Expose DataFrame-style read API (ReadBuilder / Scan / Split / TableRead) to Python
- Lenguaje dominante
- Rust
- Estrellas
- 197
- Forks
- 92
- Merge medio
- 1 d 16 h
- PR fusionados (30 d)
- 91
Descripción
### Search before asking
- [x] I searched in the [issues](https://github.com/apache/paimon-rust/issues) and found nothing similar.
### Motivation
PyPaimon has two read paths today:
- **SQL** (`SQLContext.sql`) — already runs on the Rust DataFusion engine.
- **DataFrame** (`ReadBuilder → Split → TableRead.to_arrow/to_pandas/to_ray`) —
still **pure Python**, even though the Rust core already implements the same
model in `crates/paimon/src/table/read_builder.rs`. It's just not exposed
through `bindings/python` (`PyTable` only has `identifier/location/schema`).
Goal: expose the existing Rust read API to Python so the DataFrame read path can
optionally run on Rust. Initially this lands as a **basic, opt-in path behind a
config flag**, running alongside the pure-Python reader rather than replacing it,
so the Rust path can mature before it becomes a default. Write path is out of scope.
## Scope (incremental PRs)
This can be implemented incrementally:
- **PR 1** — Expose scan planning:
`new_read_builder()`, `with_projection()`, `with_limit()`, and
`new_scan().plan()` returning serializable splits.
- **PR 2** — Expose filter pushdown:
add `with_filter()` after the Python Predicate → Rust Predicate conversion
layer is defined.
- **PR 3** — Expose split → Arrow read:
`new_read().read(splits)` returning Arrow data backed by Rust `TableRead`.
- **PR 4** (in `apache/paimon`, `[python]`) — Wire PyPaimon's
`to_arrow` / `to_pandas` / `to_ray` to the Rust reader as an **opt-in path**
(config-gated), keeping the pure-Python reader as the default. Unsupported
capabilities error out rather than silently falling back.
PR 1–3 land here; PR 4 lands in the main repo once bindings are released.
### Notes
`with_filter()` is separated from the initial scan-planning PR because it
requires a dedicated Python Predicate → Rust Predicate conversion layer. PR 1
focuses on establishing the Python binding shape and serializable splits.
Design principle: in this model Rust both **plans and reads**.
`new_read().read(splits)` returns Arrow from the Rust `TableRead`, and splits
stay **opaque** on the Python side — a serializable transport token, not
something Python inspects or reads from. Exposing split internals would imply a
Rust-plans / Python-reads path, which is a different direction and out of scope
here.
### Solution
_No response_
### Anything else?
_No response_
### Willingness to contribute
- [x] I'm willing to submit a PR!
Guía de contribución
Línea de trabajo
Comienza con crates/paimon/src/table/read_builder.rs y el directorio bindings/python, donde PyTable actualmente solo expone identifier, location y schema. Implementa los bindings de planificación incremental de escaneos, filtrado y lectura de Arrow descritos en los PRs 1–3, manteniendo los splits opacos y serializables; se considera terminado cuando la API de lectura de Rust esté expuesta sin cambiar el lector predeterminado de Python.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- python, rust
- Área
- api, data-engineering
- Tipo de issue
- Nueva funcionalidad
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Estado de actividad
- Tranquilo
- Claridad
- Bastante claro
- Aptitud para principiantes
- 45/100