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§Substrait Text Format Grammar

This document describes the grammar for the human-readable Substrait text format used by substrait-explain. This format allows you to write Substrait query plans in a concise, readable text format that can be parsed back into full Substrait protobuf plans.

§Overview

The Substrait text format consists of three sections:

  1. Version Section (optional) - Declares the Substrait version of the plan
  2. Extensions Section (optional) - Defines URNs and function/type extensions
  3. Plan Section - Contains the actual query plan with relations

§Design Principles

This section describes the syntax and semantics principles of the text-format DSL. For the repository-level design philosophy, compatibility expectations, and format change guidance, see DESIGN.md.

The grammar is designed around several concrete choices that make it practical and consistent:

§1. Single-Line, Structured Relations

All relations follow the same structure: Name[arguments => columns]

  • Name: The relation type (Read, Filter, Project, etc.)
  • Arguments: Relation-specific: input expressions, field references, or function calls
    • Arguments follow a regular pattern (tuple, input expression, etc.) or combination, and should map directly to Substrait proto fields. Uses tuples for compound arguments, with literals, expressions, and enums for values.
  • Arrow: => separates arguments from output columns
  • Columns: Output column names and types

Every relation fits on one line with indentation showing hierarchy. This uniform pattern makes it easy to parse any relation, understand input/output structure, and add new relation types.

§2. SQL-Like References, Literals, and Enums

  • Field references: $0, $1, etc.
  • Types are shown inline with literals and column names: 42:i64, 'hello':string
  • Nullability is explicit: string? for nullable, string for non-nullable

This prevents ambiguity and makes plans self-documenting while being familiar to SQL developers.

§3. Extension Support and Structured Syntax

  • Extensions section defines URNs and function/type mappings.
  • Function calls can include anchors: add#10@1($0, $1).
  • Clear structural boundaries: [] for relations, <> for types, () for functions.
  • Maintains full Substrait compatibility while keeping the text format readable and parseable.

§4. Hierarchical Organization

  • Section headers (===) separate major components.
  • 2-space indentation shows query plan hierarchy.
  • Consistent formatting across all document elements.

The format maps directly to Substrait protobuf messages, with relations, expressions, types, and extensions corresponding to their respective protobuf structures.

§Grammar Notation

This document uses PEG (Parsing Expression Grammar) notation:

  • "text" - Literal text
  • element? - Optional element
  • element* - Zero or more repetitions
  • element+ - One or more repetitions
  • element1 / element2 - Choice (try element1 first)
    • Implementation Note: Pest uses | instead of /
  • element1 element2 - Sequence
    • Implementation Note: Pest uses ~ for explicit concatenation

§Basic Example

=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_arithmetic.yaml
Functions:
  # 10 @  1: add
  # 11 @  1: multiply

=== Plan
Root[result]
  Project[$0, $1, add($0, $1):i64]
    Read[orders => quantity:i32?, price:i64]

§Document Structure

A Substrait text format document consists of two main sections with specific formatting rules.

§Sections

The document uses === headers to separate major sections:

  • === Version - Declares the plan’s Substrait version (optional)
  • === Extensions - Defines URNs and function/type mappings (optional)
  • === Plan - Contains the actual query plan (required)

When present, the sections appear in this order, mirroring the field order of the Substrait Plan protobuf.

§Version format
=== Version major.minor.patch
  producer: producer string
  git_hash: git hash

The header carries the version number as major.minor.patch (three non-negative integers). The indented producer: and git_hash: lines are optional and may appear in either order beneath the header.

The === Version section as a whole is optional; a document with no version section is valid and denotes a plan without a declared version.

=== Version 0.55.0
  producer: my-optimizer
=== Plan
Root[result]
  Read[orders => quantity:i32?]
§Extension format
=== Extensions
URNs:
  @  urn_anchor: urn
  …
Functions:
  ##  anchor @  urn_anchor: name
  …
Types:
  ##  anchor @  urn_anchor: name
  …
Type Variations:
  ##  anchor @  urn_anchor: name
  …

Where anchor and urn_anchor are integers, urn is a text URN, and function, type, and type variation names are identifiers or quoted text.

