 
--- Step 7: Calculate total occupied time per day (86400 - missing)
-occupied_seconds_per_day AS (
-    SELECT 
-        space_id,
-        missing_date as event_date,
-        86400 - total_missing_seconds AS total_occupied_seconds,
-        (86400 - total_missing_seconds)/86400*100 as occupancy_prct
-    FROM missing_seconds_per_day
-)
+final_data AS (
+SELECT 
+  space_id,
+  event_date,
+  LEAST(raw_occupied_seconds, 86400) AS occupied_seconds,
+  ROUND(LEAST(raw_occupied_seconds, 86400) / 86400.0 * 100, 2) AS occupancy_percentage
+FROM summed_intervals
+ORDER BY space_id, event_date)
 
--- Final Output
-, final_data as (
-SELECT space_id,
-        event_date,
-        total_occupied_seconds,
-        occupancy_prct
-FROM occupied_seconds_per_day 
-ORDER BY 1,2
-)
 
 INSERT INTO public."space-daily-occupancy-duration" (
 	space_uuid,	
@@ -104,12 +97,13 @@ INSERT INTO public."space-daily-occupancy-duration" (
 )
 select space_id,
        event_date,
-       total_occupied_seconds,
-       occupancy_prct
+       occupied_seconds,
+       occupancy_percentage
 FROM final_data
 ON CONFLICT (space_uuid, event_date) DO UPDATE
 SET
-    occupancy_percentage = EXCLUDED.occupancy_percentage;
+    occupancy_percentage = EXCLUDED.occupancy_percentage, 
+   	occupied_seconds = EXCLUDED.occupied_seconds;
     
    
    

libs/common/src/sql/procedures/fact_daily_space_occupancy_duration/procedure_update_daily_space_occupancy_duration.sql

@@ -2,116 +2,108 @@ WITH params AS (
 	SELECT 
       TO_DATE(NULLIF($1, ''), 'YYYY-MM-DD') AS event_date,
       $2::uuid AS space_id
-)
-
-, start_date AS (
-    SELECT 
-        d.uuid AS device_id,
-        d.space_device_uuid AS space_id,
-        l.value,
-        l.event_time::timestamp AS event_time,
-        LAG(l.event_time::timestamp) OVER (PARTITION BY d.uuid ORDER BY l.event_time) AS prev_timestamp
-    FROM device d
-    LEFT JOIN "device-status-log" l
-        ON d.uuid = l.device_id
-    LEFT JOIN product p
-        ON p.uuid = d.product_device_uuid
-    WHERE p.cat_name = 'hps'
-      AND l.code = 'presence_state'
 ),
 
--- Step 2: Identify periods when device reports "none"
-device_none_periods AS ( 
-    SELECT 
-        space_id,
-        device_id,
-        event_time AS empty_from,
-        LEAD(event_time) OVER (PARTITION BY device_id ORDER BY event_time) AS empty_until
-    FROM start_date
-    WHERE value = 'none'
+presence_logs AS (
+  SELECT 
+    d.space_device_uuid AS space_id,
+    l.device_id,
+    l.event_time,
+    l.value,
+    LAG(l.event_time) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_time
+  FROM device d
+  JOIN "device-status-log" l ON d.uuid = l.device_id
+  JOIN product p ON p.uuid = d.product_device_uuid
+  WHERE l.code = 'presence_state'
+    AND p.cat_name = 'hps'
 ),
 
--- Step 3: Clip the "none" periods to the edges of each day
-clipped_device_none_periods AS (
-    SELECT 
-        space_id,
-        GREATEST(empty_from, DATE_TRUNC('day', empty_from)) AS clipped_from,
-        LEAST(empty_until, DATE_TRUNC('day', empty_until) + INTERVAL '1 day') AS clipped_until
-    FROM device_none_periods
-    WHERE empty_until IS NOT NULL
+presence_intervals AS (
+  SELECT 
+    space_id,
+    prev_time AS start_time,
+    event_time AS end_time
+  FROM presence_logs
+  WHERE value = 'none' AND prev_time IS NOT NULL
 ),
 
--- Step 4: Break multi-day periods into daily intervals
-generated_daily_intervals AS (
-    SELECT 
-        space_id,
-        gs::date AS day,
-        GREATEST(clipped_from, gs) AS interval_start,
-        LEAST(clipped_until, gs + INTERVAL '1 day') AS interval_end
-    FROM clipped_device_none_periods,
-    LATERAL generate_series(DATE_TRUNC('day', clipped_from), DATE_TRUNC('day', clipped_until), INTERVAL '1 day') AS gs
+split_intervals AS (
+  SELECT 
+    space_id,
+    generate_series(
+      date_trunc('day', start_time),
+      date_trunc('day', end_time),
+      interval '1 day'
+    )::date AS event_date,
+    GREATEST(start_time, date_trunc('day', start_time)) AS interval_start,
+    LEAST(end_time, date_trunc('day', end_time) + INTERVAL '1 day') AS interval_end
+  FROM presence_intervals
+),
+
+ordered_intervals AS (
+  SELECT 
+    space_id,
+    event_date,
+    interval_start,
+    interval_end,
+    LAG(interval_end) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS prev_end
+  FROM split_intervals
+),
+
+grouped_intervals AS (
+  SELECT *,
+    SUM(CASE 
+          WHEN prev_end IS NULL OR interval_start > prev_end THEN 1 
+          ELSE 0 
+        END) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS grp
+  FROM ordered_intervals
 ),
 
