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feat: add max_change_absolute to metric_stability - #1096
Adds max_change_absolute to elementary.metric_stability, so a threshold can
be expressed as a raw move rather than only as a relative one.
Closes CORE-1664. Raised by a customer who wants to alert when a margin moves 20
basis points, e.g. 45.30% dropping below 45.10%.
Why
max_change_percent is a relative change, abs(measured - baseline) / abs(baseline) * 100.
That is the right instrument for magnitudes like sum and row_count, where
scale varies by orders of magnitude between models, so one number transfers
across a whole model without retuning.
For ratios the logic inverts. A margin already sits on a fixed scale, so the
move that transfers is the absolute one.
And because the relative form divides by the baseline, its sensitivity is
recomputed against each bucket's own prior value. A setting that means 20bp at a
45.30% margin means something different everywhere else:
Bucket's margin
What max_change_percent: 0.4415 catches
20%
8.8 bp
45.3%
20 bp
60%
26.5 bp
So it drifts as the data drifts, which is self-defeating for a metric you are
watching because it moves. Noisy where the ratio is low, blind where it is high.
No existing test covers this. column_anomalies is anomaly detection rather than
a threshold, ignore_small_changes is also percent-based, min_value filters on
magnitude rather than change, and accepted_range_with_context is a static
per-row bound. metric_stability is the only test that compares a bucket against
its own earlier measurements.
What it does
Exposed as a plain absolute value rather than literally "basis points", because
the right number depends on how the figure is stored and guessing would be a
silent wrong answer. 20bp is 0.20 on a 0-100 scale, 0.0020 on a 0-1 scale.
AND, so the absolute one is a noise floor under the relative one
max_change_percent now defaults internally to none so that unset is
distinguishable from an explicit zero. Unset still behaves as 0 when no absolute
threshold stands in for it; I rendered the predicate for percent=none and percent=0 and both are byte-identical to master's.
At a zero baseline, where relative change has no meaning, the absolute threshold
decides on its own. Without one, any move away from exactly zero still counts, as
before. This is a deliberate behaviour change: a metric legitimately sitting at 0,
such as zero_percent on a clean column, is now held to the same tolerance as
everything else instead of failing on any movement at all.
Review found a bug worth calling out
The first commit had the relative conjunct as baseline != 0 and ..., which is
false at a zero baseline. ANDed with the absolute test it made the predicate false
whatever the measured value, so setting both thresholds suppressed every
zero-baseline restatement: 0 -> 1000 passed. Adding an absolute threshold as a
noise floor therefore switched off detection that a percent-only config still had.
The second commit fixes it by satisfying the relative guard at zero rather than
falsifying it. The same restructure closed a second gap: with only an absolute
threshold the relative conjunct was not emitted at all, so there was no
float-noise guard and max_change_absolute: 0 failed on re-aggregation noise.
Testing
Six new integration tests: an absolute threshold on a ratio, AND semantics, a zero
baseline with absolute only, a zero baseline with both thresholds, an unset
threshold still failing a sub-1% change, and an absolute threshold across both change_since baselines.
Each was checked to discriminate, by stubbing the feature out and confirming it
fails. One earlier version of the AND test passed either way and was rewritten
around a smaller base, where a 0.10 move is 2% relative but under the absolute
floor.
Run locally: Postgres 25 passed, ClickHouse 25 passed, DuckDB 50 passed including test_collect_metrics and test_column_anomalies as regression checks.
Note for reviewers
The user-facing docs at docs.elementary-data.com/data-tests/metric-stability live
outside this repo and do not yet describe the new argument, the AND semantics, or
the zero-baseline change. Needs a follow-up there.
Metric stability checks support an optional absolute-change threshold alongside the relative threshold. When both are set, a change must exceed both limits; without an absolute threshold, a scale-adjusted noise floor is used.
Bug Fixes
Threshold inputs are validated, and invalid values are rejected.
Zero-baseline percentage changes return no percentage, and threshold comparisons account for floating-point precision.
max_change_percent is a relative change, which suits magnitudes whose
scale varies by orders of magnitude between models. It does not suit
ratios: a margin already sits on a fixed scale, so the move that
transfers is the absolute one.