§Plan Hierarchy and Indentation

Relations use indentation to show the query plan hierarchy:

  • Root level: No indentation (typically Root relation)
  • Child relations: Indented with 2 spaces per level
  • Each relation: On its own line with format Name[arguments => columns]
§Example
=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_arithmetic.yaml
Functions:
  # 10 @  1: gt

=== Plan
Root[result]                   // Level 0 (no indentation)
  Project[$0, $1]              // Level 1 (2 spaces)
    Filter[gt($0, 10):boolean => $0]   // Level 2 (4 spaces)
      Read[data => a:i64]      // Level 3 (6 spaces)

§Basic Terminals

§Character Classes

  • letter := [a-zA-Z] - Alphabetic characters
  • digit := [0-9] - Numeric digits

§name and identifier

  • name := identifier / quoted_name
    • Used for column names, function names, etc. It can be unquoted if it’s a valid identifier, or using “double quotes” if special characters are required (much like SQL)
    • Examples: function_name, "quoted name"
  • identifier := letter (letter / digit / "_")*
    • Used for columns, function names, etc. that are proper identifiers.
    • Examples: table_name, my_function, col1
  • quoted_name := '"' ("\\" . / !'"' .)* '"'
    • Used for columns, function names, etc. that are not valid as identifiers, and thus need quoting.
    • Examples: "function name", "table.name", "table\.name", "function \"with some\nescapes\""

§enum

Enum fields in arguments are represented as &-prefixed variants (e.g., &AscNullsFirst), matching the Substrait proto definition. This applies to all enum fields in relation arguments.

§Syntax

enum := "&" identifier

§Examples
  • &AscNullsFirst, &AscNullsLast, &DescNullsFirst, &DescNullsLast - sort directions

§literal

A literal can be an integer, float, boolean, string, or null. Literals may include a type annotation:

literal := (float / integer / boolean / string / "null") (":" type)?

  • integer := "-"? digit+
    • Examples: 42, -10, 0
    • Default to i64 type; other integer types may be assigned
  • float := "-"? digit+ "." digit+
    • Examples: 3.14, -2.5, 1.0
    • Default to fp64 type; other float types may be assigned
  • boolean := "true" / "false"
    • Examples: true, false
    • May only be boolean type
  • string := "'" ("\\" . / !"'" .)* "'"
    • Examples: 'hello', 'table name', 'C:\path\to\file', 'line1\nline2', 'quote\'s here'
    • Default to string type; other types may also be assigned
  • null := "null"
    • Examples: null:i64?, null:string?, null:date?
    • A type annotation is required for null
  • typed_literal := string ":" type
    • String literals with type annotations for non-primitive types
    • Examples: '2023-01-01':date, '2023-12-25T14:30:45.123':timestamp, '2023-01-01T12:00:00.123456789':precisiontimestamp<9>, '14:30:45.123456':precisiontime<6>

All basic literal types (integer, float, boolean, and string) are supported, plus date, time, timestamp, precisiontime, precisiontimestamp, precisiontimestamptz, and typed null literals. Other Substrait literal types (e.g., interval_year, decimal, uuid) are not yet implemented. The deprecated timestamp_tz literal is also not yet implemented; use precisiontimestamptz<6> instead.

§Types

The type syntax in this grammar follows the standard Substrait type definition syntax, with extensions to support anchors and URN references for user-defined types.

§Type Syntax Overview

All types follow this general pattern:

type := ("u!")? identifier anchor? urn_anchor? nullability? parameters?

Where:

  • identifier - The type name (case-insensitive, lowercase preferred), e.g. geo_point or my_type. u!my_type syntax is accepted, but not recommended; the u! will be dropped - e.g. both u!json and json refer to the same extension.
  • anchor := "#" integer - Extension anchor (e.g., #10)
  • urn_anchor := "@" integer - URN anchor (e.g., @1)
  • nullability := "?" - Optional nullability indicator (defaults to non-nullable)
  • parameters := "<" (param ("," param)*)? ">" - Optional type parameters
  • param := type / integer / name - Type parameter (type, integer, or name)

§Simple Types

Simple types are the basic Substrait types with optional nullability.

§Syntax

simple_type_name nullability?

