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This error occurs when you attempt to create or update a dataset, access rule, or view with a unique_name that conflicts with an existing resource. Datasets, access rules, and views all share a single namespace — NQL does not distinguish between them — so unique_name must be unique across all three resource types.

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Error response

{
  "type": "https://docs.narrative.io/reference/errors/access-rule-name-conflict",
  "title": "Access rule, table, or view already exists",
  "status": 409,
  "detail": "An access rule, table, or view with the name '<name>' already exists.",
  "instance": "/api/...",
  "logId": "unique-error-identifier"
}

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When this occurs

You receive this error when creating or renaming any of the following and the chosen unique_name is already in use:
  • Dataset — A new or renamed dataset conflicts with an existing dataset, access rule, or view
  • Access rule — A new or renamed access rule conflicts with an existing dataset, access rule, or view
  • View — A new or renamed view conflicts with an existing dataset, access rule, or view
The conflict can occur across resource types. For example, creating an access rule named customer_events will fail if a dataset or view with that name already exists.

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How to resolve

  1. Check the detail field — It identifies the conflicting name
  2. Choose a unique name — Pick a unique_name that doesn’t conflict with any existing dataset, access rule, or view
  3. Check for cross-type conflicts — If the name looks unfamiliar, the conflict may be with a different resource type (e.g., a dataset blocking an access rule name)
  4. Update instead of create — If you intended to modify an existing resource, use the update endpoint with the correct resource ID instead of creating a new one
Because NQL uses unique_name to reference datasets, access rules, and views interchangeably, all three share a single namespace. A name used by any one of them cannot be reused by the others.

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Related content

Access Rules

Understand how access rules control data access

Datasets

Understand dataset schemas and structure

Error Reference

Overview of common API errors