Francois Forster
12/13/2023, 8:06 PMFrancois Forster
12/13/2023, 8:08 PMcreate table `test_table` (timestamp timestamp, id int);
insert into `test_table`
(timestamp, id)
values
(timestamp("2023-11-27T12:00:00"), 123),
(timestamp("2023-11-28T12:00:00"), 123),
(timestamp("2023-11-29T12:00:00"), 123),
(timestamp("2023-11-30T12:00:00"), 123),
(timestamp("2023-12-01T12:00:00"), 123),
(timestamp("2023-12-02T12:00:00"), 123),
(timestamp("2023-12-03T12:00:00"), 123),
(timestamp("2023-12-04T12:00:00"), 123),
(timestamp("2023-12-05T12:00:00"), 123),
(timestamp("2023-12-06T12:00:00"), 123),
(timestamp("2023-12-07T12:00:00"), 123),
(timestamp("2023-12-08T12:00:00"), 123),
(timestamp("2023-12-09T12:00:00"), 123),
(timestamp("2023-12-10T12:00:00"), 123),
(timestamp("2023-12-11T12:00:00"), 123),
(timestamp("2023-12-12T12:00:00"), 123)Francois Forster
12/13/2023, 8:09 PM- elementary.freshness_anomalies:
timestamp_column: "timestamp"
days_back: 14
backfill_days: 2
time_bucket:
period: day
count: 1Francois Forster
12/13/2023, 8:10 PMFrancois Forster
12/13/2023, 8:19 PMFrancois Forster
12/13/2023, 10:18 PMFrancois Forster
12/13/2023, 10:31 PMOfek Weiss
01/08/2024, 8:42 AMFrancois Forster
01/08/2024, 2:56 PMOfek Weiss
01/09/2024, 10:50 AMelementary are you using?
also, the days_back and backfill_days parameters were deprecated in favor of training_period and detection_period, mind trying to use those instead?Francois Forster
01/09/2024, 3:00 PMdbt-core==1.6.7
dbt-bigquery==1.6.8
elementary-data[bigquery]== 0.11.0Francois Forster
01/09/2024, 3:00 PM- package: elementary-data/elementary
version: 0.12.1Francois Forster
01/09/2024, 3:00 PM