§Simple Type Names

From official Substrait grammar, simple_type_name can be any of these literal strings:

  • boolean, i8, i16, i32, i64
  • fp32, fp64
  • string, binary
  • timestamp, timestamp_tz, date, time
  • interval_year, uuid
§Nullability
  • ? - nullable
  • - unspecified nullability (not generally valid)
  • (nothing) - non-nullable
§Examples:

let plan_text = r#"
=== Plan
Root[result]
  Project[$0, $1, $2, $3]
    Read[data => int_field:i64, string_field:string?, created_at:timestamp?, user_id:uuid]
"#;

§Compound Types

Compound types follow the same syntax as standard Substrait parameterized types.

§Precision Time And Timestamp Types

Precision time and timestamp types put the nullability marker before the precision parameter.

§Syntax
precision_time_type         := "precisiontime" nullability? "<" integer ">"
precision_timestamp_type    := "precisiontimestamp" nullability? "<" integer ">"
precision_timestamp_tz_type := "precisiontimestamptz" nullability? "<" integer ">"

The precision parameter follows the Substrait unit convention: 0 means seconds, 3 milliseconds, 6 microseconds, 9 nanoseconds, and 12 picoseconds. Two different subsets apply:

  • Types accept the full Substrait range, any precision from 0 through 12.
  • Literals accept only 0, 3, 6, and 9.

The literal restriction is a limitation of this implementation, not of Substrait, which supports every precision from 0 to 12.

Literals stop at 9 because chrono (the underlying date/time library) has no sub-nanosecond resolution, so precision-12 literals cannot be parsed. Textifying a precision-12 value from a protobuf plan is still supported: the value is truncated to nanosecond resolution and a truncation diagnostic is emitted, but the declared type is preserved as <12> (truncating the value does not silently rewrite its type).

§Examples
precisiontime<6>
precisiontime?<6>
precisiontimestamp<9>
precisiontimestamp?<9>
precisiontimestamptz<3>
precisiontimestamptz?<3>
§Examples

// TODO: This example uses map type, which is not yet implemented in the parser.

use substrait_explain::Parser;

let plan_text = r#"
=== Plan
Root[result]
  Project[$0, $1, $2]
    Read[data => list_field:list<i64>, map_field:map<string, i64>, struct_field:struct<i64, string?>]
"#;

let plan = Parser::parse(plan_text).unwrap();
assert_eq!(plan.relations.len(), 1);

§User-Defined Types

User-defined types extend the standard Substrait UDT syntax to support anchors and URN references.

§Syntax

("u!")? identifier anchor? urn_anchor? nullability? parameters?

§Key differences from standard Substrait
  • Adds optional anchor and urn_anchor for extension references
  • The u! prefix is accepted in type declarations but normalized at storage time, so u!json and json in a declaration refer to the same type. It is an error to use u! on function or type-variation declarations.
  • In plan references both u!json and json are accepted and resolve to the same anchor. The canonical output always uses the bare name.
§Examples
=== Extensions
URNs:
  @  1: https://example.com/types
  @  2: https://example.com/functions
Types:
  #  8 @  1: point
  #  9 @  1: custom_type
Functions:
  # 10 @  2: add

=== Plan
Root[result]
  Project[$0, $1, $2]
    Read[data => point_field:point#8@1?<i8>, custom_field:custom_type#9, prefixed_field:u!custom_type]

§Expressions

§Syntax

expression := function_call / reference / literal / if_then

§Examples

add($3, 10):i64              // Simple function call with required output type
add#10@2($3, 10):i64         // Function call with anchors and output type

§Field References

Currently, only references to fields in the Relations’ input are supported.

§Syntax

reference := "$" integer

§Examples
=== Plan
Root[result]
  Project[$0, $1, $42]
    Read[data => field0:i64, field1:string, field42:boolean]

§Function Calls

§Syntax

function_call := function_signature anchor? urn_anchor? "(" (expression ("," expression)*)? ")" ":" type

where function_signature is the function base name with an optional colon-delimited type-signature suffix:

function_signature := identifier (":" argument_signature?)?
argument_signature := short_arg_type ("_" short_arg_type)*
short_arg_type     := "u!" short_arg_name | short_arg_name
short_arg_name     := ASCII_ALPHA ASCII_ALPHANUMERIC*

Examples of function signatures: add, equal:any_any, count: (empty signature), json_extract_path:u!json_str, bar:u!arg_u!arg.

