CREATE FUNCTION

Creates a new UDF (user-defined function). Depending on how you configure it, the function can return either scalar results or tabular results.

When you create a UDF, you specify a handler whose code is written in one of the supported languages. Depending on the handler’s language, you can either include the handler source code in-line with the CREATE FUNCTION statement or reference the handler’s location from CREATE FUNCTION, where the handler is precompiled or source code on a stage.

The following table lists each of the supported languages and whether its code may be kept in-line with CREATE FUNCTION or kept on a stage. For more information, see Keeping handler code in-line or on a stage.

Language

Handler Location

Java

In-line or staged

JavaScript

In-line

Python

In-line or staged

Scala

In-line or staged

SQL

In-line

This command supports the following variants:

See also:

ALTER FUNCTION, DROP FUNCTION, SHOW USER FUNCTIONS , DESCRIBE FUNCTION, CREATE OR ALTER <object>

Syntax

The syntax for CREATE FUNCTION varies depending on which language you’re using as the UDF handler.

Java handler

Use the syntax below if the source code is in-line:

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] FUNCTION [ IF NOT EXISTS ] <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS { <result_data_type> | TABLE ( <col_name> <col_data_type> [ , ... ] ) }
  [ [ NOT ] NULL ]
  LANGUAGE JAVA
  [ { CALLED ON NULL INPUT | { RETURNS NULL ON NULL INPUT | STRICT } } ]
  [ { VOLATILE | IMMUTABLE } ]
  [ RUNTIME_VERSION = <java_jdk_version> ]
  [ COMMENT = '<string_literal>' ]
  [ IMPORTS = ( '<stage_path_and_file_name_to_read>' [ , ... ] ) ]
  [ PACKAGES = ( '<package_name_and_version>' [ , ... ] ) ]
  HANDLER = '<path_to_method>'
  [ EXTERNAL_ACCESS_INTEGRATIONS = ( <name_of_integration> [ , ... ] ) ]
  [ SECRETS = ('<secret_variable_name>' = <secret_name> [ , ... ] ) ]
  [ TARGET_PATH = '<stage_path_and_file_name_to_write>' ]
  AS '<function_definition>'
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Use the following syntax if the handler code will be referenced on a stage (such as in a JAR):

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] FUNCTION [ IF NOT EXISTS ] <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS { <result_data_type> | TABLE ( <col_name> <col_data_type> [ , ... ] ) }
  [ [ NOT ] NULL ]
  LANGUAGE JAVA
  [ { CALLED ON NULL INPUT | { RETURNS NULL ON NULL INPUT | STRICT } } ]
  [ { VOLATILE | IMMUTABLE } ]
  [ RUNTIME_VERSION = <java_jdk_version> ]
  [ COMMENT = '<string_literal>' ]
  IMPORTS = ( '<stage_path_and_file_name_to_read>' [ , ... ] )
  HANDLER = '<path_to_method>'
  [ EXTERNAL_ACCESS_INTEGRATIONS = ( <name_of_integration> [ , ... ] ) ]
  [ SECRETS = ('<secret_variable_name>' = <secret_name> [ , ... ] ) ]
Copy

JavaScript handler

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] FUNCTION <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS { <result_data_type> | TABLE ( <col_name> <col_data_type> [ , ... ] ) }
  [ [ NOT ] NULL ]
  LANGUAGE JAVASCRIPT
  [ { CALLED ON NULL INPUT | { RETURNS NULL ON NULL INPUT | STRICT } } ]
  [ { VOLATILE | IMMUTABLE } ]
  [ COMMENT = '<string_literal>' ]
  AS '<function_definition>'
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Python handler

Use the syntax below if the source code is in-line:

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] [ AGGREGATE ] FUNCTION [ IF NOT EXISTS ] <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS { <result_data_type> | TABLE ( <col_name> <col_data_type> [ , ... ] ) }
  [ [ NOT ] NULL ]
  LANGUAGE PYTHON
  [ { CALLED ON NULL INPUT | { RETURNS NULL ON NULL INPUT | STRICT } } ]
  [ { VOLATILE | IMMUTABLE } ]
  RUNTIME_VERSION = <python_version>
  [ COMMENT = '<string_literal>' ]
  [ IMPORTS = ( '<stage_path_and_file_name_to_read>' [ , ... ] ) ]
  [ PACKAGES = ( '<package_name>[==<version>]' [ , ... ] ) ]
  [ ARTIFACT_REPOSITORY = '<repository_name>' ]
  HANDLER = '<function_name>'
  [ EXTERNAL_ACCESS_INTEGRATIONS = ( <name_of_integration> [ , ... ] ) ]
  [ SECRETS = ('<secret_variable_name>' = <secret_name> [ , ... ] ) ]
  AS '<function_definition>'
Copy

