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Lossy TimeSeries DataBase
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Peter J. Holzer c462ca4d80 Extrapolate further into the future 
So far we have only extapolated as far into the future as we could look
into the past. Everything beyond that was "infinity". Now we use the
first and last observation to extrapolate beyond that.
 		2024-09-07 12:01:20 +02:00
clients Record postgresql version 2024-02-06 11:45:21 +01:00
doc Think about scheduling measurements and processing them 2022-11-27 10:19:37 +01:00
templates Fix formatting of time values in graph descriptions 2024-08-24 23:07:05 +02:00
test_data Rename data to test_data to prevent clash with live layout 2023-03-19 11:38:37 +01:00
tests Allow arbitrary number of stops 2023-03-19 11:34:38 +01:00
app.py Avoid race condition during config update 2023-09-20 10:50:29 +02:00
dashboard.py Fix formatting of time values in graph descriptions 2024-08-24 23:07:05 +02:00
ltsdb-json Maintain a single lossy timeseries (PoC) 2022-08-20 17:39:12 +02:00
ltsdb_json.py Log JSON decode errors 2024-08-24 22:51:29 +02:00
ltsdb_test Use random time stamps 2023-08-18 21:14:15 +02:00
predict_disk_full Use a lossy timeseries to predict when a filesystem will be full (PoC) 2022-08-20 17:40:16 +02:00
predict_disk_full_home_bytes Use a lossy timeseries to predict when a filesystem will be full (PoC) 2022-08-20 17:40:16 +02:00
predict_disk_full_var_bytes Use a lossy timeseries to predict when a filesystem will be full (PoC) 2022-08-20 17:40:16 +02:00
process_queue Extrapolate further into the future 2024-09-07 12:01:20 +02:00
pyproject.toml Add test case 2023-02-04 12:43:04 +01:00
record_df Record disk usage in LTsDb 2022-08-21 12:00:07 +02:00
record_dus Be quiet(er) 2022-08-21 13:15:01 +02:00
requirements.txt Add gunicorn to requirements 2022-09-03 22:57:32 +02:00