The relative form also divides by the baseline, so its sensitivity is
recomputed against each bucket's own prior value. A setting that means 20
basis points at a 45% margin means about 9bp at 20% and 27bp at 60%, so
it drifts as the data drifts. max_change_absolute expresses the move
directly and means the same thing at every level.
Setting both fails only when both are exceeded, so the absolute one acts
as a noise floor under the relative one. That needs max_change_percent to
default to none rather than 0 so an unset value is distinguishable from
an explicit zero; unset still behaves as 0 when no absolute threshold
stands in for it.
The zero-baseline branch is skipped when an absolute threshold is set.
It exists only because relative change is undefined at zero, and absolute
change is not, so a metric legitimately sitting at 0 is now held to the
same tolerance as everything else rather than failing on any movement.
Closes CORE-1664
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Setting both thresholds suppressed every zero-baseline restatement. The
relative conjunct was written as `baseline != 0 and ...`, which is false
at zero, and ANDing it with the absolute test made the whole predicate
false whatever the measured value. Adding max_change_absolute as a noise
floor therefore switched off zero-baseline detection entirely, which a
percent-only config still had. The relative guard is now satisfied rather
than falsified at zero, so the absolute threshold decides there.
The absolute path also had no float-noise guard: with only an absolute
threshold the relative conjunct was not emitted at all, so
max_change_absolute: 0 failed on re-aggregation noise. The relative guard
is now always emitted, clamped to the noise floor.
Rejects a max_change_absolute too small to survive the "%.10f" rendering,
which silently became 0, and rejects booleans, which pass Jinja's
`is number` because bool subclasses int.
Adds the three cases the review found untested: a zero baseline with both
thresholds set, an unset threshold still failing a sub-1% change, and an
absolute threshold across both change_since baselines.
Test names shortened to stay under the 63-character identifier limit
Postgres applies to the seed table named after each test.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
👋 @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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Walkthrough
The metric stability test and query now accept optional relative and absolute change thresholds. The query applies threshold comparisons to zero and nonzero baselines. The test validates supplied thresholds, and integration tests cover threshold and baseline combinations.
Changes: Metric stability thresholds
Layer / File(s)
Summary
Threshold arguments and validation macros/edr/tests/test_metric_stability.sql
The test accepts optional relative and absolute thresholds, passes both to query generation, and validates each supplied value. Its documentation describes threshold behavior.
Absolute-only metric tests can miss changes that exceed their configured threshold when metric values are large. Resolve or explicitly accept this limitation before merging.
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The title "feat: add max_change_absolute to metric_stability" names the main change: a new max_change_absolute argument on the metric_stability test. The changeset adds this parameter to the test macr…
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The title "feat: add max_change_absolute to metric_stability" names the main change: a new max_change_absolute argument on the metric_stability test. The changeset adds this parameter to the test macro, the argument parser, and the metric_stability_query macro, and adds integration tests for it. The title is specific, short, and uses a conventional commit prefix. It does not cover the secondary changes (AND semantics, zero-baseline handling, float-precision validation, Dremio fractional-seed tests), which is acceptable for a title.
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Unverified finding
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Fix the corrupted docstring in test_metric_stability_both_detect_zero_baseline.
Line 403 ends with "a relative conjunct written as". Line 404 then starts with "is false there". The expression that belongs between them is missing. Line 404 also contains the typo "ANDead".
The docstring explains why the baseline = 0 or ... relative guard exists. As written, the explanation cannot be followed. Restore the missing expression and correct the typo.
📝 Proposed fix
- Relative change has no meaning at zero, so a relative conjunct written as- is false there. ANDead with the absolute one it would- suppress every zero-baseline restatement, and adding an absolute threshold- as a noise floor would silently switch that detection off.+ Relative change has no meaning at zero, so a plain relative conjunct such+ as `change_percent > threshold` is false there. If it were combined with+ the absolute one by AND, it would suppress every zero-baseline+ restatement, and adding an absolute threshold as a noise floor would+ silently switch that detection off.