--- Step 5: Merge overlapping or adjacent intervals per day
 merged_intervals AS (
-    SELECT 
-        space_id,
-        day,
-        interval_start,
-        interval_end
-    FROM (
-        SELECT 
-            space_id,
-            day,
-            interval_start,
-            interval_end,
-            LAG(interval_end) OVER (PARTITION BY space_id, day ORDER BY interval_start) AS prev_end
-        FROM generated_daily_intervals
-    ) sub
-    WHERE prev_end IS NULL OR interval_start > prev_end
+  SELECT 
+    space_id,
+    event_date,
+    MIN(interval_start) AS merged_start,
+    MAX(interval_end) AS merged_end
+  FROM grouped_intervals
+  GROUP BY space_id, event_date, grp
 ),
 
--- Step 6: Sum up total missing seconds (device reported "none") per day
-missing_seconds_per_day AS (
-    SELECT 
-        space_id,
-        day AS missing_date,
-        SUM(EXTRACT(EPOCH FROM (interval_end - interval_start))) AS total_missing_seconds
-    FROM merged_intervals
-    GROUP BY space_id, day
+summed_intervals AS (
+  SELECT
+    space_id,
+    event_date,
+    SUM(EXTRACT(EPOCH FROM (merged_end - merged_start))) AS raw_occupied_seconds
+  FROM merged_intervals
+  GROUP BY space_id, event_date
 ),
 
--- Step 7: Calculate total occupied time per day (86400 - missing)
-occupied_seconds_per_day AS (
-    SELECT 
-        space_id,
-        missing_date as event_date,
-        86400 - total_missing_seconds AS total_occupied_seconds,
-        (86400 - total_missing_seconds)/86400*100 as occupancy_percentage
-    FROM missing_seconds_per_day
-)
-
--- Final Output
-, final_data as (
-SELECT occupied_seconds_per_day.space_id,
-        occupied_seconds_per_day.event_date,
-        occupied_seconds_per_day.occupancy_percentage
-FROM occupied_seconds_per_day 
-join params p on true 
-	and p.space_id = occupied_seconds_per_day.space_id
-	and p.event_date = occupied_seconds_per_day.event_date
-ORDER BY 1,2
+final_data AS (
+  SELECT 
+    s.space_id,
+    s.event_date,
+    LEAST(raw_occupied_seconds, 86400) AS occupied_seconds,
+    ROUND(LEAST(raw_occupied_seconds, 86400) / 86400.0 * 100, 2) AS occupancy_percentage
+  FROM summed_intervals s
+  JOIN params p 
+    ON p.space_id = s.space_id 
+   AND p.event_date = s.event_date
 )
 
 INSERT INTO public."space-daily-occupancy-duration" (
 	space_uuid,	
 	event_date,
+	occupied_seconds,
 	occupancy_percentage
 )
-select space_id,
-       event_date,
-       occupancy_percentage
+SELECT 
+    space_id,
+    event_date,
+    occupied_seconds,
+    occupancy_percentage
 FROM final_data
 ON CONFLICT (space_uuid, event_date) DO UPDATE
 SET
-    occupancy_percentage = EXCLUDED.occupancy_percentage;
+   occupancy_percentage = EXCLUDED.occupancy_percentage,
+   occupied_seconds = EXCLUDED.occupied_seconds;
+

libs/common/src/sql/procedures/fact_device_occupancy_count/procedure_select_fact_daily_device_occupancy.sql

@@ -16,4 +16,5 @@ WITH params AS (
 	WHERE A.device_uuid::text = ANY(P.device_ids)
 	  AND (P.month IS NULL 
 	    OR date_trunc('month', A.event_date) = P.month
-	  )
+	  );
+	  

libs/common/src/sql/queries/fact_daily_space_presence_duration/fact_daily_space_presence_duration.sql

@@ -1,91 +1,92 @@
--- Step 1: Get device presence events with previous timestamps
-WITH start_date AS (
-    SELECT 
-        d.uuid AS device_id,
-        d.space_device_uuid AS space_id,
-        l.value,
-        l.event_time::timestamp AS event_time,
-        LAG(l.event_time::timestamp) OVER (PARTITION BY d.uuid ORDER BY l.event_time) AS prev_timestamp
-    FROM device d
-    LEFT JOIN "device-status-log" l
-        ON d.uuid = l.device_id
-    LEFT JOIN product p
-        ON p.uuid = d.product_device_uuid
-    WHERE p.cat_name = 'hps'
-      AND l.code = 'presence_state'
+WITH presence_logs AS (
+  SELECT 
+    d.space_device_uuid AS space_id,
+    l.device_id,
+    l.event_time,
+    l.value,
+    LAG(l.event_time) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_time
+  FROM device d
+  JOIN "device-status-log" l ON d.uuid = l.device_id
+  JOIN product p ON p.uuid = d.product_device_uuid
+  WHERE l.code = 'presence_state'
+    AND p.cat_name = 'hps'
 ),
 
