Iceberg UDF Spec

Background and Motivation

A SQL user-defined function (UDF or UDTF) is a callable routine that accepts input parameters and executes a function body. Depending on the function type, the result can be:

• Scalar function (UDF) – returns a single value, which may be a primitive type (e.g., int, string) or a non-primitive type (e.g., struct, list).
• Table function (UDTF) – returns a table with zero or more rows of columns with a uniform schema.

This specification introduces a standardized metadata format for UDFs in Iceberg.

Goals

• Define a portable metadata format for both scalar and table SQL UDFs. The metadata is self-contained and can be moved across catalogs.
• Support function evolution through versioning and rollback.
• Provide consistent semantics for representing UDFs across engines.

Overview

UDF metadata follows the same design principles as Iceberg table and view metadata: each function is represented by a self-contained metadata file. Metadata captures definitions, parameters, return types, documentation, security, properties, and engine-specific representations.

• UDF metadata files are immutable. Any modification (new definition, updated representation, changed properties, etc.) creates a new metadata file. Catalogs use an atomic swap to update the metadata file linked to a catalog identifier.
• Each metadata file includes recent definition versions, enabling rollbacks without external state.

Specification

UDF Metadata

The UDF metadata file has the following fields:

Notes:

1. When secure is set to true, engines should prevent leakage of sensitive information to end users. Each engine may have its own security definition and mechanisms. It is the administrator's responsibility to ensure that UDFs marked as secure are properly configured and protected in their environment.
2. Entries in properties are treated as hints, not strict rules.
3. UDF names are not stored in metadata. It's the catalog's responsibility to map UDF names to metadata file locations.

Definition

Each definition represents one function signature (e.g., add_one(int) vs add_one(float)). A definition is uniquely identified by its signature (the ordered list of parameter types). There can be only one definition for a given signature. All versions within a definition must accept the same signature as specified in the definition's parameters field and must produce values of the declared return-type.

Parameter

Notes:

1. Variadic (vararg) parameters are not supported. Each definition must declare a fixed number of parameters.
2. Parameterized signatures are not supported (e.g., <E> array_agg(E)).
3. All types, including parameters and return types, are considered nullable.

Types

Types are based on the Iceberg Type.

Primitive and semi-structured type strings are encoded based on Iceberg Type JSON Representation (e.g., int, string, timestamp, decimal(9,2), variant). Type strings must contain no spaces or quote characters.

Nested types (struct, list, map) use the Iceberg Type JSON Representation with the following fields required. Any other fields must be ignored.

• list requires type and element, e.g., { "type": "list", "element": "string" }
• map requires type, key, and value, e.g., { "type": "map", "key": "string", "value": "int" }
• struct requires type and fields, where each field requires name and type, e.g., { "type": "struct", "fields": [ { "name": "id", "type": "int" }, { "name": "name", "type": "string" } ] }

Definition ID

The definition-id is a canonical string derived from the parameter types, formatted as a comma-separated list with no spaces. Each type uses the following string representation:

• Primitives and semi-structured: the type name (e.g., int, variant)
• List: list<element-type> (e.g., list<int>)
• Map: map<key-type,value-type> (e.g., map<string,int>)
• Struct: struct<name1:type1,name2:type2,...> with field names and types (e.g., struct<id:int,name:string>)

Examples of complete definition-id signatures:

• int – single int parameter
• int,string – two parameters: int and string
• int,list<int>,struct<id:int,name:string> – three parameters: an int, a list and a struct

Definition Version

Each definition can evolve over time by introducing new versions. A definition version represents a specific implementation of that definition at a given point in time.

Null Input Handling

on-null-input provides an optimization hint for query engines:

1. If set to return-null, the function always returns NULL if any input argument is NULL. This allows engines to apply predicate pushdown or skip function evaluation for rows with NULL inputs. For a function f(x, y) = x + y, the engine can safely rewrite WHERE f(a,b) > 0 as WHERE a IS NOT NULL AND b IS NOT NULL AND f(a,b) > 0.
2. If set to call, the function may handle NULLs internally (e.g., COALESCE, NVL, IFNULL), so the engine must execute the function even if some inputs are NULL.

Representation

Each representation is an object with at least one common field, type, that is one of the following:

• sql: a SQL expression that defines the function body

Representations further define metadata for each type.

SQL Representation

A definition version can have multiple SQL representations of different dialects, but only one SQL representation per dialect. The SQL representation stores the function body as a SQL expression, with metadata such as the SQL dialect.

