Disk usage discrepancy?

[jammerdan]

@elek

Satellite shares the bytes*hour usage for a certain period. The average period can be calculated (for that period) which dividing it with the duration of the period (diff between the previous and current end time)

That’s not in question for me. I am trying to put that together with the “advanced” query

@JWvdV

Adapted usage query on the sqlite-database:

root@STORJ6:/storj/DBs# sqlite3 storage_usage.db "SELECT * FROM (SELECT timestamp, hex(satellite_id) AS satellite, at_rest_total, interval_end_time, julianday(interval_end_time), ROW_NUMBER() OVER (PARTITION BY satellite_id ORDER BY timestamp DESC) AS rown FROM storage_usage) WHERE rown <= 6 ORDER BY satellite,rown"
2024-01-31 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1144871492.78699|2024-01-31 12:08:11.655857+00:00|2460341.00569046|1
2024-01-30 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1905812703.83945|2024-01-30 22:07:58.305931+00:00|2460340.42220262|2
2024-01-29 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1963121158.57989|2024-01-29 22:49:17.618464+00:00|2460339.45089836|3
2024-01-28 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1962384981.24134|2024-01-28 22:48:33.406566+00:00|2460338.45038666|4
2024-01-27 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1960121297.41671|2024-01-27 22:48:21.61155+00:00|2460337.45025014|5
2024-01-26 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1964648129.49649|2024-01-26 22:49:49.495744+00:00|2460336.45126731|6
2024-01-31 00:00:00+00:00|84A74C2CD43C5BA76535E1F42F5DF7C287ED68D33522782F4AFABFDB40000000|366591057285.886|2024-01-31 12:20:56.281846+00:00|2460341.0145403|1
2024-01-30 00:00:00+00:00|84A74C2CD43C5BA76535E1F42F5DF7C287ED68D33522782F4AFABFDB40000000|607945919264.781|2024-01-30 22:21:20.621328+00:00|2460340.43148867|2
2024-01-29 00:00:00+00:00|84A74C2CD43C5BA76535E1F42F5DF7C287ED68D33522782F4AFABFDB40000000|625035496727.823|2024-01-29 23:09:06.727148+00:00|2460339.46466119|3
2024-01-28 00:00:00+00:00|84A74C2CD43C5BA76535E1F42F5DF7C287ED68D33522782F4AFABFDB40000000|625963109207.811|2024-01-28 23:18:00.108378+00:00|2460338.47083458|4
2024-01-27 00:00:00+00:00|84A74C2CD43C5BA76535E1F42F5DF7C287ED68D33522782F4AFABFDB40000000|629843985583.987|2024-01-27 23:24:09.029323+00:00|2460337.4751045|5
2024-01-26 00:00:00+00:00|84A74C2CD43C5BA76535E1F42F5DF7C287ED68D33522782F4AFABFDB40000000|629327864851.166|2024-01-26 23:21:56.485264+00:00|2460336.47357043|6
2024-01-31 00:00:00+00:00|A28B4F04E10BAE85D67F4C6CB82BF8D4C0F0F47A8EA72627524DEB6EC0000000|2550794586300.69|2024-01-31 10:34:11.078242+00:00|2460340.940406|1
2024-01-30 00:00:00+00:00|A28B4F04E10BAE85D67F4C6CB82BF8D4C0F0F47A8EA72627524DEB6EC0000000|6415699699302.59|2024-01-30 23:30:44.978691+00:00|2460340.47968726|2
2024-01-29 00:00:00+00:00|A28B4F04E10BAE85D67F4C6CB82BF8D4C0F0F47A8EA72627524DEB6EC0000000|5058033869119.73|2024-01-29 19:44:39.873507+00:00|2460339.32268373|3
2024-01-28 00:00:00+00:00|A28B4F04E10BAE85D67F4C6CB82BF8D4C0F0F47A8EA72627524DEB6EC0000000|6234512324652.41|2024-01-28 21:51:48.240841+00:00|2460338.41097501|4
2024-01-27 00:00:00+00:00|A28B4F04E10BAE85D67F4C6CB82BF8D4C0F0F47A8EA72627524DEB6EC0000000|5010395282047.32|2024-01-27 18:46:03.322426+00:00|2460337.28198289|5
2024-01-26 00:00:00+00:00|A28B4F04E10BAE85D67F4C6CB82BF8D4C0F0F47A8EA72627524DEB6EC0000000|5018996834657.59|2024-01-26 20:56:45.586654+00:00|2460336.37274985|6
2024-01-31 00:00:00+00:00|AF2C42003EFC826AB4361F73F9D890942146FE0EBE806786F8E7190800000000|2177062238235.85|2024-01-31 10:35:42.833848+00:00|2460340.94146799|1
2024-01-30 00:00:00+00:00|AF2C42003EFC826AB4361F73F9D890942146FE0EBE806786F8E7190800000000|4518726578542.36|2024-01-30 22:41:42.942761+00:00|2460340.44563591|2
2024-01-29 00:00:00+00:00|AF2C42003EFC826AB4361F73F9D890942146FE0EBE806786F8E7190800000000|4658415876735.9|2024-01-29 22:02:22.726171+00:00|2460339.41831859|3
2024-01-28 00:00:00+00:00|AF2C42003EFC826AB4361F73F9D890942146FE0EBE806786F8E7190800000000|5340204565777.73|2024-01-28 21:51:46.287986+00:00|2460338.41095241|4
2024-01-27 00:00:00+00:00|AF2C42003EFC826AB4361F73F9D890942146FE0EBE806786F8E7190800000000|7335583691130.42|2024-01-27 22:17:33.555502+00:00|2460337.4288606|5
2024-01-26 00:00:00+00:00|AF2C42003EFC826AB4361F73F9D890942146FE0EBE806786F8E7190800000000|9712548046971.15|2024-01-26 22:12:46.172614+00:00|2460336.42553441|6

and what you have said before:

@elek

(which makes it unnecessary to manually calculate the difference between rows. The interval of rows can be different and should be calculated for actual average usage)

For me it looks like this when I take the first 2 rows:

2024-01-31 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1144871492.78699|2024-01-31 12:08:11.655857+00:00|2460341.00569046|1
2024-01-30 00:00:00+00:00|7B2DE9D72C2E935F1918C058CAAF8ED00F0581639008707317FF1BD000000000|1905812703.83945|2024-01-30 22:07:58.305931+00:00|2460340.42220262|2

Byte hours: 1144871492.78699
Interval: 2460341.00569046-2460340.42220262 * 24
Average: 1144871492.78699/14,00370816
= 81754880,90055927 |~ 8,17 TB