FEAT : hypertable et select dessus

docker-compose.yml

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+services:
+  timescaledb:
+    image: timescale/timescaledb-ha:pg18
+    ports:
+      - 5432:5432
+    environment:
+      - POSTGRES_PASSWORD=postgres

notes.md

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+# timescaledb
+
+<https://github.com/timescale/timescaledb>
+
+## Test
+
+### Récup datas
+
+```bash
+ssh grab-4
+docker exec -t client-demo-postgres-1 pg_dump -Fc -U postgres -d postgres -f /tmp/backup_postgres.dump
+docker cp client-demo-postgres-1:/tmp/backup_postgres.dump /tmp/backup_postgres.dump
+exit
+
+cd /tmp
+scp grab-4:/tmp/backup_postgres.dump .
+pg_restore -c -x -t mesure -d postgres -h localhost -U postgres -W  backup_postgres.dump
+pg_restore -c -x -I mesure_idx1 -d postgres -h localhost -U postgres -W  backup_postgres.dump
+pg_restore -c -x -I mesure_idx2 -d postgres -h localhost -U postgres -W  backup_postgres.dump
+```
+
+### Création d'une hypertable
+
+```sql
+CREATE TABLE mesure_ng (
+  "date" TIMESTAMPTZ,
+  id_captation INT NOT NULL,
+  valeur float4 NOT NULL,
+) WITH (
+  tsdb.hypertable,
+  timescaledb.segmentby = 'id_captation',
+  timescaledb.orderby='time DESC'
+)
+
+INSERT INTO mesure_ng ("date", id_captation, valeur)
+  SELECT "date", id_captation, valeur
+    FROM mesure
+```
+
+### Ex. de requête
+
+```sql
+SELECT
+  time_bucket('1 hour', "date") AS heure,
+  round(
+    average(
+      time_weight('linear', "date", valeur)
+    )
+  ) AS moyenne_conso,
+  COUNT(*) AS nombre_de_mesures
+FROM
+  mesure_ng
+WHERE
+  "date" BETWEEN '2026-03-01 00:00:00' AND '2026-03-31 23:59:59'
+  and id_captation = 59 -- puissance PAC
+GROUP BY
+  heure
+ORDER BY
+  heure;
+```
+
+### Continuous aggregates (WIP)
+
+<https://www.tigerdata.com/docs/use-timescale/latest/continuous-aggregates/create-a-continuous-aggregate>
+
+* CREATE MATERIALIZED VIEW
+* SELECT add_continuous_aggregate_policy
+* supprimer les "vieilles" données de mesure_ng