Notes:

1. The sql must reference parameters using the names declared in the definition's parameters field.

Definition Log

Function Call Convention and Resolution in Engines

Selecting the definition of a function to use is delegated to engines, which may apply their own casting rules. However, engines should:

1. Prefer exact parameter matches over safe (widening) or unsafe casts.
2. Safely widen types as needed to avoid failing to find a matching definition.
3. Require explicit casts for unsafe or non-obvious conversions.
4. Use definitions with the same number of arguments as the input.
5. Pass positional arguments in the same position as the input.
6. Use definitions with the same set of field names as named input arguments.

Appendix A: Example – Overloaded Scalar Function

SQL statement:

-- Trino SQL
CREATE FUNCTION add_one(x INT COMMENT 'Input integer')
COMMENT 'Add one to the input integer'
RETURNS INT
RETURN x + 1;

-- Trino SQL
CREATE FUNCTION add_one(x FLOAT COMMENT 'Input float')
COMMENT 'Add one to the input float'
RETURNS FLOAT
RETURN x + 1.0;

-- Spark SQL
CREATE OR REPLACE FUNCTION add_one(x FLOAT)
RETURNS FLOAT
RETURN x + 1.0;

{
  "function-uuid": "42fd3f91-bc10-41c1-8a52-92b57dd0a9b2",
  "format-version": 1,
  "definitions": [
    {
      "definition-id": "int",
      "parameters": [
        {
          "name": "x", "type": "int", "doc": "Input integer"
        }
      ],
      "return-type": "int",
      "function-type": "udf",
      "doc": "Add one to the input integer",
      "versions": [
        {
          "version-id": 1,
          "deterministic": true,
          "representations": [
            { "type": "sql", "dialect": "trino", "sql": "x + 2" }
          ],
          "timestamp-ms": 1734507000123
        },
        {
          "version-id": 2,
          "deterministic": true,
          "representations": [
            { "type": "sql", "dialect": "trino", "sql": "x + 1" },
            { "type": "sql", "dialect": "spark", "sql": "x + 1" }
          ],
          "timestamp-ms": 1735507000124
        }
      ],
      "current-version-id": 2
    },
    {
      "definition-id": "float",
      "parameters": [
        {
          "name": "x", "type": "float", "doc": "Input float"
        }
      ],
      "return-type": "float",
      "function-type": "udf",
      "doc": "Add one to the input float",
      "versions": [
        {
          "version-id": 1,
          "deterministic": true,
          "representations": [
            { "type": "sql", "dialect": "trino", "sql": "x + 1.0" }
          ],
          "timestamp-ms": 1734507001123
        }
      ],
      "current-version-id": 1
    }
  ],
  "definition-log": [
    {
      "timestamp-ms": 1734507000123,
      "definition-versions": [
        { "definition-id": "int", "version-id": 1 }
      ]
    },
    {
      "timestamp-ms": 1734507001123,
      "definition-versions": [
        { "definition-id": "int", "version-id": 1 },
        { "definition-id": "float", "version-id": 1 }
      ]
    },
    {
      "timestamp-ms": 1735507000124,
      "definition-versions": [
        { "definition-id": "int", "version-id": 2 },
        { "definition-id": "float", "version-id": 1 }
      ]
    }
  ],
  "doc": "Overloaded scalar UDF for integer and float inputs",
  "secure": false
}

Appendix B: UDTF Example

SQL statement:

CREATE FUNCTION fruits_by_color(c VARCHAR COMMENT 'Color of fruits')
    COMMENT 'Return fruits of specific color from fruits table'
RETURNS TABLE (name VARCHAR, color VARCHAR)
RETURN SELECT name, color FROM fruits WHERE color = c;

{
  "function-uuid": "8a7fa39a-6d8f-4a2f-9d8d-3f3a8f3c2a10",
  "format-version": 1,
  "definitions": [
    {
      "definition-id": "string",
      "parameters": [
        {
          "name": "c", "type": "string", "doc": "Color of fruits"
        }
      ],
      "return-type": {
        "type": "struct",
        "fields": [
          { "name": "name", "type": "string" },
          { "name": "color", "type": "string" }
        ]
      },
      "function-type": "udtf",
      "doc": "Return fruits of a specific color from the fruits table",
      "versions": [
        {
          "version-id": 1,
          "deterministic": true,
          "representations": [
            { "type": "sql", "dialect": "trino", "sql": "SELECT name, color FROM fruits WHERE color = c" },
            { "type": "sql", "dialect": "spark", "sql": "SELECT name, color FROM fruits WHERE color = c" }
          ],
          "timestamp-ms": 1734508000123
        }
      ],
      "current-version-id": 1
    }
  ],
  "definition-log": [
    {
      "timestamp-ms": 1734508000123,
      "definition-versions": [
        { "definition-id": "string", "version-id": 1 }
      ]
    }
  ],
  "doc": "UDTF returning (name, color) rows filtered by the given color",
  "secure": false
}