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/public/store/generate_overview.sql

@@ -36,7 +36,7 @@
     (    
         select
             {{ overview_select_base('metric', 'computed_on')}}
-            {{ to_single_json(['metric', 'value', 'time_window_end', 'interval_length_sec']) }} as {{ f2dq.quote_column('data') }}
+            {{ to_single_json(['metric', 'value', 'time_window_start', 'time_window_end', 'interval_length_sec']) }} as {{ f2dq.quote_column('data') }}
         from
             {{ ref('f2dq_base_metrics') }}
             where {{ in_date_window('time_window_end', start_date, end_date) }}