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Null-safe division. The zero-baseline guard reads `baseline = 0 or
<division>`, and SQL does not promise the left side is evaluated first, so
an engine that evaluates both would raise on the division. nullif makes
the expression NULL at a zero baseline instead. This also covers the
pre-existing `baseline != 0 and <division>` form, which had the same
exposure.
A tolerance under the absolute comparison. A decimal threshold has no
exact float representation, so two moves that are both 0.20 in decimal
land either side of it: 45.30 -> 45.10 is 0.19999999999999574 and
45.30 -> 45.50 is 0.20000000000000284. Without it the customer's own 20bp
example fires in one direction and not the other.
Validation now names a cutoff that matches what the query does. A percent
below the noise floor was accepted and then silently clamped to it, and
the old message quoted a minimum that was not the real one.
Adds tests for the rejected threshold values, which had none, and for the
float boundary. The boundary test is skipped where metric_value is stored
at single precision: dbt's type_float is double on some adapters and
single on others, and the same subtraction gives 0.20000000000000284 on
Postgres against 0.20000076293945312 on DuckDB and ClickHouse. That limit
is now documented, since it bounds what an absolute threshold can mean.
Repairs a test docstring mangled by an unquoted heredoc and by the typos
hook rewriting ANDed.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Actionable comments posted: 1
Fix comments: Fix CodeRabbit comments on this PR
Prompt to fix review comments
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Inline comments:
Review comments at
@macros/edr/data_monitoring/monitors_query/metric_stability_query.sql:
- Line 82: Update the precision used to render max_change_absolute in the metric
stability query so every threshold accepted by validation retains its value; add
a boundary test where a zero baseline changes by less than a very small accepted
threshold, such as 0.00000000014.
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Review found 6 issues. One correctness bug, the rest smaller. The AND semantics, the zero-baseline handling, unset vs explicit-0 max_change_percent, the nullif change and the boolean rejection all look right.
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Bug: the tolerance rounds away for small thresholds. The 1e-9 relative slack is rendered with "%.10f", so for any threshold below roughly 0.05 it disappears and the literal is the bare threshold again. That includes 0.0020, the 0-1 scale form the PR description recommends for 20bp: 0.0020 * (1 + 1e-9) renders as 0.0020000000.
On double-precision warehouses (Postgres, Snowflake, BigQuery), 0.1000 -> 0.0980 computes 0.0020000000000000018 and fails, while 0.1001 -> 0.0981 computes 0.001999999999999988 and passes. Over margins 0.10 to 0.98 in 1bp steps, 8517 of 8800 exactly-20bp moves fire. On the 0-100 scale the same move passes, so the behaviour depends on how the metric is scaled.
Suggest rendering with enough significant digits, e.g. "%.17g", instead of fixed decimals.
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This says the tolerance makes the 20bp example behave the same in both directions, but on adapters where type_float is single precision (DuckDB, ClickHouse, per the test file's own note) storage error is around 1e-5, four orders of magnitude above the slack. There, 45.30 -> 45.10 stores as a diff of 0.20000076 and fails, while 45.10 -> 44.90 gives 0.19999695 and passes.
The boundary test skips those targets, so this is known, but the comment reads as if it is fixed everywhere. Worth stating the limitation here.
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This only rejects values below the minimum, but "%.10f" also rounds any absolute threshold that is not a multiple of 1e-10. 0.00000000014 passes validation and renders as 0.0000000001; 0.00000000016 becomes 0.0000000002. The error message says only smaller values get rounded. Minor in practice, and fixing the rendering on the query side would make this go away.
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This only covers 0.20 on a 0-100 scale, where the slack survives the 10-decimal rendering, so it cannot catch the rounding issue in the query macro. A 0-1 scale variant (e.g. base 0.1001, max_change_absolute: 0.0020, restate to 0.0981) fails today on Postgres and would pin the fix.
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Nit: this new comment was added under the existing one rather than replacing it, so the macro now has two stacked doc comments that both open with "Relative change from a baseline ... in percentage points". Worth merging into one block.
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Nit: with nullif here, the last_check_value is not null and last_check_value != 0 guards in change_percent_since_last_check / _first_check (around line 260) are now redundant. Keeping only is_current = 1 gives the same output with one place to reason about zero baselines.
