Files
lancedb/python/src/table.rs
BubbleCal 7ff6ec7fe3 feat: upgrade to lance v0.25.0-beta.5 (#2248)
- adds `loss` into the index stats for vector index
- now `optimize` can retrain the vector index

---------

Signed-off-by: BubbleCal <bubble-cal@outlook.com>
2025-03-21 10:12:23 -07:00

538 lines
18 KiB
Rust

// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
use arrow::{
datatypes::DataType,
ffi_stream::ArrowArrayStreamReader,
pyarrow::{FromPyArrow, ToPyArrow},
};
use lancedb::table::{
AddDataMode, ColumnAlteration, Duration, NewColumnTransform, OptimizeAction, OptimizeOptions,
Table as LanceDbTable,
};
use pyo3::{
exceptions::{PyKeyError, PyRuntimeError, PyValueError},
pyclass, pymethods,
types::{IntoPyDict, PyAnyMethods, PyDict, PyDictMethods},
Bound, FromPyObject, PyAny, PyRef, PyResult, Python,
};
use pyo3_async_runtimes::tokio::future_into_py;
use std::collections::HashMap;
use crate::{
error::PythonErrorExt,
index::{extract_index_params, IndexConfig},
query::Query,
};
/// Statistics about a compaction operation.
#[pyclass(get_all)]
#[derive(Clone, Debug)]
pub struct CompactionStats {
/// The number of fragments removed
pub fragments_removed: u64,
/// The number of new, compacted fragments added
pub fragments_added: u64,
/// The number of data files removed
pub files_removed: u64,
/// The number of new, compacted data files added
pub files_added: u64,
}
/// Statistics about a cleanup operation
#[pyclass(get_all)]
#[derive(Clone, Debug)]
pub struct RemovalStats {
/// The number of bytes removed
pub bytes_removed: u64,
/// The number of old versions removed
pub old_versions_removed: u64,
}
/// Statistics about an optimize operation
#[pyclass(get_all)]
#[derive(Clone, Debug)]
pub struct OptimizeStats {
/// Statistics about the compaction operation
pub compaction: CompactionStats,
/// Statistics about the removal operation
pub prune: RemovalStats,
}
#[pyclass]
pub struct Table {
// We keep a copy of the name to use if the inner table is dropped
name: String,
inner: Option<LanceDbTable>,
}
#[pymethods]
impl OptimizeStats {
pub fn __repr__(&self) -> String {
format!(
"OptimizeStats(compaction={:?}, prune={:?})",
self.compaction, self.prune
)
}
}
impl Table {
pub(crate) fn new(inner: LanceDbTable) -> Self {
Self {
name: inner.name().to_string(),
inner: Some(inner),
}
}
}
impl Table {
fn inner_ref(&self) -> PyResult<&LanceDbTable> {
self.inner
.as_ref()
.ok_or_else(|| PyRuntimeError::new_err(format!("Table {} is closed", self.name)))
}
}
#[pymethods]
impl Table {
pub fn name(&self) -> String {
self.name.clone()
}
/// Returns True if the table is open, False if it is closed.
pub fn is_open(&self) -> bool {
self.inner.is_some()
}
/// Closes the table, releasing any resources associated with it.
pub fn close(&mut self) {
self.inner.take();
}
pub fn schema(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let schema = inner.schema().await.infer_error()?;
Python::with_gil(|py| schema.to_pyarrow(py))
})
}
pub fn add<'a>(
self_: PyRef<'a, Self>,
data: Bound<'_, PyAny>,
mode: String,
) -> PyResult<Bound<'a, PyAny>> {
let batches = ArrowArrayStreamReader::from_pyarrow_bound(&data)?;
let mut op = self_.inner_ref()?.add(batches);
if mode == "append" {
op = op.mode(AddDataMode::Append);
} else if mode == "overwrite" {
op = op.mode(AddDataMode::Overwrite);
} else {
return Err(PyValueError::new_err(format!("Invalid mode: {}", mode)));
}
future_into_py(self_.py(), async move {
op.execute().await.infer_error()?;
Ok(())
})
}
pub fn delete(self_: PyRef<'_, Self>, condition: String) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.delete(&condition).await.infer_error()
})
}
#[pyo3(signature = (updates, r#where=None))]
pub fn update<'a>(
self_: PyRef<'a, Self>,
updates: &Bound<'_, PyDict>,
r#where: Option<String>,
) -> PyResult<Bound<'a, PyAny>> {
let mut op = self_.inner_ref()?.update();
if let Some(only_if) = r#where {
op = op.only_if(only_if);
}
for (column_name, value) in updates.into_iter() {
let column_name: String = column_name.extract()?;
let value: String = value.extract()?;
op = op.column(column_name, value);
}
future_into_py(self_.py(), async move {
op.execute().await.infer_error()?;
Ok(())
})
}
#[pyo3(signature = (filter=None))]
pub fn count_rows(
self_: PyRef<'_, Self>,
filter: Option<String>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.count_rows(filter).await.infer_error()
})
}
#[pyo3(signature = (column, index=None, replace=None))]
pub fn create_index<'a>(
self_: PyRef<'a, Self>,
column: String,
index: Option<Bound<'_, PyAny>>,
replace: Option<bool>,
) -> PyResult<Bound<'a, PyAny>> {
let index = extract_index_params(&index)?;
let mut op = self_.inner_ref()?.create_index(&[column], index);
if let Some(replace) = replace {
op = op.replace(replace);
}
future_into_py(self_.py(), async move {
