fix: align the backfill start to the time bucket on reruns

[joostboon]

Summary

On reruns of anomaly tests on sources and incremental models, the backfill window starts at a plain date (detection_end - backfill_days), not at the start of a time bucket. For weekly, monthly and multi-day buckets, the buckets are then generated from that mid-bucket start, for example Sep 15 to Oct 15 instead of Sep 1 to Oct 1. Rows fall into no bucket, the values come out as 0, and the test fails with a drop that isn't there. It only happens on the second and later runs, which makes it easy to miss.

The fix aligns the backfill start to the start of its bucket with get_start_bucket_in_data, the macro the monitors already use to assign rows to buckets.

Impact

This changes the incremental path of every anomaly test and collect_metrics on sources and incremental models:

• Daily buckets: no change, since the backfill start is already a bucket start.
• Weekly, monthly and multi-day buckets (and hour buckets whose size doesn't divide 24 hours): a rerun now recalculates from the start of the bucket that contains the backfill start, so at most one extra bucket per run, and the values are correct.

Plain tables and views, and runs with force_metrics_backfill, recalculate everything anyway and are not affected.

Tests

test_buckets_stay_aligned_on_rerun[week|month] runs a weekly and a monthly dimension anomaly test twice on a source, then checks that every stored bucket starts on the same weekday (week) or on the 1st (month). The status check alone can't catch the weekly case: with one upload a week, every shifted 7-day bucket still holds one upload, so the values look normal. Locally on DuckDB:

• Without the fix, the monthly second run fails with the false drop, and the weekly buckets start on two different weekdays.
• With the fix, both pass, as do the dimension, backfill logic, volume and column anomaly suites.

Month is skipped on Redshift, which has no monthly buckets.

Split out of #1071 (include_current_bucket) as suggested in review. #1071 depends on this fix, so this should merge first.

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Summary by CodeRabbit

• Bug Fixes
  • Monitoring buckets for weekly, monthly, and three-day intervals now stay aligned to their expected boundaries when checks are rerun with backfills, supporting consistent results across runs.
  • Backfills that begin partway through a bucket now use the start of the appropriate bucket, keeping monitoring results aligned with the configured time interval. This applies when determining the backfill window for metric buckets.

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• integration_tests/tests/test_dimension_anomalies.py

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📝 Walkthrough

📝 Walkthrough

📝 Walkthrough

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Walkthrough

The bucket configuration now aligns the backfill start with its calendar bucket. The integration test checks weekly and monthly bucket alignment after reruns.

Changes

Dimension anomaly bucket alignment

Layer / File(s)	Summary
Align bucket starts and validate reruns macros/edr/data_monitoring/data_monitors_configuration/get_buckets_configuration.sql, integration_tests/tests/test_dimension_anomalies.py	The configuration derives the backfill bucket start using elementary.get_start_bucket_in_data. The integration test checks weekly and monthly bucket starts after reruns, with the monthly case skipped on Redshift.

Priority: ➖ Normal

Estimated code review effort: 2 (Simple) | ~10 minutes

Change: Bug fix

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Merge Risk: ⚪ Minimal · up to aa05c

The change aligns backfill starts to bucket boundaries and adds rerun checks for the affected bucket types. No material merge-blocking risk is identified.

Security Architecture Review

Security architecture risk: 🔵 Low · up to aa05c

The change restores bucket alignment without adding public endpoints, inputs, or privileges. Remaining uncertainty concerns previously stored misaligned metrics and recovery from interrupted or concurrent runs across supported databases.

Retained concerns
No architecture-level concerns identified.

Security review details

Security Blast Radius

• inferred — The recalculation window can extend backward within the configured bucket, but inspected paths continue using the same configured model relation and metric properties. The change does not introduce a way to select additional assets or obtain greater database authority.

Trust Boundaries and Controls

• observed — Existing historical-metric selection retains full-table-name and metric-property predicates, with optional metric-name and column restrictions. Anomaly scoring retains corresponding relation, metric, column, and dimension filters. These controls are unchanged by the PR.

