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SHOW VOLUMES

Applies to: check marked yes Databricks SQL check marked yes Databricks Runtime 13.3 LTS and above check marked yes Unity Catalog only

Lists all the volumes accessible to the current user in the current or optionally specified schema. Additionally, the output of this statement may be filtered by an optional matching pattern.

Syntax

SHOW VOLUMES [ { FROM | IN } schema_name ] [ [ LIKE ] regex_pattern } ]

Parameters

  • schema_name

    Specifies the schema in which volumes are to be listed.

  • regex_pattern

    A STRING literal with a regular expression pattern that is used to filter the results of the statement.

    • Except for * and | character, the pattern works like a regular expression.
    • * alone matches 0 or more characters and | is used to separate multiple different regular expressions, any of which can match.
    • The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.

Returns

A result-set with two columns:

  • database STRING NOT NULL: The schema of the volume
  • volumeName STRING NOT NULL: The name of the volume

Examples

– List all volumes accessible by the caller
> SHOW VOLUMES
  database         volumeName
  ---------------- ----------
  default          my_external_volume
  default          another_volume
  default          foo_volume

– List all volumes under schema `machine_learning`
> SHOW VOLUMES IN machine_learning
  database         volumeName
  ---------------- ----------
  machine_learning bar_volume

– List all volumes whose name starts with 'a'
> SHOW VOLUMES LIKE 'a*'
  database         volumeName
  ---------------- ----------
  default          another_volume

Additional resources

Training

Module

Use system catalogs and system views in PostgreSQL - Training

Relational databases can store vast quantities of data, but they also need to hold information about the structure of that data. For an operational database management system (DBMS) information about the structure of tables, and all other objects, security, and concurrency, amongst many other settings and metrics, is required. This information is know as metadata and is stored in system catalogs in Azure Database for PostgreSQL. In addition to directly accessing system catalogs, you can access system views