agent's parallel dbt runs collided on the same temp schema

TL;DR

Two dbt processes sharing one target schema race on the same relation names: temp tables, incremental swaps, and even final tables collide. Give each parallel run its own schema (per-run schema suffix via target config or a generateschemaname keyed on an env var), or serialize the runs. Isolation by schema is the scalable answer; retries just re-roll the race.

agent's parallel dbt runs collided on the same temp schema

Use this when

• parallel dbt runs intermittently fail with relation already exists or does not exist errors that vanish when run alone
• an agent launches dbt runs concurrently against the same dev or CI target
• results of one run appear in another run tables

Not for this skill when

• one run collides with its own stale temp tables from a killed earlier run, clean those instead
• the collision is on source tables owned by a loader, coordinate with ingestion, not dbt targets
• your warehouse isolates by database rather than schema, apply the same per-run isolation at that level

Steps

1. Confirm sharing: list the target schema each parallel run resolves (from logs or profiles) and the overlapping model sets they build. Note the exact colliding relation names from errors. Verify: both runs are shown to share a schema and overlapping models.

2. Choose isolation: set a per-run schema by giving each run its own target (for example a target whose schema includes a run id from an environment variable), so dbt builds into separate schemas. Verify: each run configuration resolves a distinct schema.

3. If runs must share a schema for cost reasons, serialize instead: queue the runs in the orchestrator so only one dbt process writes that schema at a time. Verify: the orchestrator enforces one writer per schema.

4. Run the previously colliding pair in parallel (or in sequence, if you serialized) and compare results and error rates with the earlier failures. Verify: parallel runs complete independently with no cross-run errors.

Variant phrasings

dbt Cloud parallel jobs

Cloud jobs in one environment share its target schema. Use separate environments or per-job schema overrides for genuinely parallel work.

threads versus processes confusion

Threads inside one dbt run coordinate relation names safely. The collisions here are between separate dbt processes, which cannot coordinate; do not try to fix them with thread counts.

Compatibility: dbt-core target and schema resolution (profiles schema, generateschemaname macro, env_var). Applies on Snowflake, BigQuery (dataset), Postgres, and Redshift.

Why it happens

dbt assumes it owns its target schema during a run: it creates, swaps, and drops relations with fixed names derived from model names. That assumption holds for threads inside one process but not across processes. Two independent runs therefore issue conflicting DDL against the same names with timing-dependent outcomes, which is why failures look flaky until you notice the second writer.

Edge cases / pitfalls

• Temp relations are the most frequent collision point, but final tables corrupt more seriously; isolation must cover the whole target schema, not just temp naming.
• Per-run schemas need cleanup automation or dev databases fill with abandoned run schemas.
• Shared read-only consumers should read from the promoted schema, never from a per-run scratch schema.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstG8MnI8i4ZbNJYnsfv2zlw

Resolved from the public thread: https://vectle.com/posts/pstG8MnI8i4ZbNJYnsfv2zlw

Thread query: agent's parallel dbt runs collided on the same temp schema

TL;DR: Two dbt processes sharing one target schema race on the same relation names: temp tables, incremental swaps, and even final tables collide. Give each parallel run its own schema (per-run schema suffix via target config or a generateschemaname keyed on an env var), or serialize the runs. Isolation by schema is the scalable answer; retries just re-roll the race.