Postgres/TimescaleDB: Difference between revisions
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topic_id INTEGER NOT NULL REFERENCES topic(id), | topic_id INTEGER NOT NULL REFERENCES topic(id), | ||
value DOUBLE PRECISION NULL, | value DOUBLE PRECISION NULL, | ||
UNIQUE(timestamp, topic_id) | |||
); | |||
CREATE TABLE IF NOT EXISTS process_value_text ( | |||
timestamp TIMESTAMPTZ NOT NULL, | |||
topic_id INTEGER NOT NULL REFERENCES topic(id), | |||
value TEXT NULL, | |||
UNIQUE(timestamp, topic_id) | UNIQUE(timestamp, topic_id) | ||
); | ); | ||
Revision as of 13:18, 5 January 2025
Setup Timescale for Unified Namespace data logging
- connect
psql -d "postgres://user:password@localhost/postgres"
- check
\dx # list extensions \dt # list all tables
- Create database
# DROP DATABASE unifiednamespace; CREATE DATABASE unifiednamespace OWNER user; GRANT ALL PRIVILEGES ON DATABASE unifiednamespace TO user; \c unifiednamespace # switch to database
Option A: Simple table (with topic as text column
-- Create table
CREATE TABLE IF NOT EXISTS process_value_numeric (
timestamp TIMESTAMPTZ NOT NULL,
topic TEXT NOT NULL,
value DOUBLE PRECISION NULL );
-- Create hypertable
SELECT create_hypertable('process_value_numeric', 'timestamp');
-- add index
CREATE INDEX ON process_value_numeric (topic, timestamp DESC);
- View table information
\d process_value_numeric
Option B: Linked tables (with topic as id)
- create topic table
CREATE TABLE IF NOT EXISTS topic (
id SERIAL PRIMARY KEY,
topic TEXT NOT NULL,
UNIQUE(topic)
);
- create data table
CREATE TABLE IF NOT EXISTS process_value_numeric (
timestamp TIMESTAMPTZ NOT NULL,
topic_id INTEGER NOT NULL REFERENCES topic(id),
value DOUBLE PRECISION NULL,
UNIQUE(timestamp, topic_id)
);
CREATE TABLE IF NOT EXISTS process_value_text (
timestamp TIMESTAMPTZ NOT NULL,
topic_id INTEGER NOT NULL REFERENCES topic(id),
value TEXT NULL,
UNIQUE(timestamp, topic_id)
);
SELECT create_hypertable('process_value_numeric', 'timestamp');
- insert sample topics
INSERT INTO topic (topic) VALUES
('uns/v1/home/plug-fridge/sensor/energy/state'),
('uns/v1/home/plug-f3e8e6-dishwasher/sensor/energy/state'),
('uns/v1/home/modbus-meter/sensor/total_import_kwh/state'),
('uns/v1/home/modbus-meter/sensor/total_system_power_w/state');
- insert sample data
INSERT INTO process_value_numeric (timestamp, topic_id, value) VALUES (now(), '1', '132');
- insert data with topic_id lookup
-- step 1: insert topic if not exists
INSERT INTO topic (topic) VALUES
('uns/v1/home/plug-fridge/sensor/energy/state')
ON CONFLICT (topic) DO NOTHING;
-- step 2: insert data point
INSERT INTO process_value_numeric (timestamp, topic_id, value) VALUES (
NOW(),
(SELECT id FROM topic WHERE topic = 'uns/v1/home/plug-fridge/sensor/energy/state'),
2135.5
);
- create view to show process value together with topic name
CREATE VIEW process_value_with_topic_name AS SELECT pv.timestamp, t.topic, pv.value FROM "process_value_numeric" pv INNER JOIN topic t ON pv.topic_id = t.id
Insert data
- via Node-RED
INSERT INTO process_value (timestamp, topic, value) VALUES (
now(),
'{{{ msg.topic }}}',
'{{{ msg.payload }}}'
);
Get table size
SELECT hypertable_size('process_value');
Query
Grafana timefilter macro
- limits query to timeframe selected in grafana
SELECT *
FROM process_value
WHERE (topic = 'home/modbus-meter/sensor/total_system_power_w/state'
AND $__timeFilter("time"))
Time buckets
- https://docs.timescale.com/use-timescale/latest/time-buckets/about-time-buckets/
- https://docs.timescale.com/use-timescale/latest/time-buckets/use-time-buckets/
- 15min average time_buckets
SELECT time_bucket('1 hour', timestamp) as time,
avg(value) AS avg_value
FROM sensor_data
WHERE
topic = 'home/modbus-meter/sensor/total_system_power_w/state'
AND
$__timeFilter("timestamp")
GROUP by time
Meter / increasing counter
- https://github.com/timescale/timescaledb-toolkit/blob/main/docs/counter_agg.md
- https://stackoverflow.com/questions/76774353/get-complete-hours-time-buckets-with-timescaledb
- https://docs.timescale.com/use-timescale/latest/query-data/advanced-analytic-queries/#calculate-the-increase-in-a-value
SELECT time_bucket('1 hour', time) as bucket,
first(time,time) as period_begin,
last(time,time) as period_end,
MAX(counter) - MIN(counter) as total_consumption
FROM
GROUP BY 1;
first() + last ()
Grafana > Dashboards > Settings > Variables
- topic = SELECT DISTINCT topic FROM "sensor_data"