Use the following syntax if the handler code will be referenced on a stage (such as in a module):

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] [ AGGREGATE ] FUNCTION [ IF NOT EXISTS ] <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS { <result_data_type> | TABLE ( <col_name> <col_data_type> [ , ... ] ) }
  [ [ NOT ] NULL ]
  LANGUAGE PYTHON
  [ { CALLED ON NULL INPUT | { RETURNS NULL ON NULL INPUT | STRICT } } ]
  [ { VOLATILE | IMMUTABLE } ]
  RUNTIME_VERSION = <python_version>
  [ COMMENT = '<string_literal>' ]
  [ ARTIFACT_REPOSITORY = '<repository_name>' ]
  IMPORTS = ( '<stage_path_and_file_name_to_read>' [ , ... ] )
  [ PACKAGES = ( '<package_name>[==<version>]' [ , ... ] ) ]
  HANDLER = '<module_file_name>.<function_name>'
  [ EXTERNAL_ACCESS_INTEGRATIONS = ( <name_of_integration> [ , ... ] ) ]
  [ SECRETS = ('<secret_variable_name>' = <secret_name> [ , ... ] ) ]
Copy

Scala handler

Use the syntax below if the source code is in-line:

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] FUNCTION [ IF NOT EXISTS ] <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS <result_data_type>
  [ [ NOT ] NULL ]
  LANGUAGE SCALA
  [ { CALLED ON NULL INPUT | { RETURNS NULL ON NULL INPUT | STRICT } } ]
  [ { VOLATILE | IMMUTABLE } ]
  [ RUNTIME_VERSION = <scala_version> ]
  [ COMMENT = '<string_literal>' ]
  [ IMPORTS = ( '<stage_path_and_file_name_to_read>' [ , ... ] ) ]
  [ PACKAGES = ( '<package_name_and_version>' [ , ... ] ) ]
  HANDLER = '<path_to_method>'
  [ TARGET_PATH = '<stage_path_and_file_name_to_write>' ]
  AS '<function_definition>'
Copy

Use the following syntax if the handler code will be referenced on a stage (such as in a JAR):

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] FUNCTION [ IF NOT EXISTS ] <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS <result_data_type>
  [ [ NOT ] NULL ]
  LANGUAGE SCALA
  [ { CALLED ON NULL INPUT | { RETURNS NULL ON NULL INPUT | STRICT } } ]
  [ { VOLATILE | IMMUTABLE } ]
  [ RUNTIME_VERSION = <scala_version> ]
  [ COMMENT = '<string_literal>' ]
  IMPORTS = ( '<stage_path_and_file_name_to_read>' [ , ... ] )
  HANDLER = '<path_to_method>'
Copy

SQL handler

CREATE [ OR REPLACE ] [ { TEMP | TEMPORARY } ] [ SECURE ] FUNCTION <name> (
    [ <arg_name> <arg_data_type> [ DEFAULT <default_value> ] ] [ , ... ] )
  [ COPY GRANTS ]
  RETURNS { <result_data_type> | TABLE ( <col_name> <col_data_type> [ , ... ] ) }
  [ [ NOT ] NULL ]
  [ { VOLATILE | IMMUTABLE } ]
  [ MEMOIZABLE ]
  [ COMMENT = '<string_literal>' ]
  AS '<function_definition>'
Copy

Variant syntax

CREATE OR ALTER FUNCTION

Creates a new function if it doesn’t already exist, or transforms an existing function into the function defined in the statement. A CREATE OR ALTER FUNCTION statement follows the syntax rules of a CREATE FUNCTION statement and has the same limitations as an ALTER FUNCTION statement.

Supported function alterations include:

  • Change function properties and parameters. For example, SECURE, MAX_BATCH_ROWS, LOG_LEVEL, or COMMENT.

For more information, see CREATE OR ALTER FUNCTION usage notes.

CREATE [ OR ALTER ] FUNCTION ...
Copy

Note

The COPY GRANTS parameter is not supported with this variant syntax.

Required parameters

All languages

name ( [ arg_name arg_data_type [ DEFAULT default_value ] ] [ , ... ] )

Specifies the identifier (name), any input arguments, and the default values for any optional arguments for the UDF.

RETURNS ...

Specifies the results returned by the UDF, which determines the UDF type:

  • result_data_type: Creates a scalar UDF that returns a single value with the specified data type.

    Note

    For UDF handlers written in Java, Python, or Scala, the result_data_type must be in the SQL Data Type column of the following table corresponding to the handler language:

  • TABLE ( col_name col_data_type , ... ): Creates a table UDF that returns tabular results with the specified table column(s) and column type(s).

    Note

    For Scala UDFs, the TABLE return type is not supported.

AS function_definition

Defines the handler code executed when the UDF is called. The function_definition value must be source code in one of the languages supported for handlers. The code may be:

For more details, see General usage notes (in this topic).

