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Table of Contents

RFC-0126: Introduce XCQ(Cross Consensus Query)
Start DateOct 25 2024
DescriptionIntroduce XCQ (Cross Consensus Query)
AuthorsBryan Chen, Jiyuan Zheng

Summary

This proposal introduces XCQ (Cross Consensus Query), which aims to serve as an intermediary layer between different chain runtime implementations and tools/UIs, to provide a unified interface for cross-chain queries. XCQ abstracts away concrete implementations across chains and supports custom query computations.

Use cases benefiting from XCQ include:

  • XCM bridge UI:
    • Query asset balances
    • Query XCM weight and fee from hop and dest chains
  • Wallets:
    • Query asset balances
    • Query weights and fees for operations across chains
  • Universal dApp that supports all the parachains:
    • Perform Feature discovery
    • Query pallet-specific features
    • Construct extrinsics by querying pallet index, call index, etc

Motivation

In Substrate, runtime APIs facilitate off-chain clients in reading the state of the consensus system. However, different chains may expose different APIs for a similar query or have varying data types, such as doing custom transformations on direct data, or differing AccountId types. This diversity also extends to client-side, which may require custom computations over runtime APIs in various use cases. Therefore, tools and UI developers often access storage directly and reimplement custom computations to convert data into user-friendly representations, leading to duplicated code between Rust runtime logic and UI JS/TS logic. This duplication increases workload and potential for bugs.

Therefore, a system is needed to serve as an intermediary layer between concrete chain runtime implementations and tools/UIs, to provide a unified interface for cross-chain queries.

Stakeholders

  • Runtime Developers
  • Tools/UI Developers

Explanation

The overall query pattern of XCQ consists of three components:

  • Runtime: View-functions across different pallets are amalgamated through an extension-based system.
  • XCQ query: Custom computations over view-function results are encapsulated via PolkaVM programs.
  • XCQ query arguments: Query arguments like accounts to be queried are also passed together with the query program.

XCQ Runtime API

The runtime API for off-chain query usage includes two methods:

  • execute_query: Executes the query and returns the result. It takes the query, input, and weight limit as arguments. The query is the query program in PolkaVM program binary format. The input is the query arguments that is SCALE-encoded. The weight limit is the maximum weight allowed for the query execution.
  • metadata: Return metadata of supported extensions (introduced in later section) and methods, serving as a feature discovery functionality. The representation and encoding mechanism is similar to the frame-metadata, using scale-info.

Example XCQ Runtime API

#![allow(unused)]
fn main() {
decl_runtime_apis! {
    pub trait XcqApi {
        fn execute_query(query: Vec<u8>, input: Vec<u8>, weight_limit: u64) -> XcqResult;
        fn metadata() -> Vec<u8>;
    }
}
type XcqResult =  Result<XcqResponse, XcqError>;
type XcqResponse = Vec<u8>;
enum XcqError {
    Custom(String),
}
}

Example Metadata (before SCALE-encoded)

#![allow(unused)]
fn main() {
pub struct Metadata {
    pub types: PortableRegistry,
    pub extensions: Vec<ExtensionMetadata<PortableForm>>,
}
}

XCQ Executor

An XCQ executor is a runtime module that executes XCQ queries. It has a core method execute that takes a PolkaVM program binary, method name of the exported functions in the PolkaVM program, input arguments, and weight limit that the PolkaVM program can consume.

#![allow(unused)]
fn main() {
pub fn execute(
    &mut self,
    raw_blob: &[u8],
    method: &str,
    input: &[u8],
    weight_limit: u64,
) -> Result<Vec<u8>, XcqExecutorError> {...}
}

XCQ Extension

An extension-based design is essential for several reasons:

  • Different chains may have different data types for semantically similar queries, making it challenging to standardize function calls across them. An extension-based design with optional associated types allows these diverse data types to be specified and utilized effectively.
  • Function calls distributed across various pallets can be amalgamated into a single extension, simplifying the development process and ensuring a more cohesive and maintainable codebase.
  • New functionalities can be added without upgrading the core part of the XCQ.
  • Ensure the core part is in a minimal scope.

Essential components of an XCQ extension system include:

  • A hash-based extension id generation mechanism for addressing and versioning . The hash value derives from the extension name and its method sets. Any update to an extension is treated as a new extension.

