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178 changes: 178 additions & 0 deletions docs/rfcs/0001_kernel.md
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# RFC: Extract `iceberg-kernel` for Pluggable Execution Layers
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## Background

Issue #1819 proposes decoupling the protocol/metadata/plan logic that currently lives inside the `iceberg` crate so that it can serve as a reusable “kernel,” similar to the approach taken by delta-kernel-rs. Today the `iceberg` crate simultaneously exposes the public trait surface and the default engine (Tokio runtime, opendal-backed FileIO, Arrow readers, etc.). This tight coupling makes it difficult for downstream projects to embed Iceberg metadata while providing their own storage, runtime, or execution stack.
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## Goals and Scope

- **Full read & write coverage**: the kernel must contain every protocol component required for both scan planning and transactional writes (append, rewrite, commit, etc.).
- **No default runtime dependency**: the kernel defines a `Runtime` trait instead of depending on Tokio or Smol.
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- **No default storage dependency**: the kernel defines `FileIO` traits only; concrete implementations (for example `iceberg-fileio-opendal`) live in dedicated crates.

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Should this be Storage trait rather than FileIO trait?

From the code example below it seems like FileIO is a struct container for Storage and registry

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I'm thinking that we have a iceberg-storage crate, which contains all fileio related things, including FileIO/InputFile/OutputFile struct, Storage trait, some builtin storage implemention(enabled independently by feature).

- **Stable facade for existing users**: the top-level `iceberg` crate continues to expose the familiar API by re-exporting the kernel plus a default engine feature.

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I agree that we should keep public api as stable as possible, but it maybe not practical before we reach 1.0. Currently we reply on review to ensure it, but after reaching 1.0 we should use some autonomous checks to ensure that.


Out of scope: changes to the Iceberg table specification or rewriting catalog adapters.

## Architecture Overview

### Workspace Layout

```
crates/
kernel/ # new: pure protocols & planning logic
spec/ expr/ catalog/ table/ transaction/ scan/ runtime_api
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io/traits.rs # FileIO traits (no opendal)
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fileio/
opendal/ # e.g. `iceberg-fileio-opendal`
fs/ # other FileIO implementations
runtime/
tokio/ # e.g. `iceberg-runtime-tokio`
smol/
iceberg/ # facade re-exporting kernel + default engine
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catalog/* # depend on kernel (+ chosen FileIO/Runtime crates)
integrations/* # e.g. datafusion using facade or composing crates
```

### Trait Surfaces

#### FileIO
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```rust
pub struct FileMetadata {
pub size: u64,
...
}

pub type FileReader = Box<dyn FileRead>;

#[async_trait::async_trait]
pub trait FileRead: Send + Sync + 'static {
async fn read(&self, range: Range<u64>) -> Result<Bytes>;
}

pub type FileWriter = Box<dyn FileWrite>;

#[async_trait::async_trait]
pub trait FileWrite: Send + Unpin + 'static {
async fn write(&mut self, bs: Bytes) -> Result<()>;
async fn close(&mut self) -> Result<FileMetadata>;
}

pub type StorageFactory = fn(attrs: HashMap<String, String> -> Result<Arc<dyn Storage>>);

#[async_trait::async_trait]
pub trait Storage: Clone + Send + Sync {
async fn reader(&self, path: &str) -> Result<FileReader>;
async fn writer(&self, path: &str) -> Result<FileWriter>;
async fn delete(&self, path: &str) -> Result<()>;
async fn exists(&self, path: &str) -> Result<bool>;

...
}

pub struct FileIO {
registry: DashMap<String, StorageFactory>,
}

impl FileIO {
fn register(scheme: &str, factory: StorageFactory);

async fn read(path: &str) -> Result<Bytes>;
async fn reader(path: &str) -> Result<FileReader>;
async fn write(path: &str, bs: Bytes) -> Result<FileMetadata>;
async fn writer(path: &str) -> Result<FileWriter>;
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async fn delete(&self, path: &str) -> Result<()>;
...
}
```

- The kernel only defines the trait and error types.
- `iceberg-fileio-opendal` (new crate) ships an opendal-based implementation; other backends can publish their own crates.
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#### Runtime

