Files
lancedb/python/src/permutation.rs
T
Jack Ye f39a7a4dd9 feat: support remote tables in the data loader (#3981)
`StreamingDataset`, `PermutationBuilder`, and `Permutation` now work
against a `RemoteTable` (LanceDB Cloud and Enterprise), which unblocks
benchmarking the loader against the enterprise cluster cache.

```python
db = lancedb.connect("db://my-db", api_key=..., host_override=...)
ds = StreamingDataset(db.open_table("training"), world_size=8, rank=r)
```

Rows are addressed by `_rowid` exactly as before —
`PermutationReader::load_batch` already built the same `_rowid IN (...)`
filter that `Table::take_row_ids` sends, so the loader's fetch was
always the take path. It just was never allowed to run.

### The guard

`PermutationBuilder.__init__` rejected anything without `_inner`, so a
`RemoteTable` raised `TypeError` before reaching the PyO3 layer — which
already unwraps one via `_table._inner`.

### A bounded schema lookup

`PermutationReader::output_schema` reads the schema off a query plan,
and building a plan on a remote table *executes* the query
(`create_plan` → `execute_query`). With no limit that is `k =
isize::MAX`, so asking a remote table for its output schema pulled the
whole table over HTTP and threw it away — once per assigned split, on
every epoch, since `StreamingDataset.__iter__` constructs a
`Permutation` per split.

One row rather than zero, deliberately: lance gates its limit node on
`self.limit.unwrap_or(0) > 0`, so `Some(0)` means *no limit*.

### Tables with an LSM write spec are refused

A permutation references rows by row id, and rows that have not been
flushed to the base table do not have one yet. The loader could read
around them, but they would then be missing from training with nothing
said about it, so the build refuses such a table up front instead of
half supporting it.

### Fallible identity construction

`PermutationReader::identity` resolved `inner_new` with `unwrap`. That
was near total against a local dataset, but construction counts the base
table — an HTTP round trip for a remote one — so a transient network or
auth failure became a panic across the PyO3 boundary.

### Tests

End-to-end `permutation_builder` and `StreamingDataset` runs against a
mock server, the former torch-free so it runs wherever the suite does,
plus a test that a build succeeds without an LSM write spec and is
refused once one is installed.
2026-08-21 13:45:39 -07:00