  • decl_extension macro: Defines an extension as a Rust trait with optional associated types.

Example usage:

#![allow(unused)]
fn main() {
use xcq_extension::decl_extension;

pub trait Config {
    type AssetId: Codec;
    type AccountId: Codec;
    type Balance: Codec;
}
decl_extension! {
    pub trait ExtensionFungibles {
        type Config: Config;
        fn total_supply(asset: <Self::Config as Config>::AssetId) -> <Self::Config as Config>::Balance;
        fn balance(asset: <Self::Config as Config>::AssetId, who: <Self::Config as Config>::AccountId) -> <Self::Config as Config>::Balance;
    }
}
}
  • impl_extensions macro: Generates extension implementations and extension-level metadata.

Example Usage:

#![allow(unused)]
fn main() {
// ExtensionImpl is an aggregate struct to impl different extensions
struct ExtensionImpl;
impl extension_fungibles::Config for ExtensionImpl {
    type AssetId = u32;
    type AccountId = [u8; 32];
    type Balance = u64;
}
impl_extensions! {
    impl extension_core::ExtensionCore for ExtensionImpl {
        type Config = ExtensionImpl;
        fn has_extension(id: <Self::Config as extension_core::Config>::ExtensionId) -> bool {
            matches!(id, 0 | 1)
        }
    }

    impl extension_fungibles::ExtensionFungibles for ExtensionImpl {
        type Config = ExtensionImpl;
        #[allow(unused_variables)]
        fn total_supply(asset: <Self::Config as extension_fungibles::Config>::AssetId) -> <Self::Config as extension_fungibles::Config>::Balance {
            200
        }
        #[allow(unused_variables)]
        fn balance(asset: <Self::Config as extension_fungibles::Config>::AssetId, who: <Self::Config as extension_fungibles::Config>::AccountId) -> <Self::Config as extension_fungibles::Config>::Balance {
            100
        }
    }
}
}
  • ExtensionExecutor: Connects extension implementations and xcq-executor. All methods of all extensions that a chain supports are amalgamated into a single host_call entry. Then this entry is registered as a typed function entry in PolkaVM Linker within the xcq-executor. Given the extension ID and call data encoded in SCALE format, call requests from the guest XCQ program are dispatched to corresponding extensions:
#![allow(unused)]
fn main() {
linker
    .define_typed(
        "host_call",
        move |caller: Caller<'_, Self::UserData>,
              extension_id: u64,
              call_ptr: u32,
              call_len: u32|
              -> Result<u64, ExtensionError> {
                  ...
              });
}
  • PermissionController: Filters guest XCQ program calling requests, useful for host chains to disable some queries by filtering invoking sources.
#![allow(unused)]
fn main() {
pub trait PermissionController {
    fn is_allowed(extension_id: ExtensionIdTy, call: &[u8], source: InvokeSource) -> bool;
}
#[derive(Copy, Clone)]
pub enum InvokeSource {
    RuntimeAPI,
    XCM,
    Extrinsic,
    Runtime,
}
}

XCQ Program Structure

An XCQ program is structured as a PolkaVM program with the following key components:

  • Imported Functions:

    • host_call: Dispatches call requests to the XCQ Extension Executor.

      #![allow(unused)]
fn main() {
#[polkavm_derive::polkavm_import]
extern "C" {
    fn host_call(extension_id: u64, call_ptr: u32, call_len: u32) -> u64;
}
}

      Results are SCALE-encoded bytes, with the pointer address (lower 32 bits) and length (higher 32 bits) packed into a u64.

    • return_ty: Returns the type of the function call result.

      #![allow(unused)]
fn main() {
#[polkavm_derive::polkavm_import]
extern "C" {
    fn return_ty(extension_id: u64, call_index: u32) -> u64;
}
}

      Results are SCALE-encoded bytes, with the pointer address and length packed similarly to host_call.

  • Exported Functions:

    • main: The entry point of the XCQ program. It performs type checking, arguments and results passing and executes the query.

XCQ Program Execution Flow

The interaction between an XCQ program and the XCQ Extension Executor follows these steps:

  1. Program Loading: The Executor loads the PolkaVM program binary.

  2. Environment Setup: The Executor configures the PolkaVM environment, registering host functions like host_call and return_ty.

