Transform complex Substrait protobuf plans into readable, SQL EXPLAIN-like text
A Rust library that converts Substrait query plans between protobuf format and a human-readable text format. It transforms verbose, nested protobuf structures into concise, SQL-like text that's easy to read and debug.
- Human-readable output: Convert complex Substrait plans into simple, readable text
- Bidirectional conversion: Parse text format back into Substrait plans
- Extension support: Full support for Substrait extensions and custom functions
- Error handling: Graceful error handling that doesn't prevent output generation
- Flexible formatting: Configurable output options for different use cases
- Complete grammar: Full specification of the text format in the [
grammar] module
For project-level design principles, compatibility expectations, and format change guidance, see the design philosophy. For installation instructions, see the README.
The main workflow is parsing text format and formatting plans. This example demonstrates both basic usage and extension handling:
use substrait_explain::{parse, format};
// Parse a plan from text format (includes extensions for custom functions)
let plan_text = r#"
=== Extensions
URNs:
@ 1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_arithmetic.yaml
Functions:
## 10 @ 1: add
=== Plan
Project[$0, $1, add($0, $1):i32?]
Read[table1 => col1:i32?, col2:i32?]
"#;
let plan = parse(plan_text).unwrap();
let (output, errors) = format(&plan);
println!("{}", output);
// Check for any formatting warnings
if !errors.is_empty() {
println!("Warnings: {:?}", errors);
}Control output detail with formatting options:
use substrait_explain::{parse, format_with_options, OutputOptions, Visibility};
let plan = parse(r#"
=== Plan
Project[$0, 42, 54:i16]
Read[data => name:string?, num:i64]
"#).unwrap();
// Verbose output with all details
let verbose = OutputOptions::verbose();
let (text, _) = format_with_options(&plan, &verbose);
// Custom options
let custom = OutputOptions {
literal_types: Visibility::Always,
indent: " ".to_string(),
..OutputOptions::default()
};
let (text, _) = format_with_options(&plan, &custom);The library provides graceful error handling for formatting, producing best-effort output even if there are errors:
use substrait_explain::{parse, format};
match parse("=== Plan\nInvalidRelation[invalid]") {
Ok(plan) => {
let (text, errors) = format(&plan);
println!("Formatted: {}", text);
if !errors.is_empty() {
println!("Warnings: {:?}", errors);
}
}
Err(e) => println!("Parse error: {}", e),
}Substrait has two extension mechanisms:
- Simple extensions declare extension functions, types, and type variations.
substrait-explainreads and writes these declarations in the=== Extensionssection and uses them to resolve anchors while parsing and formatting expressions and types. No YAML files are read; substrait-explain relies on the protobufs / text format itself for function names, and does not validate type signatures exist / match extensions. - Advanced extensions carry
google.protobuf.Anypayloads for custom relation types, relation enhancements, and optimization hints.
This section describes how to register Rust handlers for advanced extension payloads, enabling round-trip conversion for custom relation types, relation enhancements, and optimization hints.
To use a custom advanced extension type with [ExtensionRegistry], it must
implement:
- [
prost::Message] - For protobuf serialization. This is usually generated byprost-buildfrom a.protofile, or derived with#[derive(prost::Message)]for hand-written message types. - [
prost::Name] - For type URL encoding.prost-buildcan generate this when configured withprost_build::Config::enable_type_names(). Default- Required by the blanket [AnyConvertible] implementation. Generated or derived prost message types normally satisfy this.- [
Explainable] - For mapping between your extension type and structured extension arguments. This is always implemented manually.
Types that do not satisfy the blanket [AnyConvertible] implementation can
implement [AnyConvertible] manually instead.
The [Explainable] trait maps between your extension type and structured
extension arguments. substrait-explain handles parsing and rendering the text
syntax around those arguments:
name()- The extension name used in text (e.g.,"ParquetScan")from_args(args)- Parse text arguments into your typeto_args(&self, context)- Convert your type to text arguments, optionally using information about relation inputs.
The extension API works across three representations:
- Text - the human-readable Substrait-explain syntax
- Extension arguments - structured values passed to
Explainable, such asExtensionArgs,ExtensionValue, andExtensionColumn - Protobuf - Substrait protobuf values and extension
Anypayloads
Untyped scalar extension literals such as 2 or 'path' are represented as
scalar ExtensionValue variants and render without expression type suffixes,
even in verbose output. The same values can still be requested as Expr through
ArgsExtractor, which widens them to default non-nullable Substrait literal
expressions. Typed literals, field references, function calls, and casts are
represented as expression values.
ExtensionProtoConvert converts between extension arguments and Substrait
protobuf values in either direction, such as output columns and relation
NamedStructs.
The to_args method receives an ExtensionContext. Relation extensions get one
ExtensionInput per available child, in relation order. Each input exposes its
emitted column count, including any output mapping applied by that child. Other
extension namespaces receive an empty input slice.
