How to calculate power consumption from power records? - sql

Question

I have table which contains power values (kW) for devices. Values are read from each device once a minute and inserted into table with timestamp. What I need to do is calculate power consumption (kWh) for given time span and return 10 most power consuming devices. Right now I query results for given time span and do calculation in backend looping all records. This works fine with small amount of devices and with short time span, but in real use case I could have thousands of devices and long time span.
So my question is how could I do this all in PostgreSQL 9.4.4 so that my query would return only 10 most power consuming (device_id, power_consumption) pairs?
Example table:
CREATE TABLE measurements (
id serial primary key,
device_id integer,
power real,
created_at timestamp
);
Simple data example:
| id | device_id | power | created_at |
|----|-----------|-------|--------------------------|
| 1 | 1 | 10 | August, 26 2015 08:23:25 |
| 2 | 1 | 13 | August, 26 2015 08:24:25 |
| 3 | 1 | 12 | August, 26 2015 08:25:25 |
| 4 | 2 | 103 | August, 26 2015 08:23:25 |
| 5 | 2 | 134 | August, 26 2015 08:24:25 |
| 6 | 2 | 2 | August, 26 2015 08:25:25 |
| 7 | 3 | 10 | August, 26 2015 08:23:25 |
| 8 | 3 | 13 | August, 26 2015 08:24:25 |
| 9 | 3 | 20 | August, 26 2015 08:25:25 |
Wanted results for query:
| id | device_id | power_consumption |
|----|-----------|-------------------|
| 1 | 1 | 24.0 |
| 2 | 2 | 186.5 |
| 3 | 3 | 28.0 |
Simplified example (created_at in hours) how I calculate kWh value:
data = [
[
{ 'id': 1, 'device_id': 1, 'power': 10.0, 'created_at': 0 },
{ 'id': 2, 'device_id': 1, 'power': 13.0, 'created_at': 1 },
{ 'id': 3, 'device_id': 1, 'power': 12.0, 'created_at': 2 }
],
[
{ 'id': 4, 'device_id': 2, 'power': 103.0, 'created_at': 0 },
{ 'id': 5, 'device_id': 2, 'power': 134.0, 'created_at': 1 },
{ 'id': 6, 'device_id': 2, 'power': 2.0, 'created_at': 2 }
],
[
{ 'id': 7, 'device_id': 3, 'power': 10.0, 'created_at': 0 },
{ 'id': 8, 'device_id': 3, 'power': 13.0, 'created_at': 1 },
{ 'id': 9, 'device_id': 3, 'power': 20.0, 'created_at': 2 }
]
]
# device_id: power_consumption
results = { 1: 0, 2: 0, 3: 0 }
for d in data:
for i in range(0, len(d)):
if i < len(d)-1:
# Area between two records gives us kWh
# X-axis is time(h)
# Y-axis is power(kW)
x1 = d[i]['created_at']
x2 = d[i+1]['created_at']
y1 = d[i]['power']
y2 = d[i+1]['power']
# Area between two records gives us kWh
# X-axis is time(h)
# Y-axis is power(kW)
x1 = d[i]['created_at']
x2 = d[i+1]['created_at']
y1 = d[i]['power']
y2 = d[i+1]['power']
results[d[i]['device_id']] += ((x2-x1)*(y2+y1))/2
print results
EDIT: Check this to see how I ended up solving this.

Answer 1

Some of the elements that you'll need in order to do this are:
Sum() aggregations, to calculate the total of a number of records
Lag()/Lead() functions, to calculate for a given record what the "previous" or "next" record's values were.
So where for a given row you can get the current created_at and power records, in SQL you'd probably use a Lead() windowing function to get the created_at and power records for the record for the same device id that has the next highest value for created_at.
Docs for Lead() are here: http://www.postgresql.org/docs/9.4/static/functions-window.html
When for each row you have calculated the power consumption by reference to the "next" record, you can use a Sum() to aggregate up all of the calculated powers for that one device.
When you have calculated the power per device, you can use ORDER BY and LIMIT to select the top n power-consuming devices.
Steps to follow, if you're not confident to plunge in and just write the final SQL -- after each step make sure you haveSQL you understand, and which returns just the data you need:
Start small, by selecting the data rows that you want.
Work out the Lead() function, defining the appropriate partition and order clauses to get the next row.
Add the calculation of power per row.
Define the Sum() function, and group by the device id.
Add the ORDER BY and LIMIT clauses.
If you have trouble with any one of these steps, they would each make a decent StackOverflow question.

Answer 2

If someone happens to wonder same thing here is how I solved this.
I followed instructions by David and made this:
SELECT
t.device_id,
sum(len_y*(extract(epoch from date_trunc('milliseconds', len_x)))/7200) AS total
FROM (
SELECT
m.id,
m.device_id,
m.power,
m.created_at,
m.power+lag(m.power) OVER (
PARTITION BY device_id
ORDER BY m.created_at
) AS len_y,
m.created_at-lag(m.created_at) OVER (
PARTITION BY device_id
ORDER BY m.created_at
) AS len_x
FROM
mes AS m
WHERE m.created_at BETWEEN '2015-08-26 13:39:57.834674'::timestamp
AND '2015-08-26 13:43:57.834674'::timestamp
) AS t
GROUP BY t.device_id
ORDER BY total
DESC LIMIT 10;