  3. Main Function Execution: The Executor calls the program's main function, passing serialized query arguments.

  4. Program Execution:

    1. Type Checking: The program uses the return_ty function to ensure compatibility with supported chain extensions.
    2. Query Execution: The program executes the query using host_call and performs custom computations.
    3. Result Serialization: The program serializes the result, writes it to shared memory, and returns the pointer and length to the executor.

  5. Result Retrieval: The Executor reads the result from shared memory and returns it to the caller.

XCM integration

The integration of XCQ into XCM is achieved by adding a new instruction to XCM, as well as a new variant of the Response type in QueryResponse message.:

  • A new ReportQuery instruction
#![allow(unused)]
fn main() {
ReportQuery {
  query: SizeLimitedXcq,
  weight_limit: WeightLimit,
  info: QueryResponseInfo,
}
}

Report to a given destination the results of an XCQ query. After query, a QueryResponse message of type XcqResult will be sent to the described destination.

Operands:

  • query: SizeLimitedXcq has a size limit(2MB)

    • program: Vec<u8>: A pre-built PVM program binary.
    • input: Vec<u8>: The arguments of the program.

  • weight_limit: WeightLimit: The maximum weight that the query should take. WeightLimit is an enum that can specify either Limit(Weight) or Unlimited.

  • info: QueryResponseInfo: Information for making the response.

    • destination: Location: The destination to which the query response message should be sent.
    • query_id: Compact<QueryId>: The query_id field of the QueryResponse message
    • max_weight: Weight: The max_weight field of the QueryResponse message

  • Add a new variant to the Response type in QueryResponse

  • XcqResult = 6 (XcqResult) XcqResult is a enum

    • Ok = 0 (Vec<u8>): XCQ executes successfully with a SCALE-encoded response.
    • Err = 1 (ErrorCode): XCQ fails with an error code. ErrorCode is a enum

  • ExceedMaxWeight = 0

  • MemoryAllocationError = 1

  • MemoryAccessError = 2

  • CallError = 3

  • OtherPVMError = 4

Errors

  • BadOrigin
  • DestinationUnsupported

Drawbacks

Performance issues

  • XCQ Query Program Size: The size of XCQ query programs should be optimized to ensure efficient storage and transmission via XCMP/HRMP. Some strategies to address this issue include:
    • Exploring modular program structures that allow for separate storage and transmission of core logic and supporting elements. PolkaVM supports splitting the program into multiple modules.
    • Establishing guidelines for optimizing dynamic memory usage within query programs

User experience issues

  • Debugging: Currently, there is no full-fledged debuggers for PolkaVM programs. The only debugging approach is to set the PolkaVM backend in interpreter mode and then log the operations at the assembly level, which is too low-level to debug efficiently.
  • Gas computation: According to this issue, the gas cost model of PolkaVM is not accurate for now.

Testing, Security, and Privacy

  • Testing:

    • A comprehensive test suite should be developed to cover various scenarios:
      • Positive test cases:
        • Basic queries with various extensions, data types, return values, custom computations, etc.
        • Accurate conversion between given weight limit and the gas limit of PolkaVM
      • Negative test cases:
        • Queries exceeding weight limits
        • Invoking queries from unauthorized sources
      • Edge cases:
        • Queries with minimal or maximum allowed input sizes
    • Integration tests to ensure proper interaction with off-chain wallets/UI and on-chain XCM, including the aforementioned use cases in Motivation section.

  • Security:

    • The XCQ system must enforce a strict read-only policy for all query operations. A mechanism should be implemented to prevent any state-changing operations within XCQ queries. For example, perform a final rollback in frame_support::storage::with_transaction to ensure the storage won't be changed.
    • Clear guidelines and best practices should be provided for parachain developers to ensure secure implementation.

Performance, Ergonomics, and Compatibility

Performance

It's a new functionality, which doesn't modify the existing implementations.

Ergonomics

The proposal facilitate the wallets and dApps developers. Developers no longer need to examine every concrete implementation to support conceptually similar operations across different chains. Additionally, they gain a more modular development experience through encapsulating custom computations over the exposed APIs in PolkaVM programs.

Compatibility

The proposal defines new apis, which doesn't break compatibility with existing interfaces.

Prior Art and References

There are several discussions related to the proposal, including:

Unresolved Questions

  • The metadata of the XCQ extensions can be integrated into frame-metadata's CustomMetadata field, but the trade-offs (i.e. compatibility between versions) need examination.