Note

The AS clause is not required when the UDF handler code is referenced on a stage with the IMPORTS clause.

Java

LANGUAGE JAVA

Specifies that the code is in the Java language.

RUNTIME_VERSION = java_jdk_version

Specifies the Java JDK runtime version to use. The supported versions of Java are:

  • 11.x

  • 17.x

If RUNTIME_VERSION is not set, Java JDK 11 is used.

IMPORTS = ( 'stage_path_and_file_name_to_read' [ , ... ] )

The location (stage), path, and name of the file(s) to import.

A file can be a JAR file or another type of file.

If the file is a JAR file, it can contain one or more .class files and zero or more resource files.

JNI (Java Native Interface) is not supported. Snowflake prohibits loading libraries that contain native code (as opposed to Java bytecode).

Java UDFs can also read non-JAR files. For an example, see Reading a file specified statically in IMPORTS.

If you plan to copy a file (JAR file or other file) to a stage, then Snowflake recommends using a named internal stage because the PUT command supports copying files to named internal stages, and the PUT command is usually the easiest way to move a JAR file to a stage.

External stages are allowed, but are not supported by PUT.

Each file in the IMPORTS clause must have a unique name, even if the files are in different subdirectories or different stages.

If both the IMPORTS and TARGET_PATH clauses are present, the file name in the TARGET_PATH clause must be different from each file name in the IMPORTS clause, even if the files are in different subdirectories or different stages.

Snowflake returns an error if the TARGET_PATH matches an existing file; you cannot use TARGET_PATH to overwrite an existing file.

For a UDF whose handler is on a stage, the IMPORTS clause is required because it specifies the location of the JAR file that contains the UDF.

For UDF whose handler code is in-line, the IMPORTS clause is needed only if the in-line UDF needs to access other files, such as libraries or text files.

For Snowflake system packages, such the Snowpark package, you can specify the package with the PACKAGES clause rather than specifying its JAR file with IMPORTS. When you do, the package JAR file need not be included in an IMPORTS value.

In-line Java

AS function_definition

In-line Java UDFs require a function definition.

HANDLER = handler_name

The name of the handler method or class.

  • If the handler is for a scalar UDF, returning a non-tabular value, the HANDLER value should be a method name, as in the following form: MyClass.myMethod.

  • If the handler is for a tabular UDF, the HANDLER value should be the name of a handler class.

JavaScript

LANGUAGE JAVASCRIPT

Specifies that the code is in the JavaScript language.

Python

LANGUAGE PYTHON

Specifies that the code is in the Python language.

RUNTIME_VERSION = python_version

Specifies the Python version to use. The supported versions of Python are:

  • 3.9

  • 3.10

  • 3.11

  • 3.12

IMPORTS = ( 'stage_path_and_file_name_to_read' [ , ... ] )

The location (stage), path, and name of the file(s) to import.

A file can be a .py file or another type of file.

Python UDFs can also read non-Python files, such as text files. For an example, see Reading a file.

If you plan to copy a file to a stage, then Snowflake recommends using a named internal stage because the PUT command supports copying files to named internal stages, and the PUT command is usually the easiest way to move a file to a stage.

External stages are allowed, but are not supported by PUT.

Each file in the IMPORTS clause must have a unique name, even if the files are in different subdirectories or different stages.

When the handler code is stored in a stage, you must use the IMPORTS clause to specify the handler code’s location.

For an in-line Python UDF, the IMPORTS clause is needed only if the UDF handler needs to access other files, such as packages or text files.

For packages included on the Snowflake system, such numpy, you can specify the package with the PACKAGES clause alone, omitting the package’s source as an IMPORTS value.

HANDLER = handler_name

The name of the handler function or class.

  • If the handler is for a scalar UDF, returning a non-tabular value, the HANDLER value should be a function name. If the handler code is in-line with the CREATE FUNCTION statement, you can use the function name alone. When the handler code is referenced at a stage, this value should be qualified with the module name, as in the following form: my_module.my_function.

  • If the handler is for a tabular UDF, the HANDLER value should be the name of a handler class.

Scala

LANGUAGE SCALA

Specifies that the code is in the Scala language.

RUNTIME_VERSION = scala_version

Specifies the Scala runtime version to use. The supported versions of Scala are:

  • 2.12

If RUNTIME_VERSION is not set, Scala 2.12 is used.

IMPORTS = ( 'stage_path_and_file_name_to_read' [ , ... ] )

The location (stage), path, and name of the file(s) to import, such as a JAR or other kind of file.

  • The JAR file might contain handler dependency libraries. It can contain one or more .class files and zero or more resource files.

    JNI (Java Native Interface) is not supported. Snowflake prohibits loading libraries that contain native code (as opposed to Java bytecode).