353 lines
11 KiB
Rust

// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
use std::sync::{Arc, Mutex};
use crate::{
arrow::RecordBatchStream, error::PythonErrorExt, runtime::future_into_py, table::Table,
};
use arrow::pyarrow::{PyArrowType, ToPyArrow};
use lancedb::{
dataloader::permutation::{
builder::{PermutationBuilder as LancePermutationBuilder, ShuffleStrategy},
reader::PermutationReader,
split::{SplitSizes, SplitStrategy},
},
query::Select,
};
use pyo3::{
Bound, PyAny, PyRef, PyRefMut, PyResult, Python,
exceptions::PyRuntimeError,
pyclass, pymethods,
types::{PyAnyMethods, PyDict, PyDictMethods, PyType},
};
fn table_from_py<'a>(table: Bound<'a, PyAny>) -> PyResult<Bound<'a, Table>> {
if table.hasattr("_inner")? {
Ok(table.getattr("_inner")?.cast_into::<Table>()?)
} else if table.hasattr("_table")? {
Ok(table
.getattr("_table")?
.getattr("_inner")?
.cast_into::<Table>()?)
} else {
Err(PyRuntimeError::new_err(
"Provided table does not appear to be a Table or RemoteTable instance",
))
}
}
/// Create a permutation builder for the given table
#[pyo3::pyfunction]
pub fn async_permutation_builder(table: Bound<'_, PyAny>) -> PyResult<PyAsyncPermutationBuilder> {
let table = table_from_py(table)?;
let inner_table = table.borrow().inner_ref()?.clone();
let inner_builder = LancePermutationBuilder::new(inner_table);
Ok(PyAsyncPermutationBuilder {
state: Arc::new(Mutex::new(PyAsyncPermutationBuilderState {
builder: Some(inner_builder),
})),
})
}
struct PyAsyncPermutationBuilderState {
builder: Option<LancePermutationBuilder>,
}
#[pyclass(name = "AsyncPermutationBuilder")]
pub struct PyAsyncPermutationBuilder {
state: Arc<Mutex<PyAsyncPermutationBuilderState>>,
}
impl PyAsyncPermutationBuilder {
fn modify(
&self,
func: impl FnOnce(LancePermutationBuilder) -> LancePermutationBuilder,
) -> PyResult<Self> {
let mut state = self.state.lock().unwrap();
let builder = state
.builder
.take()
.ok_or_else(|| PyRuntimeError::new_err("Builder already consumed"))?;
state.builder = Some(func(builder));
Ok(Self {
state: self.state.clone(),
})
}
}
#[pymethods]
impl PyAsyncPermutationBuilder {
#[pyo3(signature = (*, ratios=None, counts=None, fixed=None, seed=None, clump_size=None, split_names=None))]
pub fn split_random(
slf: PyRefMut<'_, Self>,
ratios: Option<Vec<f64>>,
counts: Option<Vec<u64>>,
fixed: Option<u64>,
seed: Option<u64>,
clump_size: Option<u64>,
split_names: Option<Vec<String>>,
) -> PyResult<Self> {
// Check that exactly one split type is provided
let split_args_count = [ratios.is_some(), counts.is_some(), fixed.is_some()]
.iter()
.filter(|&&x| x)
.count();
if split_args_count != 1 {
return Err(pyo3::exceptions::PyValueError::new_err(
"Exactly one of 'ratios', 'counts', or 'fixed' must be provided",
));
}
let sizes = if let Some(ratios) = ratios {
SplitSizes::Percentages(ratios)
} else if let Some(counts) = counts {
SplitSizes::Counts(counts)
} else if let Some(fixed) = fixed {
SplitSizes::Fixed(fixed)
} else {
unreachable!("One of the split arguments must be provided");
};
slf.modify(|builder| {
builder.with_split_strategy(
SplitStrategy::Random {
seed,
sizes,
clump_size,
},
split_names,
)
})
}
#[pyo3(signature = (columns, split_weights, *, discard_weight=0, split_names=None))]
pub fn split_hash(
slf: PyRefMut<'_, Self>,
columns: Vec<String>,
split_weights: Vec<u64>,
discard_weight: u64,
split_names: Option<Vec<String>>,
) -> PyResult<Self> {
slf.modify(|builder| {
builder.with_split_strategy(
SplitStrategy::Hash {
columns,
split_weights,
discard_weight,
},
split_names,
)
})
}
#[pyo3(signature = (*, ratios=None, counts=None, fixed=None, split_names=None))]
pub fn split_sequential(
slf: PyRefMut<'_, Self>,
ratios: Option<Vec<f64>>,
counts: Option<Vec<u64>>,
fixed: Option<u64>,
split_names: Option<Vec<String>>,
) -> PyResult<Self> {
// Check that exactly one split type is provided
let split_args_count = [ratios.is_some(), counts.is_some(), fixed.is_some()]
.iter()
.filter(|&&x| x)
.count();
if split_args_count != 1 {
return Err(pyo3::exceptions::PyValueError::new_err(
"Exactly one of 'ratios', 'counts', or 'fixed' must be provided",
));
}
let sizes = if let Some(ratios) = ratios {
SplitSizes::Percentages(ratios)
} else if let Some(counts) = counts {
SplitSizes::Counts(counts)
} else if let Some(fixed) = fixed {
SplitSizes::Fixed(fixed)
} else {
unreachable!("One of the split arguments must be provided");
};
slf.modify(|builder| {
builder.with_split_strategy(SplitStrategy::Sequential { sizes }, split_names)
})
}
pub fn split_calculated(
slf: PyRefMut<'_, Self>,