--- Step 2: Identify periods when device reports "none"
-device_none_periods AS ( 
-    SELECT 
-        space_id,
-        device_id,
-        event_time AS empty_from,
-        LEAD(event_time) OVER (PARTITION BY device_id ORDER BY event_time) AS empty_until
-    FROM start_date
-    WHERE value = 'none'
+-- Intervals when device was in 'presence' (between prev_time and event_time when value='none')
+presence_intervals AS (
+  SELECT 
+    space_id,
+    prev_time AS start_time,
+    event_time AS end_time
+  FROM presence_logs
+  WHERE value = 'none' 
+    AND prev_value = 'presence'
+    AND prev_time IS NOT NULL
 ),
 
--- Step 3: Clip the "none" periods to the edges of each day
-clipped_device_none_periods AS (
-    SELECT 
-        space_id,
-        GREATEST(empty_from, DATE_TRUNC('day', empty_from)) AS clipped_from,
-        LEAST(empty_until, DATE_TRUNC('day', empty_until) + INTERVAL '1 day') AS clipped_until
-    FROM device_none_periods
-    WHERE empty_until IS NOT NULL
+-- Split intervals across days
+split_intervals AS (
+  SELECT 
+    space_id,
+    generate_series(
+      date_trunc('day', start_time),
+      date_trunc('day', end_time),
+      interval '1 day'
+    )::date AS event_date,
+    GREATEST(start_time, date_trunc('day', start_time)) AS interval_start,
+    LEAST(end_time, date_trunc('day', end_time) + interval '1 day') AS interval_end
+  FROM presence_intervals
 ),
 
--- Step 4: Break multi-day periods into daily intervals
-generated_daily_intervals AS (
-    SELECT 
-        space_id,
-        gs::date AS day,
-        GREATEST(clipped_from, gs) AS interval_start,
-        LEAST(clipped_until, gs + INTERVAL '1 day') AS interval_end
-    FROM clipped_device_none_periods,
-    LATERAL generate_series(DATE_TRUNC('day', clipped_from), DATE_TRUNC('day', clipped_until), INTERVAL '1 day') AS gs
+-- Mark and group overlapping intervals per space per day
+ordered_intervals AS (
+  SELECT 
+    space_id,
+    event_date,
+    interval_start,
+    interval_end,
+    LAG(interval_end) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS prev_end
+  FROM split_intervals
 ),
 
--- Step 5: Merge overlapping or adjacent intervals per day
+grouped_intervals AS (
+  SELECT *,
+    SUM(CASE 
+          WHEN prev_end IS NULL OR interval_start > prev_end THEN 1 
+          ELSE 0 
+        END) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS grp
+  FROM ordered_intervals
+),
+
+-- Merge overlapping intervals per group
 merged_intervals AS (
-    SELECT 
-        space_id,
-        day,
-        interval_start,
-        interval_end
-    FROM (
-        SELECT 
-            space_id,
-            day,
-            interval_start,
-            interval_end,
-            LAG(interval_end) OVER (PARTITION BY space_id, day ORDER BY interval_start) AS prev_end
-        FROM generated_daily_intervals
-    ) sub
-    WHERE prev_end IS NULL OR interval_start > prev_end
+  SELECT 
+    space_id,
+    event_date,
+    MIN(interval_start) AS merged_start,
+    MAX(interval_end) AS merged_end
+  FROM grouped_intervals
+  GROUP BY space_id, event_date, grp
 ),
 
--- Step 6: Sum up total missing seconds (device reported "none") per day
-missing_seconds_per_day AS (
-    SELECT 
-        space_id,
-        day AS missing_date,
-        SUM(EXTRACT(EPOCH FROM (interval_end - interval_start))) AS total_missing_seconds
-    FROM merged_intervals
-    GROUP BY space_id, day
-),
-
--- Step 7: Calculate total occupied time per day (86400 - missing)
-occupied_seconds_per_day AS (
-    SELECT 
-        space_id,
-        missing_date as date,
-        86400 - total_missing_seconds AS total_occupied_seconds
-    FROM missing_seconds_per_day
+-- Sum durations of merged intervals
+summed_intervals AS (
+  SELECT
+    space_id,
+    event_date,
+    SUM(EXTRACT(EPOCH FROM (merged_end - merged_start))) AS raw_occupied_seconds
+  FROM merged_intervals
+  GROUP BY space_id, event_date
 )
 
--- Final Output
-SELECT * 
-FROM occupied_seconds_per_day 
-ORDER BY 1,2;
+-- Final output with capped seconds and percentage
+SELECT 
+  space_id,
+  event_date,
+  LEAST(raw_occupied_seconds, 86400) AS occupied_seconds,
+  ROUND(LEAST(raw_occupied_seconds, 86400) / 86400.0 * 100, 2) AS occupancy_percentage
+FROM summed_intervals
+ORDER BY space_id, event_date;
+
+
+