  • A non-JAR file might a file read by handler code. For an example, see Reading a file specified statically in IMPORTS.

If you plan to copy a file to a stage, then Snowflake recommends using a named internal stage because the PUT command supports copying files to named internal stages, and the PUT command is usually the easiest way to move a JAR file to a stage. External stages are allowed, but are not supported by PUT.

Each file in the IMPORTS clause must have a unique name, even if the files are in different stage subdirectories or different stages.

If both the IMPORTS and TARGET_PATH clauses are present, the file name in the TARGET_PATH clause must be different from that of any file listed in the IMPORTS clause, even if the files are in different stage subdirectories or different stages.

For a UDF whose handler is on a stage, the IMPORTS clause is required because it specifies the location of the JAR file that contains the UDF.

For UDF whose handler code is in-line, the IMPORTS clause is needed only if the in-line UDF needs to access other files, such as libraries or text files.

For Snowflake system packages, such the Snowpark package, you can specify the package with the PACKAGES clause rather than specifying its JAR file with IMPORTS. When you do, the package JAR file need not be included in an IMPORTS value.

In-line Scala

AS function_definition

UDFs with in-line Scala handler code require a function definition.

HANDLER = handler_name

The name of the handler method or class.

  • If the handler is for a scalar UDF, returning a non-tabular value, the HANDLER value should be a method name, as in the following form: MyClass.myMethod.

Optional parameters

All languages

SECURE

Specifies that the function is secure. For more information about secure functions, see Protecting Sensitive Information with Secure UDFs and Stored Procedures.

{ TEMP | TEMPORARY }

Specifies that the function persists only for the duration of the session that you created it in. A temporary function is dropped at the end of the session.

Default: No value. If a function is not declared as TEMPORARY, the function is permanent.

You cannot create temporary user-defined functions that have the same name as a function that already exists in the schema.

[ [ NOT ] NULL ]

Specifies whether the function can return NULL values or must return only NON-NULL values. The default is NULL (i.e. the function can return NULL).

Note

Currently, the NOT NULL clause is not enforced for SQL UDFs. SQL UDFs declared as NOT NULL can return NULL values. Snowflake recommends avoiding NOT NULL for SQL UDFs unless the code in the function is written to ensure that NULL values are never returned.

CALLED ON NULL INPUT or . { RETURNS NULL ON NULL INPUT | STRICT }

Specifies the behavior of the UDF when called with null inputs. In contrast to system-defined functions, which always return null when any input is null, UDFs can handle null inputs, returning non-null values even when an input is null:

  • CALLED ON NULL INPUT will always call the UDF with null inputs. It is up to the UDF to handle such values appropriately.

  • RETURNS NULL ON NULL INPUT (or its synonym STRICT) will not call the UDF if any input is null. Instead, a null value will always be returned for that row. Note that the UDF might still return null for non-null inputs.

Note

RETURNS NULL ON NULL INPUT (STRICT) is not supported for SQL UDFs. SQL UDFs effectively use CALLED ON NULL INPUT. In your SQL UDFs, you must handle null input values.

Default: CALLED ON NULL INPUT

{ VOLATILE | IMMUTABLE }

Specifies the behavior of the UDF when returning results:

  • VOLATILE: UDF might return different values for different rows, even for the same input (e.g. due to non-determinism and statefullness).

  • IMMUTABLE: UDF assumes that the function, when called with the same inputs, will always return the same result. This guarantee is not checked. Specifying IMMUTABLE for a UDF that returns different values for the same input will result in undefined behavior.

Default: VOLATILE

Note

IMMUTABLE is not supported on an aggregate function (when you use the AGGREGATE parameter). Therefore, all aggregate functions are VOLATILE by default.

COMMENT = 'string_literal'

Specifies a comment for the UDF, which is displayed in the DESCRIPTION column in the SHOW FUNCTIONS and SHOW USER FUNCTIONS output.

Default: user-defined function

COPY GRANTS

Specifies to retain the access privileges from the original function when a new function is created using CREATE OR REPLACE FUNCTION.

The parameter copies all privileges, except OWNERSHIP, from the existing function to the new function. The new function will inherit any future grants defined for the object type in the schema. By default, the role that executes the CREATE FUNCTION statement owns the new function.

Note:

  • With data sharing, if the existing function was shared to another account, the replacement function is also shared.

  • The SHOW GRANTS output for the replacement function lists the grantee for the copied privileges as the role that executed the CREATE FUNCTION statement, with the current timestamp when the statement was executed.

  • The operation to copy grants occurs atomically in the CREATE FUNCTION command (i.e. within the same transaction).

Java

PACKAGES = ( 'package_name_and_version' [ , ... ] )

The name and version number of Snowflake system packages required as dependencies. The value should be of the form package_name:version_number, where package_name is snowflake_domain:package. Note that you can specify latest as the version number in order to have Snowflake use the latest version available on the system.