§Components
  • function_signature - function name with optional signature suffix (see above)
  • anchor - optional anchor (e.g., #10)
  • urn_anchor - optional URN anchor (e.g., @1)
  • expression - as above
  • type - required output type
§Function Name Resolution

Within the plan, a function name has three parts: a base name (e.g. abs), a type signature (prefixed with a colon, e.g. :i64), and anchor (prefixed with #, e.g. #4).

Both type signature and anchor are separably optional if the reference is unambiguous; either or both may be required to make the reference unambiguous. A function name (base, signature if present, and anchor if present) must map to exactly one function named in the Extensions section.

Where unambiguous, signature and anchor may both be left off, used separately, or together for completeness (abs:i64#4($0):fp64).

§Examples
// Simple: resolves if there is exactly one function named `add`
add($0, $1):i64
// Signature: resolves only if exactly one function named `add` is registered,
// with type signature `:i64_i64`
add:i64_i64($0, $1):i64
// Anchor: resolves if anchor 1 exists with base name `add`
add#1($0, $1):i64
// Anchor + full name: resolves if anchor 1 exists with name `add` and
// type signature `i64_i64`
add:i64_i64#1($0, $1):i64
// Simple: resolves if there is exactly one function named `count`
count():i64
// Signature: resolves if "count:" is registered exactly once with
// type signature "" (zero arguments)
count:():i64

§Aggregate Measures

Aggregate measures are used in the output of Aggregate relations to compute aggregates. An aggregate measure is written as a plain function_call (see Function Calls section) in the output position of an Aggregate relation - the syntax is identical, e.g. sum($2):i64, count($1):i64, avg($3):fp64.

This syntax only captures a measure’s function_reference, arguments, and output_type. The Substrait Measure message also carries a filter (a per-measure filter expression, separate from the aggregate function) and the AggregateFunction itself has invocation (e.g. DISTINCT), phase, and sorts (for ordered aggregates), which are currently unsupported. Parsing always produces invocation: UNSPECIFIED, phase: UNSPECIFIED, no sorts, and no filter, regardless of what the original plan contained.

§IfThen

An IfThen expression is a conditional function or logical operator that evaluates to a boolean.

§Syntax

if_then := "if_then(" (if_clause ",")+ "_ ->" expression ")"

if_clause := expression "->" expression

§Examples
=== Plan
Root[status]
  Fetch[limit=10, offset=0 => ]
    Project[if_then(true -> $0, false -> $1, _ -> $2)]
      Read[events.logs => status:string?]

§Relations

Relations represent the operations in a query plan. Each relation is displayed on a single line with indentation showing the hierarchy.

§General Relation Grammar

All relations follow this general pattern:

§Syntax
relation := name "[" (arguments ("," named_arguments)? ("=>" columns)?)? "]"
columns := name ("," name)* / reference_list

Where:

  • name: The type of operation (Read, Filter, Project, Root, etc.)
  • arguments: Input expressions, field references, function calls, or other parameters (optional)
  • named_arguments: Named arguments (optional)
  • =>: Separator between arguments and output columns (optional, only present when both arguments and columns are specified)
  • columns: Output column names and types, or field references for pass-through (all relations specify outputs, but format varies)
  • reference_list := reference ("," reference)*: comma-separated list of field references
§Example
RelationName[arguments, named_arguments => columns]
§Special cases
  • Root relation: Only specifies output column names, no arguments or => separator
  • Project relation: Only specifies expressions, no => separator or output columns
  • Some relations may use ‘…’ instead of column names when they pass through all fields

The exact structure varies by relation type, but all follow this basic pattern.

§Arguments

Arguments in relations can be literals, expressions, enums, or tuples thereof.

§Syntax
argument := enum / reference / literal / expression / tuple
tuple := "(" ")"                                        // 0-tuple
       / "(" argument "," ")"                           // 1-tuple (trailing comma required)
       / "(" argument ("," argument)+ ","? ")"          // 2+-tuple (trailing comma optional)
arguments := argument ("," argument)*
named_arguments := name "=" argument ("," name "=" argument)*

Tuples follow the Python/Rust trailing-comma convention to disambiguate from parenthesised expressions: (x) is a parenthesised expression, not a tuple. A trailing comma is required to form a 1-element tuple: (x,). For 2+ elements the trailing comma is optional: (x, y) and (x, y,) are equivalent.

