SHOW SNOWFLAKE.ML.ANOMALY_DETECTION¶
Lists all anomaly detection models.
SHOW SNOWFLAKE.ML.ANOMALY_DETECTION INSTANCES is an alias for SHOW SNOWFLAKE.ML.ANOMALY_DETECTION.
Syntax¶
{
SHOW SNOWFLAKE.ML.ANOMALY_DETECTION |
SHOW SNOWFLAKE.ML.ANOMALY_DETECTION INSTANCES
}
[ LIKE <pattern> ]
[ IN
{
ACCOUNT |
DATABASE |
DATABASE <database_name> |
SCHEMA |
SCHEMA <schema_name> |
<schema_name>
}
]
Parameters¶
LIKE 'pattern'
Optionally filters the command output by object name. The filter uses case-insensitive pattern matching, with support for SQL wildcard characters (
%
and_
).For example, the following patterns return the same results:
... LIKE '%testing%' ...
... LIKE '%TESTING%' ...
. Default: No value (no filtering is applied to the output).
[ IN ... ]
Optionally specifies the scope of the command. Specify one of the following:
ACCOUNT
Returns records for the entire account.
DATABASE
, .DATABASE db_name
Returns records for the current database in use or for a specified database (
db_name
).If you specify
DATABASE
withoutdb_name
and no database is in use, the keyword has no effect on the output.SCHEMA
, .SCHEMA schema_name
, .schema_name
Returns records for the current schema in use or a specified schema (
schema_name
).SCHEMA
is optional if a database is in use or if you specify the fully qualifiedschema_name
(for example,db.schema
).If no database is in use, specifying
SCHEMA
has no effect on the output.
Default: Depends on whether the session currently has a database in use:
Database:
DATABASE
is the default (that is, the command returns the objects you have privileges to view in the database).No database:
ACCOUNT
is the default (that is, the command returns the objects you have privileges to view in your account).
Usage notes¶
The order of results is not guaranteed.
Output¶
Model properties and metadata in the following columns:
Column |
Description |
---|---|
created_on |
Date and time when the model was created |
name |
Name of the model |
database_name |
Database in which the model is stored |
schema_name |
Schema in which the model is stored |
current_version |
The version of the model algorithm |
comment |
Comment for the model |
owner |
The role that owns the model |
Examples¶
For a representative example, see the anomaly detection example.