For example:

-- Use version 1.2.0 of the Snowpark package.
PACKAGES=('com.snowflake:snowpark:1.2.0')

-- Use the latest version of the Snowpark package.
PACKAGES=('com.snowflake:snowpark:latest')
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You can discover the list of supported system packages by executing the following SQL in Snowflake:

SELECT * FROM INFORMATION_SCHEMA.PACKAGES WHERE LANGUAGE = 'java';
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For a dependency you specify with PACKAGES, you do not need to also specify its JAR file in an IMPORTS clause.

In-line Java

TARGET_PATH = stage_path_and_file_name_to_write

Specifies the location to which Snowflake should write the JAR file containing the result of compiling the handler source code specified in the function_definition.

If this clause is included, Snowflake writes the resulting JAR file to the stage location specified by the clause’s value. If this clause is omitted, Snowflake re-compiles the source code each time the code is needed. In that case, the JAR file is not stored permanently, and the user does not need to clean up the JAR file.

Snowflake returns an error if the TARGET_PATH matches an existing file; you cannot use TARGET_PATH to overwrite an existing file.

The generated JAR file remains until you explicitly delete it, even if you drop the function. When you drop the UDF you should separately remove the JAR file because the JAR is no longer needed to support the UDF.

For example, the following TARGET_PATH example would result in a myhandler.jar file generated and copied to the handlers stage.

TARGET_PATH = '@handlers/myhandler.jar'
Copy

When you drop this UDF to remove it, you’ll also need to remove its handler JAR file, such as by executing the REMOVE command.

REMOVE @handlers/myhandler.jar;
Copy
EXTERNAL_ACCESS_INTEGRATIONS = ( integration_name [ , ... ] )

The names of external access integrations needed in order for this function’s handler code to access external networks.

An external access integration specifies network rules and secrets that specify external locations and credentials (if any) allowed for use by handler code when making requests of an external network, such as an external REST API.

SECRETS = ( 'secret_variable_name' = secret_name [ , ...  ] )

Assigns the names of secrets to variables so that you can use the variables to reference the secrets when retrieving information from secrets in handler code.

Secrets you specify here must be allowed by the external access integration specified as a value of this CREATE FUNCTION command’s EXTERNAL_ACCESS_INTEGRATIONS parameter

This parameter’s value is a comma-separated list of assignment expressions with the following parts:

  • secret_name as the name of the allowed secret.

    You will receive an error if you specify a SECRETS value whose secret isn’t also included in an integration specified by the EXTERNAL_ACCESS_INTEGRATIONS parameter.

  • 'secret_variable_name' as the variable that will be used in handler code when retrieving information from the secret.

For more information, including an example, refer to Using the external access integration in a function or procedure.

Python

AGGREGATE

Specifies that the function is an aggregate function. For more information about user-defined aggregate functions, see Python user-defined aggregate functions.

Snowflake logo in black (no text) Preview Feature — Open

Using Python to write a handler for a user-defined aggregate function (UDAF) is a preview feature that is available to all accounts.

Note

IMMUTABLE is not supported on an aggregate function (when you use the AGGREGATE parameter). Therefore, all aggregate functions are VOLATILE by default.

ARTIFACT_REPOSITORY = repository_name

Specifies the name of the repository to use for installing PyPI packages for use by your function.

Snowflake installs these packages from the artifact repository.

Specify a list of the names of the packages that you want to install and use in your function.

Snowflake installs these packages from the artifact repository.

PACKAGES = ( 'package_name_and_version' [ , ... ] )

The name and version number of packages required as dependencies. The value should be of the form package_name==version_number. If you omit the version number, Snowflake will use the latest package available on the system.

For example:

-- Use version 1.2.2 of the NumPy package.
PACKAGES=('numpy==1.2.2')

-- Use the latest version of the NumPy package.
PACKAGES=('numpy')
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You can discover the list of supported system packages by executing the following SQL in Snowflake:

SELECT * FROM INFORMATION_SCHEMA.PACKAGES WHERE LANGUAGE = 'python';
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For more information about included packages, see Using third-party packages.

Snowflake logo in black (no text) Preview Feature — Open

Specifying a range of Python package versions is available as a preview feature to all accounts.

You can specify package versions by using these version specifiers: ==, <=, >=, <,or >.

For example:

-- Use version 1.2.3 or higher of the NumPy package.
PACKAGES=('numpy>=1.2.3')
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EXTERNAL_ACCESS_INTEGRATIONS = ( integration_name [ , ... ] )

The names of external access integrations needed in order for this function’s handler code to access external networks.

An external access integration specifies network rules and secrets that specify external locations and credentials (if any) allowed for use by handler code when making requests of an external network, such as an external REST API.