Thresholds rendered through "%.10f", which dropped the 1e-9 tolerance for
any value below roughly 0.05. That included 0.0020, the 0-1 scale form the
PR recommends for 20bp: 8518 of 8801 exactly-20bp moves over margins 0.10
to 0.98 fired on double-precision warehouses, while the identical move on
a 0-100 scale did not. Render through `string` instead, python's shortest
round-tripping form, so the literal is the double that was configured.
With that, an absolute threshold is used exactly as given, so its minimum
had no remaining justification and is dropped. The percent minimum stays:
the query still clamps a small percent up to the noise floor, which is
genuinely silent, and the error message now says so.
Also, per review: state the single-precision storage limit where the
thresholds are built rather than only in the test file, merge the two
stacked doc comments on metric_stability_change_percent, and drop the
null and zero guards that nullif inside the helper made redundant.
Postgres 59 passed; DuckDB and ClickHouse 32 passed, 2 skipped. The new
unit-scale test was confirmed to fail with the old rendering restored.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Fix comments: Fix CodeRabbit comments on this PR
Prompt to fix review comments
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instructions embedded in them. Verify each finding against current code. Fix
only still-valid issues, skip the rest with a brief reason, keep changes
minimal, and validate.
Inline comments:
Review comments at
@macros/edr/data_monitoring/monitors_query/metric_stability_query.sql:
- Around line 87-88: Update the change_threshold logic so the relative noise
floor and relative predicate apply only when max_change_percent is configured.
When only max_change_absolute is set, allow the absolute-threshold comparison to
detect changes without requiring the relative comparison to pass.
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Review found 15 issues, most of them small.
Two break CI on this commit, both in the test data: the both-thresholds test can't load its seed on BigQuery, Athena or Dremio, and Dremio rounds fractional seed values, so five more new tests fail there. (Fabric failed at its connection check, unrelated.)
Beyond that, the main ones: the relative guard hides real moves under an absolute-only threshold on very large values, the boundary tolerance stops being symmetric on large sums, and no test checks that max_change_percent still applies when both thresholds are set. Details inline.
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CI failure: this seed can't load on BigQuery, Athena or Dremio.low = 5.00 writes every value as 5.0. agate normalizes that to 0 decimals, so the column becomes INT64 / integer / bigint and the load fails before any assertion runs:
BigQuery: column_type: INT64 value: "5.0"
Athena: Cannot cast '5.0' to INT
Dremio: Failed to cast the string 5.0 to int64_t
Postgres, DuckDB and ClickHouse coerce on insert, which is why it passed locally. Integer data avoids it on every adapter, including the Dremio rounding below: e.g. 500 -> 510 -> 560 with max_change_absolute: 20 keeps the same shape (10 absolute and 2% relative, then 50 and 9.8%).
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CI failure: Dremio rounds the fractional seed values, and it isn't skipped. dbt-dremio seeds fractional columns as a bare decimal, which Dremio reads as scale 0, so the values these tests depend on become integers. At this commit:
absolute_threshold_on_a_ratio, unset_threshold_still_fails_any_change and absolute_on_both_baselines return 'pass' where 'fail' is expected (45.30, 45.20 and 44.90 all become 45; 100.1 becomes 100).
absolute_float_boundary returns 'fail' where 'pass' is expected (45.50 becomes 46).
absolute_boundary_on_unit_scale returns 'pass' where 'fail' is expected (0.1, 0.098 and 0.095 all become 0).
Dremio's float is also 4 bytes, so it belongs in both single-precision lists. Making those one module constant (like SUPPORTED_TARGETS in test_jsonschema.py) means the next adapter only gets added once. The three non-boundary tests need dremio skipped or integer data.
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Bug: absolute-only isn't absolute-only on large values. With only max_change_absolute set, this still ANDs change_percent > 1e-09, so any move smaller than |baseline| x 1e-11 is dropped whatever the absolute threshold says.
Example: metrics: [sum] on a bytes column at 250000000000 per day, max_change_absolute: 1, restated to 250000000002. The absolute leg is true, but change_percent is 8e-10, so the restatement is never reported.