§Examples
  • Simple arguments: $0, 42, 'hello', &AscNullsFirst
  • 0-tuple: ()
  • 1-tuple: (&HASH,) — trailing comma required
  • 2+-tuple: ($0, &AscNullsFirst), (&HASH, &RANGE,)
  • Named arguments: limit=10, offset=5

§Root Relation

§Syntax

"Root" "[" (name ("," name)*)? "]"

§Example
=== Plan
Root[c, d]           // root with output columns c and d
  Project[$0, $1]
    Read[data => a:i64, b:string]

§Read Relation

§Syntax
read_relation := "Read" "[" table_name output "]"
output := implicit_output / direct_output
implicit_output := "=>" named_column_list
direct_output := "+>" named_column_list ("|>" reference_list)?
§Components
  • table_name := name ("." name)* - table name, optionally qualified with schema/database
  • named_column := name ":" type - column name with type annotation
  • named_column_list := (named_column ("," named_column)*)? - the list of columns and their types to be read from the table table_name.
    • => is used to mean implicit column ordering; for Read, this translates to Direct column ordering.
    • When used with +> and no |>, the named_columns are in the expected order of the table, and Direct emit is used.
    • When used with +> … |>, the named_columns are in the expected order of the table, and the emit order is a Remap specified by reference_list.
§Example
=== Plan
Root[result]
  Project[$0, $1]
    Read[schema.table => a:i64, b:string?]
Root[result2]
  Project[$0, $1]
    Read[orders => quantity:i32?, price:i64]

Use +> when the read’s base schema records the direct output domain:

=== Plan
Root[a, b]
  Read[my_table +> a:i64, b:string]

Use +> ... |> to specify an Emit / output ordering different from the table’s base schema: only some fields should flow downstream:

=== Plan
Root[b, a]
  Read[my_table +> a:i64, b:string, c:i64 |> $1, $0]

§VirtualTable Read Relation

A VirtualTable read embeds inline data directly in the plan, similar to SQL’s VALUES clause. Instead of referencing a catalog table, the data rows are specified as part of the relation.

The Read:Virtual relation uses the same ReadRel protobuf message with ReadType::VirtualTable, where each row is a nested::Struct containing expressions.

§Syntax

"Read:Virtual" "[" virtual_read_rows ("," "filter" "=" expression)? "=>" named_column_list "]"

Where virtual_read_rows := virtual_row ("," virtual_row)* / "_", and virtual_row := "(" (expression ("," expression)*)? ")" — a parenthesized tuple of expressions forming one row. Rows may be empty (()) for zero-column tables. For an empty virtual table, write _ in place of the entire row list, e.g. Read:Virtual[_ => id:i64] for zero rows.

§Components
  • virtual_row - parenthesized tuple of expressions, one per row; () for zero-column rows
  • expression - any expression (literal, field reference, function call)
  • filter - optional ReadRel.filter expression, with field references over the virtual table output schema
  • named_column_list - output column names with type annotations
§Examples

Inline form with two rows:

=== Plan
Root[id, name]
  Read:Virtual[(1, 'alice'), (2, 'bob') => id:i64, name:string]

Empty virtual table (no rows):

=== Plan
Root[id, name]
  Read:Virtual[_ => id:i64, name:string]

Inline form with a ReadRel.filter:

=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_comparison.yaml
Functions:
  # 10 @  1: gt

=== Plan
Root[id, name]
  Read:Virtual[(1, 'alice'), (2, 'bob'), filter=gt($0, 1:i64):boolean => id:i64, name:string]
§Multi-line form

For readability, a Read:Virtual with many rows may be written across several lines. Each continuation line is indented one level deeper than the relation and prefixed with a - marker. Continuations are allowed after the opening [, after each row or filter separator (,), and before =>:

=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_comparison.yaml
Functions:
  # 10 @  1: gt

=== Plan
Root[id, name]
  Read:Virtual[
    - (1, 'alice'),
    - (2, 'bob'),
    - filter=gt($0, 1:i64):boolean
    - => id:i64, name:string]

The multi-line form is purely a layout convenience: it parses to exactly the same plan as the inline form above. The standard output may use inline or multi-line form depending on the length of the VirtualTable.

§ExtensionTable Read Relation

An ExtensionTable read uses ReadRel with ReadType::ExtensionTable. The relation header carries the read output schema, while a required + Ext: addendum carries the custom table detail payload.