Resilience and Maintainability Implications

• observed — The existing persistence path appends metrics before separate test-result writes, deduplicates within the current invocation, and explicitly commits metric insertion on DuckDB. These mechanisms predate this PR; they do not establish cross-adapter atomicity or target-table idempotency under interrupted or concurrent reruns.

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✅ Passed checks (5 passed)

Check name	Status	Explanation
Description Check		Check skipped - CodeRabbit’s high-level summary is enabled.
Title check		The title clearly and concisely describes the main change: aligning the backfill start with the configured time bucket during reruns.
Docstring Coverage		Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 4 functions across 1 files.
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Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.

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[github-actions]

👋 @joostboon
Thank you for raising your pull request.
Please make sure to add tests and document all user-facing changes.
You can do this by editing the docs files in the elementary repository.

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Actionable comments posted: 1

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Inline comments:
Review comments at @integration_tests/tests/test_dimension_anomalies.py:
- Around line 354-357: Update the test setup that builds test_args so
detection_period is derived from a backfill day count that moves the effective
start date off a bucket boundary. For weekly and monthly periods, adjust the
count from 31 days until the resulting date is not Monday or the first of the
month, respectively; keep the existing behavior for other periods.

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• macros/edr/data_monitoring/data_monitors_configuration/get_buckets_configuration.sql

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[MikaKerman]

The new test only covers count=1 buckets. A multi-day case, say 3-day buckets, would exercise the floor(.../count) * count branch of get_start_bucket_in_data directly, since that branch is part of what this PR now relies on. Not a blocker, and could be a follow-up.

Related, and this predates the PR: for count > 1 the grid origin is trunc_min_bucket_start, which depends on days_back and the run date. For example, 3-day buckets would start from a different day on each run, so buckets stored on one run may not line up with the grid on the next. This change makes the backfill start consistent with the current run's grid, which is what we want, but it doesn't make that grid stable across runs. Curious whether that's known or intended, and whether it's worth a follow-up ticket.

[MikaKerman]

Quick question about installs that already ran with the old behavior. They'll have weekly or multi-day rows in data_monitoring_metrics with shifted bucket_start values. After this change the reruns will write aligned buckets next to them. Do those old rows get replaced or ignored when the anomaly scores are computed, or could they overlap with the new buckets in the training window? If it's already handled, ignore me. If not, might be worth a note in the PR or a cleanup path.

[joostboon]

Yes, for timestamped tests the anomaly query only reads history whose bucket_start/bucket_end exactly match a bucket in the current run’s grid (get_anomaly_scores_query.sql), so the shifted rows are ignored. The incremental check in get_buckets_configuration.sql matches on the same exact start/end, so after the upgrade the aligned buckets count as missing and the first run backfills them from the start of days_back. Later runs find them and skip them.

Two side effects, neither needing code: the first run after upgrading recomputes the full days_back window for weekly and multi-day tests on sources and incremental models, so it’s heavier once, and the old shifted rows stay in data_monitoring_metrics (unused) until normal cleanup removes them.

On the multi-day grid moving with days_back and the run date: it’s known behavior and only affects count > 1 day/week/month buckets. Each run builds and scores on its own grid, so results stay correct. The cost is that the incremental cache mostly misses for those tests and rows from older grids pile up in data_monitoring_metrics. Since it’s a cost issue on an uncommon config, I’m not planning to change it unless we see someone using multi-day buckets at scale. what do you think? happy to open a ticket if you think it's needed

[MikaKerman]

Approving, nothing blocking. Two thoughts that are still open, both fine as follow-ups:

The new tests cover week, month and 3-day buckets. Thanks for adding the multi-day case.

Related, and this predates the PR: for multi-day buckets (count > 1), the bucket start times are counted from trunc_min_bucket_start, which depends on days_back and the run date. So a 3-day bucket could start on a different day from one run to the next, and buckets stored on an earlier run might not match the next run's buckets. This change makes the backfill start match the current run's buckets, which is what we want, but it doesn't make those start times stable across runs. Curious whether that's known or intended, and whether it's worth a follow-up ticket.

Also, the question on get_buckets_configuration.sql about rows already stored with shifted bucket_start values: the anomaly query only reads history that matches the current buckets, so I expect those rows are simply ignored and the buckets get recomputed once. Just flagging in case you know of a case where that isn't true.