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Graph/race-prone-id-allocation

Pattern

Race-Prone ID Allocation

race-prone-id-allocation

ID selection and updates behave incorrectly under concurrency because mutations and pre-allocation happen out of order, so range/composite-key assumptions and “pick first N” SQL patterns target the wrong rows. Reproducibility breaks and state becomes corrupted.

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Updated7/3/2026

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30 linked nodes

one failed write aborted the rest of the batch — structured post-turn extraction wrote events and beliefs without per-entry error isolation. Outcome: leaving future event inserts vulnerable once the initial partition window expired.

I can get the same performance issues with either a select or a delete — they join two tables, and none of the join conditions compares using `=`. Tension: `IS NOT DISTINCT FROM` is not supported by indexes, and `OR` is usually a performance problem anyway. Outcome: the root of your problem are the NULL values.

parallel workers sometimes grab overlapping sets, then wait to mark them as being processed — At the time of item selection, you neither lock them nor check whether they're locked. Tension: someone else could've already grabbed a subset of those. Outcome: duplicate their work on the items they happened to share.

after a few hundred requests. Tension: inconsistent responses mostly happen during concurrent requests for the same user ID.

An idempotency test reused a pre-built node array and passed even when the id-builder was made non-deterministic

related_player_id 12 non-null float64 — trying to load it to a Postgres database. Tension: This has been fine for most of the tables, but the final assignment table is causing me problems. Outcome: bigint out of range.

A PostgreSQL query uses a CTE to select the old session_id and then performs an INSERT ... ON CONFLICT DO UPDATE, returning the CTE’s result as the previous value. The user needs to know whether PostgreSQL guarantees the CTE is evaluated before the INSERT/UPDATE so the returned value is correct.

heavy parallel inserts (INSERT INTO ... SELECT ...) could slow down due to SEQUENCE contention — in Greenplum, SEQUENCE is managed globally by the master node. Tension: multiple segments request new IDs in parallel.

sequence [ID_SEQ] defined inconsistent increment-size; found [1] but expecting [100] — Quarkus postgres and liquibase. Tension: those values are inconsistent. Outcome: You have to annotate fields(ex: id) with `sequenceGenerator` not the Entity or class.

The same code can be run in parallel in multiple threads, or even in multiple Kubernetes pods — DELETE FROM my_table WHERE ctid IN ( SELECT ctid FROM my_table WHERE some_condition LIMIT 1 ). Tension: two threads start fighting for the same record.

"too many range table entries" error — I'm trying to update a partitioned PostgreSQL table using a PL/pgsql loop. Tension: it contains a self join on a large table. Outcome: If I hardcode the partition to update in the WHERE clauses, it works just fine.

ERROR: insert or update on table "course_content" violates foreign key constraint "coursedetail_fk" — INSERT INTO Course_Content(id, section_title) values (id, 'A pretty awesome crash course');. Tension: Key (id)=(1) is not present in table "course_detail". Outcome: Adding this extra column allows the id to point to whatever and not be constrained by the rules of the `SERIAL` data type.

Maintain a contiguous ordering in a PostgreSQL table when inserting or deleting rows by an integer column (e.g., questionOrder), such that items at/after a position shift appropriately.

Attempting to use UNNEST on multiple TEXT[] arrays to insert array elements as rows into a table results in misaligned values across columns. The inserted data ends up shifted (e.g., id/name/phone values come from different arrays).

you run the risk of getting duplicates — As several comments to your question pointed out. Tension: This will currently not generate an error because you do not have an appropriate constraint on your table. Outcome: Avoiding duplicates requires a table constraint.

Implementing cursor-based pagination in Knex/Postgres using a tuple comparison like `(timestamp, id) > (cursor.timestamp, cursor.id)` fails and returns no rows. The attempted Knex query with two separate `where` clauses behaves like an `AND` comparison rather than the intended tuple `>` semantics.

Trying to find an equivalent in PostgreSQL/EDB for Oracle's ROWID pseudocolumn to uniquely identify a row and use it in queries.

Software actually aliasing NS and S accesses for RAMs means you can end up with two non-coherent copies of the same data in the caches — secure and non-secure data to be distinguished in caches. Tension: which can desync because of the lack of coherency. Outcome: This is why secure world page tables can be set up with NS=1 pages.

stack layout and register allocation are subject to a great amount of optimization — An attempt to interfere this process nondeterministically. Tension: benchmarks will become useless. Outcome: nondeterministic performance.

I get a duplicate ID error — If I create a Person first and then try to create a PersonExtra with an existing Person's ID. Tension: it tries to persist both Person and PersonExtra.

those polls might be scheduled in parallel — make this concurrent. Tension: there is no ordering guarantee.

Spring JPA fails when executing an UPDATE on the Oracle table, throwing “Unable to bind parameter #7 - Invalid column index”.

with batching solution, I introduce a new problem with sorting & paginating on Java side — If let's say I get 4000 viewerIds. Tension: I would have to sort them again.

Using a single @SequenceGenerator definition in a mapped superclass causes Product and Order entities to share the same database sequence, so ids are generated from the same sequence. The goal is to have separate sequence names per entity without relying on Hibernate-specific generator classes.

This happens only when in create a "Release" build, not for "Debug " builds. — when heap-allocating (`new bool`, `make_unique`, ...) but not when stack-allocating in the same location. Tension: I was not able to reduce the code the code any further. Outcome: The code exhibits undefined behavior.

what are the correct values of three highlighted parameters? — when it comes to intrusive lockless stacks (single-linked lists). Tension: I've seen various permutations of highlighted parameters. Outcome: I understand it doesn't matter on x86, but it is nice to do things right...

Dynamic memory allocation is ill-advised in any event in most small scale and real-time embedded applications — in most small scale and real-time embedded applications. Tension: non-deterministic timing, the need to deal with the potential for failure and memory exhaustion. Outcome: particularly ill-advised in (and generally prohibited) safety critical systems.

runtime updates looked up rows by id only — After converting a memory events table to range partitioning by occurred_at. Tension: review found two production risks.

parent INSERT and the findings INSERT must be in the same transaction — existing public/staff Hono routes that previously wrote raw user input directly to Postgres. Outcome: route handlers blow up with "values is not a function" during tests.

naive optimistic updates either (a) flicker because the next server [REDACTED]shot wipes them or (b) get stuck because you can't — In a server-authoritative realtime app (game tick, collaborative doc). Tension: the next server [REDACTED]shot wipes them. Outcome: Switching to derive-from-[REDACTED]+[REDACTED] made the whole thing trivially correct.

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