§Syntax
extension_table_read_relation := "Read:Extension" "[" named_column_list "]"
extension_table_detail        := "+" "Ext" ":" name "[" (empty / extension_args)? "]"

The + Ext: line is indented one level deeper than the Read:Extension line. It is required, and addendum lines must appear before any child relations. Canonical formatting writes + Ext: first, followed by + Enh: and + Opt: lines when present.

§Components
  • named_column_list - output column names with type annotations, stored in ReadRel.base_schema
  • name - the extension name registered with ExtensionRegistry
  • extension_args - positional and/or named arguments encoded into the ExtensionTable.detail: Any
§Example
=== Plan
Root[id, payload]
  Read:Extension[id:i64, payload:string]
    + Ext:BlobStoreRead['path/to/file', limit=100, include_archived=true]

Relation-level advanced extensions can still be attached to the same read relation:

=== Plan
Root[id]
  Read:Extension[id:i64]
    + Ext:BlobStoreRead['path/to/file']
    + Enh:PartitionHint[&HASH, count=8]
    + Opt:PlanHint[hint='parallel']

§Filter Relation

§Syntax

"Filter" "[" expression "=>" reference_list "]"

§Components
  • expression - boolean expression for filtering
  • reference_list - field references to pass through
§Example
=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_arithmetic.yaml
Functions:
  # 10 @  1: gt

=== Plan
Root[result]
  Filter[gt($2, 100):boolean => $0, $1, $2]
    Project[$0, $1, $2]
      Read[data => a:i64, b:string, c:i32]

§Project Relation

§Syntax

"Project" "[" (expression ("," expression)*)? "]"

§Components
  • expression - field reference, function call, or literal (see Expressions section)
§Example
=== Plan
Root[result]
  Project[$1, 42]                    // project field 1 and literal 42
    Read[data => a:i64, b:string]

§Aggregate Relation

§Syntax

"Aggregate" "[" grouping_sets "=>" aggregate_output "]"

§Components
  • grouping_sets := grouping_set_list / expression_list - can be a list of grouping sets (each parenthesized), or a single unparenthesized list for the common, single-set case
  • grouping_set_list := grouping_set ("," grouping_set)*
  • grouping_set := "(" expression_list ")" / "_" - a grouping set can be (1) a list of expressions, or (2) _, the standard we use for empty lists
  • aggregate_output := expression ("," expression)* - comma-separated list of output items
  • Each output item is either an aggregate function call (which becomes a new measure), or an expression that must match one of the grouping_sets expressions by value - since an Aggregate relation’s output schema is always exactly grouping_expressions + measures. See Aggregate Measures section
§Example
=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_aggregate.yaml
Functions:
  # 10 @  1: sum
  # 11 @  1: count

=== Plan
Root[result]
  Aggregate[($0), ($0, $1) => $0, $1, sum($2):i64, count($2):i64]           // Group by field 0, and ($0, $1)
    Read[orders => category:string, region:string?,  amount:i64]

§Sort Relation

The Sort relation specifies sort fields and directions for ordering the input:

Sort[($0, &AscNullsFirst), ($1, &DescNullsLast) => $0, $1]

§Syntax
sort_relation := "Sort" "[" sort_fields "=>" reference_list "]"
sort_fields := sort_field ("," sort_field)*
sort_field := "(" reference "," sort_direction ")"
sort_direction := "&AscNullsFirst" / "&AscNullsLast" / "&DescNullsFirst" / "&DescNullsLast"
§Components
  • Each sort field is a tuple: (reference, sort_direction)
  • Sort directions follow the general enum syntax and specify null handling
  • reference_list - comma-separated list of field references to pass through

§Join Relation

Syntax: "Join" "[" join_type "," expression ("," "post_filter" "=" expression)? "=>" reference_list "]"

Components:

  • join_type - Join type enum with & prefix (e.g., &Inner, &Left, &Right, &Outer)
  • expression - Join condition (boolean expression relating left and right inputs), with field references over input order
  • post_filter - Optional post-join filter expression, applied after join matching, with field references over direct output order
  • reference_list - comma-separated list of field references for output columns, with field references over direct output order

Field Reference Mapping:

For join conditions, field references map to the combined schema of left and right inputs:

  • $0, $1, … refer to left input fields
  • $n, $n+1, … refer to right input fields (where n = number of left fields)

For post_filter and reference_list, field references map to the join’s direct output order:

  • inner, left, right, and outer joins output left fields followed by right fields
  • left semi, left anti, and left single joins output left fields only
  • right semi, right anti, and right single joins output right fields only, renumbered from $0
  • left mark and right mark joins output the retained side’s fields followed by the mark column

Example:

=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_comparison.yaml
Functions:
  # 10 @  1: eq

=== Plan
Root[user_orders]
  Join[&Inner, eq($0, $2):boolean => $0, $1, $3]
    Read[users => id:i64, name:string]        // Fields $0, $1
    Read[orders => user_id:i64, amount:i32]   // Fields $2, $3

§Set Relation

§Syntax

"Set" "[" set_op "=>" reference_list "]"

§Components
  • set_op - Set operation enum with & prefix, using Substrait’s protobuf SetOp variant names directly
  • reference_list - Comma-separated list of field references for output columns

A Set relation combines two or more inputs (written as indented children, like any other multi-input relation), which must all share the same output schema. Field references map to that common schema:

  • $0, $1, … refer to fields of the shared input schema
§Example
=== Plan
Root[id, name]
  Set[&UnionAll => $0, $1]
    Read[active_users => id:i64, name:string]
    Read[archived_users => id:i64, name:string]

§Cross Relation

§Syntax

"Cross" "[" reference_list "]"

§Components
  • reference_list - Comma-separated list of field references for output columns

A Cross relation is the Cartesian product of its two inputs (written as indented children). It takes no arguments, so the bracket body is just the output columns. The output concatenates the left and right inputs, so field references map to the combined schema:

  • $0, $1, … refer to left input fields
  • $n, $n+1, … refer to right input fields (where n = number of left fields)
§Example
=== Plan
Root[id, name, order_id, amount]
  Cross[$0, $1, $2, $3]
    Read[users => id:i64, name:string]
    Read[orders => order_id:i64, amount:i32]

§Extension Relations

Extension relations allow custom relation types with user-defined protobuf payloads. They enable integration with custom data sources, optimizations, or specialized operations beyond standard Substrait relations.

§Types

There are three extension relation types, based on their input cardinality:

  • ExtensionLeaf - No child relations (e.g., custom data sources)
  • ExtensionSingle - Exactly one child relation (e.g., custom transformations)
  • ExtensionMulti - Zero or more child relations (e.g., custom joins)
§Syntax
extension_relation := extension_type ":" name "[" (empty / extension_args)? ("=>" extension_columns)? "]"
extension_type := "ExtensionLeaf" / "ExtensionSingle" / "ExtensionMulti"
extension_args := (positional_args ("," named_args)?) / named_args
positional_args := extension_arg ("," extension_arg)*
extension_arg := enum / reference / literal / expression / tuple
named_args := named_arg ("," named_arg)*
named_arg := name "=" extension_arg
extension_columns := (extension_column ("," extension_column)*)?
extension_column := named_column / reference / expression

Note: the parser also accepts the => section being omitted entirely (e.g. ExtensionLeaf:Foo[_]), treating it as zero output columns. The canonical form always includes =>.

§Components
  • extension_type - One of ExtensionLeaf, ExtensionSingle, or ExtensionMulti
  • name - The extension name (registered with ExtensionRegistry)
  • empty (_) - Explicitly marks an extension with no arguments
  • extension_args - Positional arguments (enums, references, literals, expressions, or tuples) and/or named arguments (key=value pairs); both are optional
  • extension_columns - Output column definitions: named columns (name:type), field references ($0), or expressions

Untyped scalar extension arguments such as 2, 2.4, true, and 'path' are treated as extension scalar values and render without expression type suffixes, even in verbose output. They can still be consumed by extension handlers as expressions, in which case they widen to default non-nullable Substrait literal expressions. Typed literals such as 2:i16 or '2024-01-01':date, field references, function calls, and casts are expression values.

§Examples
=== Plan
Root[result]
  ExtensionSingle:CustomFilter[threshold=100 => $0, $1]
    ExtensionLeaf:ParquetScan[path='data/users.parquet', batch_size=1024 => id:i64, name:string]

Extension with positional arguments and no output columns:

ExtensionSingle:VectorNormalize[$0, $1, method='l2' => ]

Extension with no arguments:

ExtensionLeaf:EmptySource[_ => ]
§Custom Extension Types

To use custom relation types with protobuf detail payloads, register them with an ExtensionRegistry. See the API documentation for details on implementing the Explainable trait.