calculation: String,
split_names: Option<Vec<String>>,
) -> PyResult<Self> {
slf.modify(|builder| {
builder.with_split_strategy(SplitStrategy::Calculated { calculation }, split_names)
})
}
pub fn shuffle(
slf: PyRefMut<'_, Self>,
seed: Option<u64>,
clump_size: Option<u64>,
) -> PyResult<Self> {
slf.modify(|builder| {
builder.with_shuffle_strategy(ShuffleStrategy::Random { seed, clump_size })
})
}
pub fn filter(slf: PyRefMut<'_, Self>, filter: String) -> PyResult<Self> {
slf.modify(|builder| builder.with_filter(filter))
}
pub fn execute(slf: PyRefMut<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let mut state = slf.state.lock().unwrap();
let builder = state
.builder
.take()
.ok_or_else(|| PyRuntimeError::new_err("Builder already consumed"))?;
future_into_py(slf.py(), async move {
let table = builder.build().await.infer_error()?;
Ok(Table::new(table))
})
}
}
#[pyclass(name = "PermutationReader")]
pub struct PyPermutationReader {
reader: Arc<PermutationReader>,
}
impl PyPermutationReader {
fn from_reader(reader: PermutationReader) -> Self {
Self {
reader: Arc::new(reader),
}
}
fn parse_selection(selection: Option<Bound<'_, PyAny>>) -> PyResult<Select> {
let Some(selection) = selection else {
return Ok(Select::All);
};
let selection = selection.cast_into::<PyDict>()?;
let selection = selection
.iter()
.map(|(key, value)| {
let key = key.extract::<String>()?;
let value = value.extract::<String>()?;
Ok((key, value))
})
.collect::<PyResult<Vec<_>>>()?;
Ok(Select::dynamic(&selection))
}
}
#[pymethods]
impl PyPermutationReader {
#[classmethod]
pub fn from_tables<'py>(
cls: &Bound<'py, PyType>,
base_table: Bound<'py, PyAny>,
permutation_table: Option<Bound<'py, PyAny>>,
split: u64,
) -> PyResult<Bound<'py, PyAny>> {
let base_table = table_from_py(base_table)?;
let permutation_table = permutation_table.map(table_from_py).transpose()?;
let base_table = base_table.borrow().inner_ref()?.base_table().clone();
let permutation_table = permutation_table
.map(|p| PyResult::Ok(p.borrow().inner_ref()?.base_table().clone()))
.transpose()?;
future_into_py(cls.py(), async move {
let reader = if let Some(permutation_table) = permutation_table {
PermutationReader::try_from_tables(base_table, permutation_table, split)
.await
.infer_error()?
} else {
PermutationReader::identity(base_table)
.await
.infer_error()?
};
Ok(Self::from_reader(reader))
})
}
#[pyo3(signature = (selection=None))]
pub fn output_schema<'py>(
slf: PyRef<'py, Self>,
selection: Option<Bound<'py, PyAny>>,
) -> PyResult<Bound<'py, PyAny>> {
let selection = Self::parse_selection(selection)?;
let reader = slf.reader.clone();
future_into_py(slf.py(), async move {
let schema = reader.output_schema(selection).await.infer_error()?;
Python::attach(|py| schema.to_pyarrow(py).map(|obj| obj.unbind()))
})
}
#[pyo3(signature = ())]
pub fn count_rows<'py>(slf: PyRef<'py, Self>) -> u64 {
slf.reader.count_rows()
}
#[pyo3(signature = (offset))]
pub fn with_offset<'py>(slf: PyRef<'py, Self>, offset: u64) -> PyResult<Bound<'py, PyAny>> {
let reader = slf.reader.as_ref().clone();
future_into_py(slf.py(), async move {
let reader = reader.with_offset(offset).await.infer_error()?;
Ok(Self::from_reader(reader))
})
}
#[pyo3(signature = (limit))]
pub fn with_limit<'py>(slf: PyRef<'py, Self>, limit: u64) -> PyResult<Bound<'py, PyAny>> {
let reader = slf.reader.as_ref().clone();
future_into_py(slf.py(), async move {
let reader = reader.with_limit(limit).await.infer_error()?;
Ok(Self::from_reader(reader))
})
}
#[pyo3(signature = (selection=None, *, batch_size=None))]
pub fn read<'py>(
slf: PyRef<'py, Self>,
selection: Option<Bound<'py, PyAny>>,
batch_size: Option<u32>,
) -> PyResult<Bound<'py, PyAny>> {
let selection = Self::parse_selection(selection)?;
let reader = slf.reader.clone();
let batch_size = batch_size.unwrap_or(1024);
future_into_py(slf.py(), async move {
use lancedb::query::QueryExecutionOptions;
let mut execution_options = QueryExecutionOptions::default();
execution_options.max_batch_length = batch_size;
let stream = reader
.read(selection, execution_options)
.await
.infer_error()?;
Ok(RecordBatchStream::new(stream))
})
}
#[pyo3(signature = (indices, *, selection=None))]
pub fn take_offsets<'py>(
slf: PyRef<'py, Self>,
indices: Vec<u64>,
selection: Option<Bound<'py, PyAny>>,
) -> PyResult<Bound<'py, PyAny>> {
let selection = Self::parse_selection(selection)?;
let reader = slf.reader.clone();
future_into_py(slf.py(), async move {
let batch = reader
.take_offsets(&indices, selection)
.await
.infer_error()?;
Ok(PyArrowType(batch))
})
}
}