Use ArgsExtractor for convenient argument parsing:
extractor.expect_named::<T>(name)- Required argumentextractor.get_named::<T>(name)?- Optional argument, returningOption<T>extractor.check_exhausted()- Verify no unexpected arguments
Extensions are organized into namespaces by their type:
- Relation - Custom relation types (
ExtensionLeafRel,ExtensionSingleRel,ExtensionMultiRel), displayed asExtensionLeaf,ExtensionSingle, andExtensionMultiin this text format - Enhancement - Semantic metadata attached to relations, displayed with the
+ Enh:prefix - Optimization - Non-semantic optimization hints, displayed with the
+ Opt:prefix
Register extensions to the appropriate namespace:
# use prost::{Message, Name};
# use substrait_explain::extensions::{
# Explainable, ExtensionArgs, ExtensionContext, ExtensionError, ExtensionRegistry,
# };
#[derive(Clone, PartialEq, Message)]
pub struct MySourceConfig {
// Auto-generated from prost
}
impl Name for MySourceConfig {
// Implement this
# const NAME: &'static str = "MySourceConfig";
# const PACKAGE: &'static str = "example";
# fn full_name() -> String { "example.MySourceConfig".into() }
# fn type_url() -> String { "type.googleapis.com/example.MySourceConfig".into() }
}
# impl Explainable for MySourceConfig {
# fn name() -> &'static str { "MySource" }
# fn from_args(_: &ExtensionArgs) -> Result<Self, ExtensionError> { Ok(Self::default()) }
# fn to_args(
# &self,
# _context: &ExtensionContext<'_>,
# ) -> Result<ExtensionArgs, ExtensionError> {
# Ok(ExtensionArgs::default())
# }
# }
# use substrait_explain::Parser;
# use substrait_explain::format_with_registry;
let mut registry = ExtensionRegistry::new();
// Register a relation extension
registry.register_relation::<MySourceConfig>().unwrap();
// Enhancement and optimization extensions use:
// registry.register_enhancement::<MyEnhancement>().unwrap();
// registry.register_optimization::<MyOptimization>().unwrap();
let parser = Parser::new().with_extension_registry(registry.clone());
# let plan = parser.parse_plan(r"
# === Plan
# Root[x]
# Read[t => x:i64]
# ").unwrap();
# let (output, errors) = format_with_registry(&plan, &Default::default(), ®istry);See examples/extensions.rs for a complete working example with a custom ParquetScan extension type.
The library produces a structured text format that's easy to read and parse. For a complete specification of the text format grammar, see the [grammar] module.
=== Extensions
URNs:
@ 1: https://github.com/substrait-io/substrait/blob/main/extensions/functions_arithmetic.yaml
@ 2: https://github.com/substrait-io/substrait/blob/main/extensions/functions_aggregate.yaml
Functions:
# 10 @ 1: add
# 11 @ 2: sum
# 12 @ 2: count
=== Plan
Root[result]
Aggregate[$0 => $0, sum($1):i32?, count($1):i64]
Project[$0, add($1, $2):i32?]
Read[table1 => category:string, col1:i32?, col2:i32?]
Each relation is displayed on a single line with the format:
RelationName[arguments => columns]
- arguments: Input expressions, field references, or function calls
- columns: Output column names and types
- indentation: Shows the relationship hierarchy
- Field references:
$0,$1, etc. - Literals:
42,'hello',true - Function calls:
add($0, $1):i64,sum($2):i64 - Types:
i32,string?,list<i64>
Control output formatting with [OutputOptions]:
use substrait_explain::{OutputOptions, Visibility};
// Default - concise output
let default = OutputOptions::default();
// Verbose - show all details
let verbose = OutputOptions::verbose();
// Custom - show literal types and use 4-space indentation
let custom = OutputOptions {
literal_types: Visibility::Always,
indent: " ".to_string(),
..OutputOptions::default()
};The library includes a command line interface for converting between different Substrait plan formats and validating plans. The CLI is available behind the cli feature flag.
The CLI cannot load application-provided advanced extension handlers. Use the
Rust API with [ExtensionRegistry] when parsing or formatting custom relation
types, relation enhancements, or optimization hints.
Install the CLI with:
cargo install substrait-explain --features cliOr build from source:
cargo build --release --features cliThe convert command transforms plans between different formats:
# Convert text format to JSON
substrait-explain convert -f text -t json -i plan.substrait -o plan.json
# Convert JSON back to text
substrait-explain convert -f json -t text -i plan.json -o plan.substrait
# Convert to binary protobuf format
substrait-explain convert -f text -t protobuf -i plan.substrait -o plan.pb
# Use stdin/stdout (default)
cat plan.substrait | substrait-explain convert -f text -t json > plan.jsonSupported formats:
text- Human-readable Substrait text formatjson- JSON serialized protobufyaml- YAML serialized protobufprotobuf/proto/pb- Binary protobuf format
Options:
-f, --from <FORMAT>- Input format (default: text)-t, --to <FORMAT>- Output format (default: text)-i, --input <FILE>- Input file (default: stdin)-o, --output <FILE>- Output file (default: stdout)--show-literal-types- Show type annotations on literals--verbose- Show detailed progress information
The validate command performs a roundtrip test on text format plans:
# Validate a plan file
substrait-explain validate -i plan.substrait
# Validate from stdin
cat plan.substrait | substrait-explain validate
# Validate with verbose output
substrait-explain validate -i plan.substrait --verboseOptions:
-i, --input <FILE>- Input file (default: stdin)-o, --output <FILE>- Output file (default: stdout)--verbose- Show detailed progress information
# Validate the example plans
substrait-explain validate -i example-plans/basic.substrait
substrait-explain validate -i example-plans/simple.substrait
# Convert with verbose output and type information
substrait-explain convert -f text -t json --show-literal-types --verbose -i example-plans/basic.substrait
# Roundtrip test: text → protobuf → text
substrait-explain convert -f text -t protobuf -i plan.substrait -o plan.pb
substrait-explain convert -f protobuf -t text -i plan.pb -o plan_roundtrip.substrait
diff plan.substrait plan_roundtrip.substraitTo use the CLI, you must build/install with the cli feature:
[dependencies]
substrait-explain = { version = "0.1.0", features = ["cli"] }For JSON/YAML support, also enable the serde feature:
[dependencies]
substrait-explain = { version = "0.1.0", features = ["cli", "serde"] }