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Graph/scalar-return-multirow-mismatch

AntiPattern

Scalar Return Misuse

scalar-return-multirow-mismatch

A recurring SQL/PLpgSQL motif where a function declared to return a scalar (single int) is implemented with logic that can yield multiple rows/columns, causing runtime errors and forcing set-based rewrites or query-shape fixes.

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Updated5/1/2026

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30 linked nodes

MATCHESSolution

You can get rid of this TypeScript issue by casting the column definition arrays — when defining columns.

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You want to use the "NULL AS" parameter to COPY. — If you really need to distinguish between ,, and ,"",. Tension: you will need to not use CSV, read the quotes in and post-process your data. Outcome: "NULL AS" is likely the easier path.

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you can use type overrides as suggested in related issue #309 — Composite and record types aren't yet supported by `sqlc`. Outcome: you can aggregate the table record types directly into an `item[]` field.

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More complex, multi-statement queries, or things like `insert..on conflict` and `merge`.

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An alternative is to create a temporary function — if you have the `TEMP` privilege on the database. Tension: You have to call the function with the schema name. Outcome: CREATE FUNCTION pg_temp.pk_get_date() RETURNS date.

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Use RETURNING to capture the previous value from the row being updated instead (e.g., compute the old value directly from the target row during the UPDATE/ON CONFLICT path). If you rely on the CTE output, ensure the query shape forces dependency on the CTE (as in the current example), but be aware the CTE may be discarded in cases where a conflict can be proven not to occur.

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You need dynamic SQL to do this properly. — in PostgreSQL, I am trying to have SQL which orders by multiple columns. Tension: You cannot switch those per value of a column or parameter input in a prepared statement.

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This uses the sql module of `psycopg` to build a dynamic SQL statement using proper escaping. — inside a `DO`.

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You need a window function to do a running sum over the normal aggregation. — select count(distinct mt.customer) as count. Outcome: sum(count(distinct mt.customer)) over (order by mt.enrollment_dt rows unbounded preceding) as running_count.

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Cast the function result to jsonb when calling jsonb_path_query(), e.g. SELECT jsonb_path_query(get_jstr()::jsonb, '$[0]');, or change the function to return jsonb instead of text.

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Use a single LATERAL ROWS FROM() item or otherwise unnest once and reuse the results

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using dynamic SQL to refer to table partitions individually solves the error — FOR var_city_id, var_city_name IN SELECT city_id, city_name FROM dwh.city. Tension: I thought those two practically did the same thing. Outcome: EXECUTE 'UPDATE dwh.residence_' || var_city_name || ' res1.

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Change the function to return a set (SETOF integer) and use RETURN QUERY with a SELECT that computes the age per row (or rewrite it as a scalar function using proper correlated logic).

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I am trying to create a generated always column that takes the Current Date, subtract the previously mentioned int column to get an Age (int). — I am trying to learn Postgresql (12) "on the job" and seem to be stuck on a rather simple issue. Tension: the logic is faulty in that the `asset_age` is calculated when the row is inserted in the table or its underlying columns updated so as time moves on your asset ages go out of sync. Outcome: You can most easily solve your issue by dropping column `asset_age` from your table and create a view that calculates the value whenever you need it:.

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Insert rows by constructing one array per row and selecting its elements by index (e.g., using a VALUES list of arrays and then selecting a[1], a[2], a[3] for each row).

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Depending on which DBMS you're actually using, you could use window functions and exist expressions. — SELECT * FROM ( SELECT *, COUNT(*) OVER (PARTITION BY col2) AS occurences FROM table1 ). Tension: where col2 = t1.col2. Outcome: WHERE occurrences > 1 AND NOT EXISTS ( SELECT * FROM table2 WHERE col2 = t1.col2 ).

MATCHESSolution

Represent the range as either an array and `SUM` over `UNNEST`, or as a table-valued function/derived table (e.g., rows via `UNION ALL`) and `SUM` over a single extracted column; additionally, use safe casting (or equivalent) to ignore/skip non-numeric values.

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Define a composite type (e.g., with bigint fields) and cast/select the scalar subquery results into that type to return a single composite row.

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Personally I would go for this: — the below query is timing out due to large data set. Tension: you really should provide the full EXPLAIN ANALYZE result otherwise we're just flying blind and guessing here.

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Use PERFORM with the CTE in the documented form: wrap the WITH query in parentheses as a FROM-subquery (e.g., `PERFORM * FROM (WITH test_as_cte AS (SELECT * FROM myTable) SELECT * FROM test_as_cte) sub;`). This allows executing the query while discarding the result even with multiple columns.

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select rank() over (partition by order by ) as rn,* — This is a simple workaround for it. Outcome: as rn,* from ;.

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you should check for that — If there are no rows at all to insert. Outcome: A Table-Valued Parameter or a bulk insert into a temp table are therefore both better options.

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Avoid `select('*')` and instead explicitly select only the allowed columns (e.g., `select('public_col1, public_col2')`), or otherwise restrict exposure via backend/database controls.

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using `exit` within the loop is unnecessary. — since you've set `... LIMIT 1` in your `SQL` query. Tension: you expect at most one result. Outcome: an `if` check is more appropriate than a `while` loop.

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Dynamic SQL table column names from the form is not the best approach. — for `form.ID` you should use ``, this will prevent any sql injection attempts. Tension: But if you must, then I would create a map structure which controls the values which are finally rendered in the original query. Outcome: Still, I recommend using proper column names instead of a dynamic variable.

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Or you can increment value in one query — for READ_COMMITTED. Tension: There are solutions for READ_COMMITTED:.

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Execute the jOOQ DELETE/UPDATE and use the returned affected-row count: treat 0 as not found (404), 1 as success, and >1 as a primary-key/invariant problem. Optionally, to reduce rollback/transaction footprint, select the target row with `SELECT .. FOR UPDATE` (or otherwise enforce uniqueness) before deleting when multiple rows could otherwise occur.

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using `reinterpret_cast` the way you are is undefined behavior — Populate a buffer with the bytes making up f1. Tension: No reinterpret_cast, no undefined behavior. Outcome: Populate f2 with the content of the buffer.

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Re-export int from neo4j-driver (as neo4jInt) from the graph package barrel — In tool handlers, wrap all Cypher integer params. Tension: Apply to LIMIT, maxLevel, and any other integer-typed Cypher parameter. Outcome: Alternatively, use neo4j-driver's int() directly if the package is a dependency.

MATCHESSolution

What relationships actually exist? — MATCH ()-[r]->() RETURN type(r), count(r) ORDER BY count(r) DESC. Tension: What your projection expects vs what exists. Outcome: check your projection.

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