Initial publish of dbt_f2dq (f2dq) package v0.12.1.

Clean package repo for Gitea installs via packages.yml git URL. Co-authored-by: Cursor <cursoragent@cursor.com>
2026-10-11 17:37:40 +03:00
commit ff096b51b5
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+{{
+    config(
+        materialized='view'
+    )
+}}
+select
+    z.id,
+    z.table_name,
+    z.column_name,
+    z.metric,
+    z.z_score_value,
+    z.modified_z_score_value,
+    m.anomaly_detector,
+    z.last_value,
+    z.last_avg,
+    z.last_median,
+    z.last_stddev,
+    z.last_median_absolute_deviation,
+    z.last_mean_absolute_deviation,
+    z.last_iqr,
+    z.last_first_quartile - (cast( {{ json_extract('m.anomaly_detector', 'whisker_boundary_multiplier') }} as {{numeric_type()}} ) * z.last_iqr) lower_bound,
+    z.last_third_quartile + (cast( {{ json_extract('m.anomaly_detector', 'whisker_boundary_multiplier') }} as {{numeric_type()}} ) * z.last_iqr) upper_bound,
+    z.last_first_quartile,
+    z.last_third_quartile,
+    z.time_window_end,
+    z.interval_length_sec,
+    z.computed_on,
+    {{ f2dq.generate_anomaly_message('z.column_name', 'z.metric', 'z.last_value', 'z.last_avg') }} as message,
+    {{ f2dq.generate_metric_value_text('z.metric', 'z.last_value') }} as last_value_text
+from
+    {{ ref('f2dq_z_score')}} z 
+left join {{ ref('f2dq_selected') }} m 
+on {{ split_and_return_nth_value('table_name', '.', 1) }} = m.database
+and {{ split_and_return_nth_value('table_name', '.', 2) }} = m.schema
+and {{ split_and_return_nth_value('table_name', '.', 3) }} = m.name
+where
+    case when (lower(coalesce({{ json_extract('m.anomaly_detector', 'direction') }}, 'both')) = 'up' and z.last_value > z.last_avg)
+        or (lower(coalesce({{ json_extract('m.anomaly_detector', 'direction') }}, 'both')) = 'down' and z.last_value < z.last_avg)
+        or (lower(coalesce({{ json_extract('m.anomaly_detector', 'direction') }}, 'both')) != 'up' and lower(coalesce({{ json_extract('m.anomaly_detector', 'direction') }}, 'both')) != 'down')
+        then
+            case 
+                when {{ json_extract('m.anomaly_detector', 'name') }} = 'z_score' 
+                    then abs(z_score_value) > cast({{ json_extract('m.anomaly_detector', 'threshold') }} as {{ numeric_type() }})
+                when {{ json_extract('m.anomaly_detector', 'name') }} = 'modified_z_score' 
+                    then abs(modified_z_score_value) > cast( {{ json_extract('m.anomaly_detector', 'threshold') }} as {{numeric_type()}} )
+                when {{ json_extract('m.anomaly_detector', 'name') }} = 'boxplot' 
+                    then (
+                        z.last_value < z.last_first_quartile - (cast( {{ json_extract('m.anomaly_detector', 'whisker_boundary_multiplier') }} as {{numeric_type()}} ) * z.last_iqr)
+                        or 
+                        z.last_value > z.last_third_quartile + (cast( {{ json_extract('m.anomaly_detector', 'whisker_boundary_multiplier') }} as {{numeric_type()}} ) * z.last_iqr)
+                    )
+                else false
+            end
+        else false
+    end