SECRETS = ( 'secret_variable_name' = secret_name [ , ...  ] )

Assigns the names of secrets to variables so that you can use the variables to reference the secrets when retrieving information from secrets in handler code.

Secrets you specify here must be allowed by the external access integration specified as a value of this CREATE FUNCTION command’s EXTERNAL_ACCESS_INTEGRATIONS parameter

This parameter’s value is a comma-separated list of assignment expressions with the following parts:

  • secret_name as the name of the allowed secret.

    You will receive an error if you specify a SECRETS value whose secret isn’t also included in an integration specified by the EXTERNAL_ACCESS_INTEGRATIONS parameter.

  • 'secret_variable_name' as the variable that will be used in handler code when retrieving information from the secret.

For more information, including an example, refer to Using the external access integration in a function or procedure.

SQL

MEMOIZABLE

Specifies that the function is memoizable.

For details, see Memoizable UDFs.

Scala

PACKAGES = ( 'package_name_and_version' [ , ... ] )

The name and version number of Snowflake system packages required as dependencies. The value should be of the form package_name:version_number, where package_name is snowflake_domain:package. Note that you can specify latest as the version number in order to have Snowflake use the latest version available on the system.

For example:

-- Use version 1.7.0 of the Snowpark package.
PACKAGES=('com.snowflake:snowpark:1.7.0')

-- Use the latest version of the Snowpark package.
PACKAGES=('com.snowflake:snowpark:latest')
Copy

You can discover the list of supported system packages by executing the following SQL in Snowflake:

SELECT * FROM INFORMATION_SCHEMA.PACKAGES WHERE LANGUAGE = 'scala';
Copy

For a dependency you specify with PACKAGES, you do not need to also specify its JAR file in an IMPORTS clause.

TARGET_PATH = stage_path_and_file_name_to_write

Specifies the location to which Snowflake should write the JAR file containing the result of compiling the handler source code specified in the function_definition.

If this clause is included, Snowflake writes the resulting JAR file to the stage location specified by the clause’s value. If this clause is omitted, Snowflake re-compiles the source code each time the code is needed. In that case, the JAR file is not stored permanently, and the user does not need to clean up the JAR file.

Snowflake returns an error if the TARGET_PATH matches an existing file; you cannot use TARGET_PATH to overwrite an existing file.

The generated JAR file remains until you explicitly delete it, even if you drop the function. When you drop the UDF you should separately remove the JAR file because the JAR is no longer needed to support the UDF.

For example, the following TARGET_PATH example would result in a myhandler.jar file generated and copied to the handlers stage.

TARGET_PATH = '@handlers/myhandler.jar'
Copy

When you drop this UDF to remove it, you’ll also need to remove its handler JAR file, such as by executing the REMOVE command.

REMOVE @handlers/myhandler.jar;
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Access control requirements

A role used to execute this operation must have the following privileges at a minimum:

Privilege

Object

Notes

CREATE FUNCTION

Schema

The privilege only enables the creation of user-defined functions in the schema.

If you want to enable the creation of data metric functions, the role must have the CREATE DATA METRIC FUNCTION privilege.

USAGE

Function

Granting the USAGE privilege on the newly created function to a role allows users with that role to call the function elsewhere in Snowflake (such as masking policy owner role for External Tokenization).

USAGE

External access integration

Required on integrations, if any, specified by the EXTERNAL_ACCESS_INTEGRATIONS parameter. For more information, see CREATE EXTERNAL ACCESS INTEGRATION.

READ

Secret

Required on secrets, if any, specified by the SECRETS parameter. For more information, see Creating a secret to represent credentials and Using the external access integration in a function or procedure.

USAGE

Schema

Required on schemas containing secrets, if any, specified by the SECRETS parameter. For more information, see Creating a secret to represent credentials and Using the external access integration in a function or procedure.

The USAGE privilege on the parent database and schema are required to perform operations on any object in a schema.

For instructions on creating a custom role with a specified set of privileges, see Creating custom roles.

For general information about roles and privilege grants for performing SQL actions on securable objects, see Overview of Access Control.

General usage notes

All languages

  • function_definition has size restrictions. The maximum allowable size is subject to change.

  • The delimiters around the function_definition can be either single quotes or a pair of dollar signs.

    Using $$ as the delimiter makes it easier to write functions that contain single quotes.

    If the delimiter for the body of the function is the single quote character, then any single quotes within function_definition (such as string literals) must be escaped by single quotes.

  • If using a UDF in a masking policy, ensure the data type of the column, UDF, and masking policy match. For more information, see User-defined functions in a masking policy.

  • If you specify the CURRENT_DATABASE or CURRENT_SCHEMA function in the handler code of the UDF, the function returns the database or schema that contains the UDF, not the database or schema in use for the session.

