Linux/TimescaleDB: Difference between revisions

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== 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
<blockquote>
<pre>
SELECT time_bucket('15 minute', time) as fifteen_min,
  avg(value) AS avg_value
FROM "sensor_data"
WHERE "topic" = 'home/plug-c86044-fridge/sensor/power'
GROUP by fifteen_min
ORDER by fifteen_min DESC
LIMIT 50
</pre>
</blockquote>
== Counters ==
* https://github.com/timescale/timescaledb-toolkit/blob/main/docs/counter_agg.md
* https://stackoverflow.com/questions/76774353/get-complete-hours-time-buckets-with-timescaledb :
<blockquote>
<pre>
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;
</pre>
</blockquote>
== first() + last () ==
*
== Continuous aggregates ==
* https://docs.timescale.com/tutorials/latest/energy-data/dataset-energy/
== Links ==
* https://docs.timescale.com/
* https://www.timescale.com/learn/time-series-basics
* https://www.timescale.com/learn/timescale-basics


[[Category:Linux/Services]]
[[Category:Linux/Services]]
[[Category:Linux]]
[[Category:Linux]]
[[Category:Programming]]
[[Category:Programming]]

Latest revision as of 13:36, 13 October 2024

Setup

CREATE TABLE sensor_data (
        time TIMESTAMPTZ NOT NULL,
        topic TEXT,
        value DOUBLE PRECISION
);
SELECT create_hypertable('sensor_data', 'time');

Insert data via Node-RED

INSERT INTO sensor_data (time, topic, value) VALUES (
    now(),
    '{{{ msg.topic }}}',
    '{{{ msg.payload }}}'
);

Get table size

SELECT hypertable_size('sensor_data');

Time buckets

SELECT time_bucket('15 minute', time) as fifteen_min,
  avg(value) AS avg_value
FROM "sensor_data"
WHERE "topic" = 'home/plug-c86044-fridge/sensor/power'
GROUP by fifteen_min
ORDER by fifteen_min DESC
LIMIT 50

Counters

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 ()

Continuous aggregates

Links