```rust
pub trait Runtime: Send + Sync + 'static {
type JoinHandle<T>: Future<Output = T> + Send + 'static;

fn spawn<F, T>(&self, fut: F) -> Self::JoinHandle<T>
where
F: Future<Output = T> + Send + 'static,
T: Send + 'static;

fn spawn_blocking<F, T>(&self, f: F) -> Self::JoinHandle<T>
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where
F: FnOnce() -> T + Send + 'static,
T: Send + 'static;

fn sleep(&self, dur: Duration) -> Pin<Box<dyn Future<Output = ()> + Send>>;
}
```

- `TableScan` planning, metadata refresh, and `Transaction::commit` depend only on this trait.
- Crates such as `iceberg-runtime-tokio` provide concrete schedulers; consumers pick whichever runtime crate fits their stack.

#### Catalog / Table / Transaction

- The `Catalog` trait moves into the kernel and returns lightweight `TableHandle` objects (metadata + FileIO + Runtime).
- `TableHandle` no longer embeds Arrow helpers; Arrow-specific logic lives in engine crates.
- Transactions and their actions remain in the kernel, but rely on injected `Runtime` for retries/backoff.

#### Scan / Planner

- The kernel produces pure `TableScanPlan` descriptions (manifests, data-files, predicates, task graph).
- Engines provide executors (e.g., `ArrowExecutor`) that transform plans into record batches or other runtime-specific artifacts.
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### Facade Behavior

- The top-level `iceberg` crate becomes a facade (`pub use iceberg_kernel::*`) that enables a *composition* of default crates (e.g. `iceberg-runtime-tokio`, `iceberg-fileio-opendal`, and a reference executor) behind feature flags.
- Existing convenience APIs (`Table::scan().to_arrow()`, `MemoryCatalog`, etc.) stay available but internally assemble the kernel with those default building blocks.

## Migration Plan

1. **Phase 1 – Create the kernel crate**
- Add `crates/kernel` and move `spec`, `expr`, `catalog`, `table`, `transaction`, `scan`, and supporting modules.
- Introduce temporary shim modules in the facade so existing imports keep working (mark them deprecated).

2. **Phase 2 – Abstract runtime & IO**
- Define the `Runtime` and `FileIO` traits inside the kernel.
- Remove direct `tokio`/`opendal` dependencies from kernel modules.
- Introduce standalone crates (`iceberg-runtime-tokio`, `iceberg-fileio-opendal`, etc.) that implement the new traits.

3. **Phase 3 – Detach Arrow/execution**
- Move `arrow` helpers and `ArrowReaderBuilder` into a reference executor crate (e.g. `iceberg-engine-arrow`).
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In fact, there are several parts in the to_arrow method:

  1. ArrowReaderBuilder which is used to read one split of planned task. This is in fact compute engine independent, and we should leave it in iceberg crate.
  2. An executor to use runtime to scan table in parallel. I think this part should be move to the new default engine crate.

- Update the DataFusion integration to depend on the facade or directly compose kernel + runtime + fileio + executor crates.

4. **Phase 4 – Catalog & integration updates**
- Point catalog crates and other integrations to the kernel interfaces; depend on specific FileIO/Runtime crates only when required.
- Keep `iceberg-catalog-loader` kernel-only so users can inject their preferred combinations.

5. **Phase 5 – Release & documentation**
- Finish the split within the 0.y.z series, provide an upgrade guide, and add kernel acceptance tests to guarantee trait stability.

## Compatibility

- Users who stick with the `iceberg` facade keep their existing API surface; the facade simply composes kernel + default runtime + default FileIO + reference executor under the hood.
- Advanced integrators can depend solely on `iceberg-kernel` and mix in whichever `FileIO`, `Runtime`, and executor crates they need (or author their own).
- CI keeps running the current integration tests and adds kernel-specific acceptance suites.

## Risks and Mitigations

| Risk | Description | Mitigation |
| ---- | ----------- | ---------- |
| Trait churn | Updating catalog/scan traits could break downstream crates | Maintain shim modules, use `#[deprecated]` windows, and document migration steps |
| Generic complexity | New traits may introduce complicated type bounds | Prefer `Arc<dyn Trait>` and `BoxFuture` to keep signatures manageable |
| Documentation gap | Users may not know which engine to pick | Publish new docs, diagrams, and “custom engine” tutorials alongside the split |

## Open Questions

1. Should the kernel expose any Arrow helpers, or should every Arrow-specific function live exclusively in engine crates?
2. Do we need a `ScanExecutor` trait inside the kernel for non-Arrow consumers?

## Conclusion

Extracting `iceberg-kernel` plus a pluggable engine layer lets the project:

- Offer a lightweight, embeddable implementation of the Iceberg protocol,
- Enable external engines (DataFusion, Spark Connect, custom services) to reuse Iceberg metadata without inheriting specific runtime/storage dependencies,
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