  • Regarding metadata:

    Attention

    Customers should ensure that no personal data (other than for a User object), sensitive data, export-controlled data, or other regulated data is entered as metadata when using the Snowflake service. For more information, see Metadata fields in Snowflake.

  • The OR REPLACE and IF NOT EXISTS clauses are mutually exclusive. They can’t both be used in the same statement.

  • CREATE OR REPLACE <object> statements are atomic. That is, when an object is replaced, the old object is deleted and the new object is created in a single transaction.

Java

  • In Java, primitive data types don’t allow NULL values, so passing a NULL for an argument of such a type results in an error.

  • In the HANDLER clause, the method name is case-sensitive.

  • In the IMPORTS and TARGET_PATH clauses:

    • Package, class, and file name(s) are case-sensitive.

    • Stage name(s) are case-insensitive.

  • You can use the PACKAGES clause to specify package names and version numbers for Snowflake system-defined dependencies, such as those from Snowpark. For other dependencies, specify dependency JAR files with the IMPORTS clause.

  • Snowflake validates that:

    • The JAR file specified in the CREATE FUNCTION statement’s HANDLER exists and contains the specified class and method.

    • The input and output types specified in the UDF declaration are compatible with the input and output types of the Java method.

    Validation can be done at creation time or execution time, depending on whether you are connected to an active Snowflake warehouse.

    • Creation time — If you are connected to an active Snowflake warehouse at the time the CREATE FUNCTION statement is executed, the UDF is validated at creation time.

    • Execution time — If you are not connected to an active Snowflake warehouse, the UDF is created, but is not validated immediately, and Snowflake returns the following message:

      Function <name> created successfully, but could not be validated since there is no active warehouse.

JavaScript

  • Snowflake does not validate JavaScript code at UDF creation time. In other words, creation of the UDF succeeds regardless of whether the code is valid. If the code is not valid, Snowflake returns errors when the UDF is called at query time.

Python

  • In the HANDLER clause, the handler function name is case-sensitive.

  • In the IMPORTS clause:

    • File name(s) are case-sensitive.

    • Stage name(s) are case-insensitive.

  • You can use the PACKAGES clause to specify package names and version numbers for dependencies, such as those from Snowpark. For other dependencies, specify dependency files with the IMPORTS clause.

  • Snowflake validates that:

    • The function or class specified in the CREATE FUNCTION statement’s HANDLER exists.

    • The input and output types specified in the UDF declaration are compatible with the input and output types of the handler.

Scala

  • In the HANDLER clause, the method name is case-sensitive.

  • In the IMPORTS and TARGET_PATH clauses:

    • Package, class, and file name(s) are case-sensitive.

    • Stage name(s) are case-insensitive.

  • You can use the PACKAGES clause to specify package names and version numbers for Snowflake system-defined dependencies, such as those from Snowpark. For other dependencies, specify dependency JAR files with the IMPORTS clause.

  • Snowflake validates that:

    • The JAR file specified in the CREATE FUNCTION statement’s HANDLER exists and contains the specified class and method.

    • The input and output types specified in the UDF declaration are compatible with the input and output types of the Scala method.

    Validation can be done at creation time or execution time, depending on whether you are connected to an active Snowflake warehouse.

    • Creation time — If you are connected to an active Snowflake warehouse at the time the CREATE FUNCTION statement is executed, the UDF is validated at creation time.

    • Execution time — If you are not connected to an active Snowflake warehouse, the UDF is created, but is not validated immediately, and Snowflake returns the following message:

      Function <name> created successfully, but could not be validated since there is no active warehouse.

SQL

  • Currently, the NOT NULL clause is not enforced for SQL UDFs.

CREATE OR ALTER FUNCTION usage notes

  • All limitations of the ALTER FUNCTION command apply.

  • You cannot replace or transform a FUNCTION with a PROCEDURE or a PROCEDURE with a FUNCTION.

  • You cannot replace or transform a temporary FUNCTION with a non-temporary FUNCTION, or a non-temporary FUNCTION with a temporary FUNCTION.

  • You cannot replace or transform a regular FUNCTION with an EXTERNAL FUNCTION, or an EXTERNAL FUNCTION with a regular FUNCTION.

  • Changing the LANGUAGE, IMPORTS, RETURNS, HANDLER, RUNTIME_VERSION, PACKAGES, VOLATILITY, NULL_HANDLING, and TARGET_PATH properties is not supported.

  • Setting or unsetting a tag is not supported. Existing tags are not altered by a CREATE OR ALTER FUNCTION statement and remain unchanged.

