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).
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.