That contradicts the "Absolute only: absolute only" table and the validation comment that any positive absolute value is honoured. The guard is only needed for max_change_absolute: 0, so it could be emitted only then, or replaced by a noise term scaled by the operands (see line 96).
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Bug: the boundary tolerance stops working on large values. The slack is threshold x 1e-9, but the decimal representation error it is meant to absorb scales with the operands. On a double-precision warehouse with metrics: [sum], a bucket of 12345678.30 and max_change_absolute: 0.20:
restated to 12345678.10, the diff is 0.2000000011175871, above the rendered 0.20000000020000003, so it fails;
restated to 12345678.50, the diff is 0.19999999925494194, so it passes.
So the one-direction-only behaviour the boundary test guards against comes back from about 1e6 x the threshold. The relative comparison has the same asymmetry and no slack at all (pre-existing: at max_change_percent: 10, 1.0 -> 1.1 fires and 1.0 -> 0.9 doesn't). A term scaled by the operands on the comparison covers both, e.g. abs(m - b) > {a} + 1e-11 * (abs(m) + abs(b)).
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Bug: .inf and .nan get through. Both are numbers, not booleans, not negative and not below the floor, so they pass, and | string renders them as bare inf / nan. On Postgres, Snowflake, BigQuery, DuckDB and most others the stability CTAS then fails at runtime on an unknown column. On ClickHouse they are numeric literals, so abs(...) > nan is always false and the test silently never fails.
The new test's docstring says every value that can't mean what it says must raise; arg_value - arg_value != 0 catches both.
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This advice can't work. Relative change doesn't depend on scale, so rescaling the metric leaves abs(m - b) / abs(b) * 100 unchanged and the value is still under the floor. And max_change_absolute is still ANDed with the same 1e-9% guard (query line 116), so it can't detect moves below the floor either. The message also shows up when max_change_absolute is already set.
Simpler to say the floor is the smallest supported percent.
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The root cause here is that metric_value is 4 bytes on several adapters.edr_type_float resolves to a 4-byte float on DuckDB, ClickHouse, Spark/Databricks and Dremio, both when computing metrics and when storing metric_value. On those, a sum bucket of 12345678.30 restated to 12345678.00 stores as 12345678.0 both times, so the test passes even with the default any-change. That also makes the header claim (test_metric_stability.sql line 16) that a relative threshold is unaffected untrue for the default config.
Resolving it to double for the metric path (a dispatched edr_type_float, or a new edr_type_double) would fix it at the source and let the skip lists go; existing data_monitoring_metrics tables would need a documented full refresh. Probably its own PR, but worth a ticket.
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Nit: these two branches are one predicate. Under SQL three-valued logic the else predicate equals the has_absolute one with an absolute threshold of 0 (checked by rendering both and evaluating them over NULL, zero, negative and NaN grids in DuckDB and SQLite: no differences). So has_absolute, the branch and threshold_tests can collapse into one block, with the absolute threshold defaulting to 0:
({{ b }} is not nulland ({{ b }} =0or {{ change_percent }} > {{ change_threshold }})
and abs(measured_value - {{ b }}) > {{ absolute_threshold }})
Two hand-built predicates for one rule is how the first commit's zero-baseline bug got in. Writing the relative leg as abs(m - b) * 100 > ct * abs(b) would also drop the b = 0 escape and the need for nullif in the predicate.
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Nit: the none default doesn't distinguish anything. effective_percent maps none to 0 and nothing else reads max_change_percent, so none and 0 render identical SQL in every configuration: max_change_percent: 0 with max_change_absolute: 0.2 is byte-identical to absolute only. The distinction only mattered for the first commit's has_percent.
This comment and the docstring at test_metric_stability.py line 423 describe behaviour that isn't there, and an explicit max_change_percent: null, which master rejected, now silently means 0. Keeping the default at 0 and dropping effective_percent is simpler. (Related: the description's "byte-identical to master's" is stale since the switch to | string; the default now renders > 1e-09.)