Examples

Java

Here is a basic example of CREATE FUNCTION with an in-line handler:

CREATE OR REPLACE FUNCTION echo_varchar(x VARCHAR)
  RETURNS VARCHAR
  LANGUAGE JAVA
  CALLED ON NULL INPUT
  HANDLER = 'TestFunc.echoVarchar'
  TARGET_PATH = '@~/testfunc.jar'
  AS
  'class TestFunc {
    public static String echoVarchar(String x) {
      return x;
    }
  }';
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Here is a basic example of CREATE FUNCTION with a reference to a staged handler:

create function my_decrement_udf(i numeric(9, 0))
    returns numeric
    language java
    imports = ('@~/my_decrement_udf_package_dir/my_decrement_udf_jar.jar')
    handler = 'my_decrement_udf_package.my_decrement_udf_class.my_decrement_udf_method'
    ;
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For more examples of Java UDFs, see examples.

JavaScript

Create a JavaScript UDF named js_factorial:

CREATE OR REPLACE FUNCTION js_factorial(d double)
  RETURNS double
  LANGUAGE JAVASCRIPT
  STRICT
  AS '
  if (D <= 0) {
    return 1;
  } else {
    var result = 1;
    for (var i = 2; i <= D; i++) {
      result = result * i;
    }
    return result;
  }
  ';
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Python

Code in the following example creates a py_udf function whose handler code is in-line as udf.

CREATE OR REPLACE FUNCTION py_udf()
  RETURNS VARIANT
  LANGUAGE PYTHON
  RUNTIME_VERSION = '3.10'
  PACKAGES = ('numpy','pandas','xgboost==1.5.0')
  HANDLER = 'udf'
AS $$
import numpy as np
import pandas as pd
import xgboost as xgb
def udf():
    return [np.__version__, pd.__version__, xgb.__version__]
$$;
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Code in the following example creates a dream function whose handler is in a sleepy.py file located on the @my_stage stage.

CREATE OR REPLACE FUNCTION dream(i int)
  RETURNS VARIANT
  LANGUAGE PYTHON
  RUNTIME_VERSION = '3.10'
  HANDLER = 'sleepy.snore'
  IMPORTS = ('@my_stage/sleepy.py')
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Scala

Here is a basic example of CREATE FUNCTION with an in-line handler:

CREATE OR REPLACE FUNCTION echo_varchar(x VARCHAR)
  RETURNS VARCHAR
  LANGUAGE SCALA
  RUNTIME_VERSION = 2.12
  HANDLER='Echo.echoVarchar'
  AS
  $$
  class Echo {
    def echoVarchar(x : String): String = {
      return x
    }
  }
  $$;
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Here is a basic example of CREATE FUNCTION with a reference to a staged handler:

CREATE OR REPLACE FUNCTION echo_varchar(x VARCHAR)
  RETURNS VARCHAR
  LANGUAGE SCALA
  RUNTIME_VERSION = 2.12
  IMPORTS = ('@udf_libs/echohandler.jar')
  HANDLER='Echo.echoVarchar';
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For more examples of Scala UDFs, see Scala UDF handler examples.

SQL

Create a simple SQL scalar UDF that returns a hard-coded approximation of the mathematical constant pi:

CREATE FUNCTION pi_udf()
  RETURNS FLOAT
  AS '3.141592654::FLOAT'
  ;
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Create a simple SQL table UDF that returns hard-coded values:

CREATE FUNCTION simple_table_function ()
  RETURNS TABLE (x INTEGER, y INTEGER)
  AS
  $$
    SELECT 1, 2
    UNION ALL
    SELECT 3, 4
  $$
  ;
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SELECT * FROM TABLE(simple_table_function());
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Output:

SELECT * FROM TABLE(simple_table_function());
+---+---+
| X | Y |
|---+---|
| 1 | 2 |
| 3 | 4 |
+---+---+
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Create a UDF that accepts multiple parameters:

CREATE FUNCTION multiply1 (a number, b number)
  RETURNS number
  COMMENT='multiply two numbers'
  AS 'a * b';
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Create a SQL table UDF named get_countries_for_user that returns the results of a query:

CREATE OR REPLACE FUNCTION get_countries_for_user ( id NUMBER )
  RETURNS TABLE (country_code CHAR, country_name VARCHAR)
  AS 'SELECT DISTINCT c.country_code, c.country_name
      FROM user_addresses a, countries c
      WHERE a.user_id = id
      AND c.country_code = a.country_code';
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Create and alter a simple function using the CREATE OR ALTER FUNCTION command

Create a function multiply that accepts two numbers:

CREATE OR ALTER FUNCTION multiply(a NUMBER, b NUMBER)
  RETURNS NUMBER
  AS 'a * b';
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Alter multiply to add a comment and make the function secure:

CREATE OR ALTER SECURE FUNCTION multiply(a NUMBER, b NUMBER)
  RETURNS NUMBER
  COMMENT = 'Multiply two numbers.'
  AS 'a * b';
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Language: English