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A scheduled audit job can succeed on every run and still repeat the same work indefinitely if it selects a record using one URL string but saves the result under another. That is what Juan Camilo Auriti says happened in his database: a redirect and URL normalization turned example.com into example.com/, and the unique index treated the two strings as different keys.
How a successful audit loop kept repeating
Auriti describes a job that selected a domain using the URL spelling already stored in a row, then followed redirects and normalized the URL while performing the audit. The audit result was saved using that normalized spelling. When the job ran again, it looked for the original spelling, did not find the result under that key, and performed the audit again.
Nothing had to fail for the problem to persist: according to Auriti, each audit completed without an error. The loop did not converge because it read by one key and wrote by another. In his words, “The loop simply never converged, because the key it read by and the key it wrote by were never the same key.”
His question for diagnosing this kind of behavior is direct: “is the key I select by byte-identical to the key I write by?” Checking only whether a job is erroring, or whether each individual run reports success, will not answer it.
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Why the unique index did not prevent duplicates
A unique index enforces uniqueness on the values it receives. If it receives example.com in one operation and example.com/ in another, those are distinct strings. The database cannot infer that the application intends them to identify the same resource.
That distinction is the heart of the incident: uniqueness on raw strings is not the same as uniqueness on a deliberately canonicalized URL. A constraint can prevent duplicates only when the application applies the same key policy before both checking and storing a record.
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What the incident figures mean
Auriti reports that one affected domain had 1,831 audit rows, where he expected a few dozen. After the backfill he describes, that domain had 19 rows. He also reports that 86.9% of the table’s audit rows were attributable to the issue. These are figures from the author’s account of his own incident, not an independent audit or a general statistic about databases. Read Auriti’s account on DEV Community.
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Auriti’s example normalizer applies a specific set of rules: it trims surrounding whitespace, adds https:// when an input has no scheme, parses the URL, lowercases the scheme and host, removes a leading www., drops default ports 80 and 443, and removes trailing path slashes while preserving / for the root path.
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Adding a scheme before parsing matters for bare hostnames. Without it, a URL parser may treat the input as a path rather than identifying a hostname. The example also preserves a root path by using rstrip("/") or "/", rather than turning / into an empty path.
Those operations are policy decisions, not universal URL rules:
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- Removing
www.assumes that the bare host and thewwwhost represent the same entity. Some applications may need to keep them distinct. - Removing a trailing slash from a path assumes that
/aboutand/about/identify the same resource. That is not guaranteed for every site or application. - Scheme, port, host, and path treatment should reflect what your application considers equivalent, rather than being copied as a blanket rule.
Use a normalizer designed for your application’s equivalence policy; the example described by Auriti is not a complete, universal URL canonicalizer.
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Normalize at the boundary where an input URL becomes a record, before uniqueness checks and persistence. The same canonical key must then be used wherever the application selects, updates, or inserts that record. If only the write path normalizes, or only the scheduled job normalizes, the mismatch can remain.
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Before enforcing uniqueness on a canonical key, account for existing records that will collapse to the same value. Normalizing them can create collisions that did not exist among the original strings. Auriti’s described cleanup normalized existing rows, merged collisions, kept the earliest created_at, and retained the most recent result. Those choices form a merge policy; another application may need different rules for history, ownership, or audit results.
Find suspicious URL-key groups
Auriti offers a quick SQL diagnostic that groups values after lowercasing and trimming trailing slashes, then looks for groups with multiple raw spellings. Adapt it to your database’s SQL dialect and your actual canonicalization rules; this simplified grouping does not account for every rule in his normalizer, such as schemes, ports, or www..
SELECT lower(rtrim(url, '/')) AS grouped_url,
COUNT(DISTINCT url) AS raw_spellings,
COUNT(*) AS total_rows
FROM audit_rows
GROUP BY lower(rtrim(url, '/'))
HAVING COUNT(DISTINCT url) > 1;Use the results to inspect both the raw values and the records they represent before merging anything. The query identifies possible spelling groups under its limited rule; it does not prove that every grouped URL refers to the same resource.
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For a URL-backed record, evaluate the key strategy against the decisions that affect identity and maintenance:
Quick Recap
- Equivalence policy: Decide explicitly how scheme, host casing,
www, default ports, and path slashes affect identity. - Boundary consistency: Confirm the same normalization is used before selection, uniqueness checks, insertion, and updates.
- Collision handling: Define what happens when a backfill maps multiple existing rows to one canonical key, including which metadata and results survive.
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