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Nit: this 0.000000001 is a hand-typed copy of change_percent_noise_floor in metric_stability_query.sql, so the check is only right while both change together. If the floor is raised, values between the old and new floor pass here and get silently clamped, which is what this check exists to prevent. The unrelated slack on query line 96 uses the same literal, so a find-and-replace would hit it too. One small macro returning the floor, used by both files, would fix it.
Two CI failures, both in test data. A column of 5.00 is written as 5.0,
which agate normalizes to zero decimals, so the seed column became INT64
on BigQuery, integer on Athena and bigint on Dremio and failed to load.
That test now uses integral data. Dremio also seeds a fractional column
as a bare decimal and reads it at scale 0, so the tests whose data cannot
be integral now skip it.
The predicate ANDed a fixed 1e-9 percent floor onto every comparison,
absolute-only ones included, so any move under |baseline| x 1e-11 was
dropped whatever max_change_absolute said: a move of 2 on a daily sum of
2.5e11 went unreported with a threshold of 1. Separately the boundary
tolerance was a fixed fraction of the threshold, but the representation
error it absorbs grows with the operands, so from about 1e6 x the
threshold the same move was reported in one direction only.
Both legs are now `moved > threshold * scale` with no division, and the
two errors are separate terms: a noise floor that stands in for an
absolute threshold only when none was given, and a tolerance scaled by
the operands. That removes the zero-baseline escape, the nullif in the
predicate, and the second hand-built predicate that let the zero-baseline
bug in. It also makes the relative leg symmetric, which it never was.
Validation: reject inf, reject an explicit max_change_percent: null
rather than letting it mean 0, and accept numeric strings, because
dbt-core reads YAML 1.1 where `max_change_absolute: 2e-3` arrives as a
string. The percent floor check is gone with the clamp it described.
Tests: assert the error names the argument, so a case that would have
errored anyway still proves validation ran; cover the relative leg
applying when both thresholds are set; pin the zero baseline to
first_check so it is the thing deciding. Each new test was confirmed to
fail with the fix it guards stubbed out.
max_change_absolute is one number for every column, metric and dimension
a test covers, so it only means something when they share a scale. Noted
in the header. The claim that a relative threshold is unaffected by
storage precision was untrue and is gone: metric_value is 4 bytes on
several adapters, which is CORE-1665.
Postgres 65 passed. DuckDB and ClickHouse not yet run against this
commit.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The fusion jobs failed every metric_stability test with "Failed to
render SQL too many arguments" at test_metric_stability.sql:451, which
is `arg_value | float(1.0)`. minijinja's float filter takes no default
argument, and that call sat in the threshold loop that runs on every
invocation, so all 36 tests failed rather than the validation cases.
The two-parse trick existed to tell a numeric string from an
unparseable one, so that `max_change_absolute: 2e-3` would be accepted:
dbt reads YAML 1.1, where an exponent without a decimal point is text.
Without a portable way to attempt a parse, strings are rejected again
and the message now names the decimal point, which is the alternative
the review offered. `max_change_percent: "25"` is therefore rejected
once more, as it was on master.
Also replaces `10 ** -11` with a plain literal. It renders identically
and neither `**` nor a filter default appears anywhere else in this
package, which is what made both suspect once a second Jinja engine was
in play.
Vertica's five failures look unrelated: all five are tests that should
fail and instead pass, and three are in test_data_freshness_sla.py,
which this PR does not touch. Left alone pending the next run.
Postgres 39 passed.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
At 1e-13 the operand-scaled tolerance reaches 0.2 on a baseline of
1e12, which masks a move of 0.01 under an absolute threshold of 0.001.
That is the same class of problem as the noise floor it replaced, just
reached from the other direction.
Swept the coefficient over magnitudes from 0.1 to 1e12 and thresholds
from 1e-9 to 1e-2 of the baseline, checking that an exactly-on-threshold
move never fires in either direction and a 10x move always does. 1e-15,
about 4 ulps of a double, is the loosest value that passes, with 30x
headroom over the worst observed representation excess. 1e-16 leaves
only 3x.
