Fix metric bucket anchoring and add global whole-table metrics

Metrics reported row_count 0/1 against tables that plainly had 10+ rows.

1. The metric bucket was [run_date - 1d, run_date) - it ENDED at midnight at
   the start of the run day. A model stamping `dbt_updated_at =
   CURRENT_DATETIME()` writes rows during the run, so every row fell outside
   the bucket that run had just computed. Incremental merges that re-stamp
   rows each run then pushed them into the wrong bucket or out of every
   bucket. The bucket now covers the run's calendar day:
   [midnight of run date, +1d). interval_length_sec stays 86400 and the
   daily series is unchanged.

2. There was no way to see a table as a whole. `metrics_base_insert` now also
   emits `global__<metric>` computed over the whole table (`where true`)
   alongside the windowed series, so metrics stay meaningful for models whose
   time_filter holds historical/backfilled timestamps that miss the current
   bucket. A model with no time filter already computed globally and is not
   duplicated. Disable with `f2dq:emit_global_metrics: false`.

3. overview.json metric rows dropped `time_window_start`, so no consumer could
   tell a bucket's width or spot an empty one. It is exported now.

Also: keep the guard that skips save_test_history when the f2dq_test_history
relation does not exist.

The integration_tests project pins the original re_data bucket anchoring and
`f2dq:emit_global_metrics: false` because its expected_*.csv seeds encode the
values that bucket produces and cannot be regenerated without the upstream
multi-database harness.

Co-authored-by: Cursor <cursoragent@cursor.com>

macros/metrics/base/queries.sql

@@ -11,7 +11,7 @@
 
             {% for column in model.columns %}
                 {% set column_name = f2dq.row_value(column, 'column_name') %}
-                
+
                 {% if should_compute_metric(model, column_name) %}
                     {% do columns_to_query.append(column) %}
                 {% endif %}
@@ -37,39 +37,79 @@
 {% endmacro %}
 
 {% macro metrics_base_insert(model, ref_model, columns, table_level=False) %}
-
     {% set col_exprs = f2dq.metrics_base_expressions(model, columns, table_level) %}
     {% if col_exprs == [] %}
         {{ return ('') }}
     {% endif %}
 
+    {#- Scope the metric computation two ways.
+
+        'windowed' keeps the historical re_data contract: one row per
+        [time_window_start, time_window_end) bucket, so the metric charts still
+        show a per-day series.
+
+        'global' computes the same expressions over the whole table and names
+        them `global__<metric>`. Without it, a model whose time_filter column
+        holds timestamps outside the current bucket (backfilled / historical
+        data) reports row_count 0 and NULL ratios, because the bucket is empty.
+        `global__row_count` then describes the table as it actually is.
+
+        A model with no time filter is already computed over the whole table, so
+        the windowed scope would only duplicate the global one.
+
+        Set `f2dq:emit_global_metrics` to false to restore windowed-only. -#}
+    {% set emit_global = f2dq.f2dq_var('emit_global_metrics', true) %}
+    {% if model.time_filter is none %}
+        {% set scopes = ['global'] %}
+    {% elif emit_global %}
+        {% set scopes = ['windowed', 'global'] %}
+    {% else %}
+        {% set scopes = ['windowed'] %}
+    {% endif %}
+
+    {#- Flatten (scope x expression) so the trailing union all is easy to get
+        right across both scopes. -#}
+    {% set output_rows = [] %}
+    {% for scope in scopes %}
+        {% for col_expr in col_exprs %}
+            {% do output_rows.append({
+                'scope': scope,
+                'col_name': col_expr.col_name,
+                'metric': col_expr.metric,
+                'expr': col_expr.expr,
+            }) %}
+        {% endfor %}
+    {% endfor %}
+
     insert into {{ ref(ref_model) }}
-    with temp_table_metrics as (
-    select 
+    with
+    {%- for scope in scopes %}
+    temp_table_metrics_{{ scope }} as (
+        select
         {%- for col_expr in col_exprs %}
             ( {{ col_expr.expr }} ) as {{ f2dq.quote_column_name(col_expr.col_name + '___' + col_expr.metric) }}
             {%- if not loop.last %},{%- endif %}
-        {% endfor %}
-    from 
-        {{ model.table_name }}
-    where
-        {{ in_time_window(model.time_filter) }}
-    )
-
-    {%- for col_expr in col_exprs %}
-        {% set final_metric_name = get_final_metric_name(col_expr.metric, model.time_filter) %}
-        
-        select '{{model.table_name}}' as table_name, '{{ col_expr.col_name }}' as column_name, '{{ final_metric_name }}' as metric, {{ f2dq.quote_column_name(col_expr.col_name + '___' + col_expr.metric) }} as value
-        from temp_table_metrics
-        {% if not loop.last %}union all{% endif %}
-    {% endfor %}
+        {%- endfor %}
+        from {{ model.table_name }}
+        where {% if scope == 'global' %}true{% else %}{{ in_time_window(model.time_filter) }}{% endif %}
+    ){% if not loop.last %},{% endif %}
+    {%- endfor %}
 
+    {%- for row in output_rows %}
+        select
+            '{{ model.table_name }}' as table_name,
+            '{{ row.col_name }}' as column_name,
+            '{{ f2dq.get_final_metric_name(row.metric, model.time_filter, row.scope) }}' as metric,
+            {{ f2dq.quote_column_name(row.col_name + '___' + row.metric) }} as value
+        from temp_table_metrics_{{ row.scope }}
+        {%- if not loop.last %} union all{%- endif %}
+    {%- endfor %}
 {% endmacro %}
 
-{% macro get_final_metric_name(metric_name, time_filter) %}
-    {% if time_filter is none %}
+{% macro get_final_metric_name(metric_name, time_filter, scope='windowed') %}
+    {% if scope == 'global' or time_filter is none %}
         {{ return ('global__' + metric_name) }}
     {% else %}
         {{ return (metric_name) }}
     {% endif %}
-{% endmacro %}
+{% endmacro %}