§Advanced Extensions

Advanced extensions allow attaching enhancement and optimization metadata to any standard relation via the Substrait AdvancedExtension protobuf field.

§Overview

Each relation can carry:

  • At most one enhancement (+ Enh:) — extra semantic metadata attached to a relation
  • Zero or more optimizations (+ Opt:) — hints for the query planner

§Syntax

addendum      := "+" addendum_type ":" name "[" (empty | extension_args)? "]"
addendum_type := "Enh" | "Opt" | "Ext"

Where:

  • addendum_typeEnh for an enhancement, Opt for an optimization, or Ext for an ExtensionTable detail on Read:Extension
  • name — the registered type name (e.g. PartitionHint)
  • extension_args — positional and/or named arguments; use _ for empty

Addendum lines are indented one level deeper than the relation they annotate, just like child relations. They MUST appear before any child relations. + Enh: and + Opt: lines attach advanced extensions to standard relations. + Ext: lines are only valid under Read:Extension; extension relations (ExtensionLeaf, ExtensionSingle, and ExtensionMulti) do not support addenda.

§Argument Syntax

Extension arguments follow the same rules as extension-relation arguments. Enum values are written with a & prefix:

enum_value := "&" identifier
§Examples
  • &HASH, &RANGE, &BROADCASTPartitionStrategy variants for PartitionHint
  • &AscNullsFirst — sort direction enum in a relation argument

§Example: Enhancement on a Read Relation

=== Plan
Root[result]
  Read[data => col:i64]
    + Enh:PartitionHint[&HASH, count=8]

§Example: Enhancement and Multiple Optimizations

=== Plan
Root[result]
  Read[data => col:i64]
    + Enh:PartitionHint[&HASH, count=4]
    + Opt:PlanHint[hint='use_index']
    + Opt:PlanHint[hint='parallel']

§Custom Extension Types

To parse or textify advanced extensions with custom protobuf payloads, register them with an ExtensionRegistry:

  • Enhancements: registry.register_enhancement::<MyEnhancement>()
  • Optimizations: registry.register_optimization::<MyOptimization>()

Both require implementing the Explainable trait, which provides from_args / to_args for text-format conversion, and prost::Message + prost::Name for protobuf serialization.

§Parse failure behaviour

If a + Enh: or + Opt: name is not registered in the registry at parse time, the parser returns a hard error.

If the registry does not know the type URL at textify time (e.g. when formatting a plan received from an external source), the line is still emitted with a failure token and a FormatError is collected — the rest of the plan is unaffected.

For example, if a plan contains an enhancement whose type URL is not registered, the textified output replaces the name and arguments with !{extension}:

=== Plan
Root[result]
  Read[my.table => col:i64]
    + Enh[!{extension}]

The collected FormatError carries the full detail:

FormatError::Extension(ExtensionError::NotFound {
    name: "type.googleapis.com/acme.PartitionHint".to_string(),
})

The Read line and everything else in the plan are textified normally; only the unrecognized enhancement line degrades to the failure token.

§Complete Example

A complete query that joins users and orders tables, calculates total order value, filters for high-value orders, and groups by user to show total revenue per customer:

=== Extensions
URNs:
  @  1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_comparison.yaml
  @  2: https://github.com/substrait-io/substrait/blob/main/extensions/functions_arithmetic.yaml
  @  3: https://github.com/substrait-io/substrait/blob/main/extensions/functions_aggregate.yaml
Functions:
  # 10 @  1: eq
  # 11 @  1: gt
  # 12 @  2: multiply
  # 13 @  3: sum

=== Plan
Root[customer_revenue]
  Aggregate[$0, $1 => $0, $1, sum($3):i64]
    Filter[gt($3, 100):boolean => $0, $1, $2, $3]
      Project[$0, $1, $2, multiply($4, $5):i64]
        Join[&Inner, eq($0, $3):boolean => $0, $1, $2, $3, $4, $5]
          Read[users => id:i64, name:string, region:string]
          Read[orders => user_id:i64, quantity:i32, price:i64]