Name the thing represented by each row
A fill record and a benchmark-quote observation describe different things. One fill can be associated with several quotes for comparison, but those associations do not create extra fills. Preserve a scoped fill identifier and a separate reference for every benchmark annotation.
A joined table can produce a result row for each matching pair. That is useful when the question concerns pairwise comparisons. It becomes misleading if a later average is described as one observation per execution while some fills appear more often than others.
Compare two fictional averages with different weighting
Suppose fill A has a supplied cost observation of 1 quote unit and fill B has 3 quote units. The unweighted mean over those two fill-level observations is 2. Now imagine A has three benchmark annotations and B has one, so a joined view repeats A’s cost three times.
A naive average of the joined cost column is (1+1+1+3)/4 = 1.5. Neither fill’s original cost changed. The altered mean is a consequence of repeated weighting, and it should not be presented as an improvement in actual execution quality.
| Teaching representation | Values averaged | Mean |
|---|---|---|
| Two fill-level observations | 1, 3 | 2 quote units |
| Joined annotation rows | 1, 1, 1, 3 | 1.5 quote units |
| Actual execution change | No new fill supplied | Not established |
Choose the aggregation rule before reading the attractive subtotal
If the goal is a fill-level summary, retain one declared observation per fill or use an explicitly documented aggregation of its annotations. If the goal is a quote-pair study, name that unit and explain its weighting. Do not switch between the two after comparing the totals.
A count of distinct identifiers is not enough when identifiers have only local scope or an export omits part of the source key. Preserve account, product and source scope where required, while keeping private identifiers out of public reports. Unmatched or ambiguous relationships should remain visible.
Distinguish accidental repetition from an explicitly chosen weight
Another study might deliberately use quantity weights, but it should say so and use a measure with compatible units. For hypothetical per-unit cost observations 1 and 3, quantities 1 and 3 would yield a quantity-weighted mean of 2.5 in the chosen cost-per-unit measure. That is a different question from an equal-weight fill mean of 2. Neither is reproduced by accidentally repeating A three times in a join. Document the observation unit, weight and denominator together.
Keep currency and interpretation outside the join arithmetic
A Singapore reporting view may include SGD valuations, but all values in a single average must first have comparable units and timing. A repeated row cannot be fixed by changing its currency label. Likewise, benchmark selection and the sign of a cost measure need their own definitions.
This case demonstrates a data-joining effect with fictional numbers. It does not validate a benchmark, authenticate a fill or rank an execution provider. A good result reports the observation unit, annotation counts and unresolved relationships alongside the chosen statistic.
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Primary sources and scope
- PostgreSQL documentation: Table Expressions
A join can produce one result row for each matching pair. The example illustrates duplicate weighting; no private database is queried. Checked 2026-10-21. - NIST/SEMATECH: Measures of Location
Arithmetic mean uses the sum divided by the count of observations. The worked cases here are invented, not evidence of performance. Checked 2026-10-21.