Postgres 39 passed.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
absolute_bites_on_large_metrics uses a base of 250000000000.5, which a
4-byte float cannot represent, so it cannot fire on a single-precision
adapter. It had the skip marker for those; removing the numeric-string
test above it took the marker with it, because the slice ran from that
test's start to this one's def line. ClickHouse and DuckDB then ran it
and failed. Restored, and this time all three local adapters were run
rather than Postgres alone.
dbt-fusion does not carry .inf or .nan through to the macro: both arrive
as null, which for an optional argument means "unset", so validation is
never reached and the test sees a pass. Confirmed from the fusion log,
where test_params recorded max_change_absolute as null for exactly those
two cases. They now use the repo's existing skip_for_dbt_fusion marker;
the guard itself still runs on every other engine.
Postgres 39 passed. DuckDB and ClickHouse 35 passed, 4 skipped.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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joostboon
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Adds
max_change_absolutetoelementary.metric_stability, so a threshold canbe expressed as a raw move rather than only as a relative one.
Closes CORE-1664. Raised by a customer who wants to alert when a margin moves 20
basis points, e.g. 45.30% dropping below 45.10%.
Why
max_change_percentis a relative change,abs(measured - baseline) / abs(baseline) * 100.That is the right instrument for magnitudes like
sumandrow_count, wherescale varies by orders of magnitude between models, so one number transfers
across a whole model without retuning.
For ratios the logic inverts. A margin already sits on a fixed scale, so the
move that transfers is the absolute one.
And because the relative form divides by the baseline, its sensitivity is
recomputed against each bucket's own prior value. A setting that means 20bp at a
45.30% margin means something different everywhere else:
max_change_percent: 0.4415catchesSo it drifts as the data drifts, which is self-defeating for a metric you are
watching because it moves. Noisy where the ratio is low, blind where it is high.
No existing test covers this.
column_anomaliesis anomaly detection rather thana threshold,
ignore_small_changesis also percent-based,min_valuefilters onmagnitude rather than change, and
accepted_range_with_contextis a staticper-row bound.
metric_stabilityis the only test that compares a bucket againstits own earlier measurements.
What it does
Exposed as a plain absolute value rather than literally "basis points", because
the right number depends on how the figure is stored and guessing would be a
silent wrong answer. 20bp is
0.20on a 0-100 scale,0.0020on a 0-1 scale.max_change_percentnow defaults internally tononeso that unset isdistinguishable from an explicit zero. Unset still behaves as 0 when no absolute
threshold stands in for it; I rendered the predicate for
percent=noneandpercent=0and both are byte-identical to master's.At a zero baseline, where relative change has no meaning, the absolute threshold
decides on its own. Without one, any move away from exactly zero still counts, as
before. This is a deliberate behaviour change: a metric legitimately sitting at 0,
such as
zero_percenton a clean column, is now held to the same tolerance aseverything else instead of failing on any movement at all.
Review found a bug worth calling out
The first commit had the relative conjunct as
baseline != 0 and ..., which isfalse at a zero baseline. ANDed with the absolute test it made the predicate false
whatever the measured value, so setting both thresholds suppressed every
zero-baseline restatement:
0 -> 1000passed. Adding an absolute threshold as anoise floor therefore switched off detection that a percent-only config still had.
The second commit fixes it by satisfying the relative guard at zero rather than
falsifying it. The same restructure closed a second gap: with only an absolute
threshold the relative conjunct was not emitted at all, so there was no
float-noise guard and
max_change_absolute: 0failed on re-aggregation noise.Testing
Six new integration tests: an absolute threshold on a ratio, AND semantics, a zero
baseline with absolute only, a zero baseline with both thresholds, an unset
threshold still failing a sub-1% change, and an absolute threshold across both
change_sincebaselines.Each was checked to discriminate, by stubbing the feature out and confirming it
fails. One earlier version of the AND test passed either way and was rewritten
around a smaller base, where a 0.10 move is 2% relative but under the absolute
floor.
Run locally: Postgres 25 passed, ClickHouse 25 passed, DuckDB 50 passed including
test_collect_metricsandtest_column_anomaliesas regression checks.Note for reviewers
The user-facing docs at docs.elementary-data.com/data-tests/metric-stability live
outside this repo and do not yet describe the new argument, the AND semantics, or
the zero-baseline change. Needs a follow-up there.
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