op.execute().await.infer_error()?;
Ok(())
})
}
pub fn drop_index(self_: PyRef<'_, Self>, index_name: String) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.drop_index(&index_name).await.infer_error()?;
Ok(())
})
}
pub fn list_indices(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
Ok(inner
.list_indices()
.await
.infer_error()?
.into_iter()
.map(IndexConfig::from)
.collect::<Vec<_>>())
})
}
pub fn index_stats(self_: PyRef<'_, Self>, index_name: String) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let stats = inner.index_stats(&index_name).await.infer_error()?;
if let Some(stats) = stats {
Python::with_gil(|py| {
let dict = PyDict::new(py);
dict.set_item("num_indexed_rows", stats.num_indexed_rows)?;
dict.set_item("num_unindexed_rows", stats.num_unindexed_rows)?;
dict.set_item("index_type", stats.index_type.to_string())?;
if let Some(distance_type) = stats.distance_type {
dict.set_item("distance_type", distance_type.to_string())?;
}
if let Some(num_indices) = stats.num_indices {
dict.set_item("num_indices", num_indices)?;
}
if let Some(loss) = stats.loss {
dict.set_item("loss", loss)?;
}
Ok(Some(dict.unbind()))
})
} else {
Ok(None)
}
})
}
pub fn __repr__(&self) -> String {
match &self.inner {
None => format!("ClosedTable({})", self.name),
Some(inner) => inner.to_string(),
}
}
pub fn version(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(
self_.py(),
async move { inner.version().await.infer_error() },
)
}
pub fn list_versions(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let versions = inner.list_versions().await.infer_error()?;
let versions_as_dict = Python::with_gil(|py| {
versions
.iter()
.map(|v| {
let dict = PyDict::new(py);
dict.set_item("version", v.version).unwrap();
dict.set_item(
"timestamp",
v.timestamp.timestamp_nanos_opt().unwrap_or_default(),
)
.unwrap();
let tup: Vec<(&String, &String)> = v.metadata.iter().collect();
dict.set_item("metadata", tup.into_py_dict(py)?).unwrap();
Ok(dict.unbind())
})
.collect::<PyResult<Vec<_>>>()
});
versions_as_dict
})
}
pub fn checkout(self_: PyRef<'_, Self>, version: u64) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.checkout(version).await.infer_error()
})
}
pub fn checkout_latest(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.checkout_latest().await.infer_error()
})
}
pub fn restore(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(
self_.py(),
async move { inner.restore().await.infer_error() },
)
}
pub fn query(&self) -> Query {
Query::new(self.inner_ref().unwrap().query())
}
/// Optimize the on-disk data by compacting and pruning old data, for better performance.
#[pyo3(signature = (cleanup_since_ms=None, delete_unverified=None, retrain=None))]
pub fn optimize(
self_: PyRef<'_, Self>,
cleanup_since_ms: Option<u64>,
delete_unverified: Option<bool>,
retrain: Option<bool>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
let older_than = if let Some(ms) = cleanup_since_ms {
if ms > i64::MAX as u64 {
return Err(PyValueError::new_err(format!(
"cleanup_since_ms must be between {} and -{}",
i32::MAX,
i32::MAX
)));
}
Duration::try_milliseconds(ms as i64)
} else {
None
};
future_into_py(self_.py(), async move {
let compaction_stats = inner
.optimize(OptimizeAction::Compact {
options: lancedb::table::CompactionOptions::default(),
remap_options: None,
})
.await
.infer_error()?
.compaction
.unwrap();
let prune_stats = inner
.optimize(OptimizeAction::Prune {
older_than,
delete_unverified,
error_if_tagged_old_versions: None,
})
.await
.infer_error()?
.prune
.unwrap();
inner
.optimize(lancedb::table::OptimizeAction::Index(match retrain {
Some(true) => OptimizeOptions::retrain(),
_ => OptimizeOptions::default(),
}))
.await
.infer_error()?;
Ok(OptimizeStats {
compaction: CompactionStats {
files_added: compaction_stats.files_added as u64,
files_removed: compaction_stats.files_removed as u64,
fragments_added: compaction_stats.fragments_added as u64,
fragments_removed: compaction_stats.fragments_removed as u64,
},
prune: RemovalStats {
bytes_removed: prune_stats.bytes_removed,
old_versions_removed: prune_stats.old_versions,
},
})
})
}
pub fn execute_merge_insert<'a>(
self_: PyRef<'a, Self>,
data: Bound<'a, PyAny>,
parameters: MergeInsertParams,
) -> PyResult<Bound<'a, PyAny>> {
let batches: ArrowArrayStreamReader = ArrowArrayStreamReader::from_pyarrow_bound(&data)?;
let on = parameters.on.iter().map(|s| s.as_str()).collect::<Vec<_>>();
let mut builder = self_.inner_ref()?.merge_insert(&on);
if parameters.when_matched_update_all {
builder.when_matched_update_all(parameters.when_matched_update_all_condition);
}
if parameters.when_not_matched_insert_all {
builder.when_not_matched_insert_all();
}
if parameters.when_not_matched_by_source_delete {
builder
.when_not_matched_by_source_delete(parameters.when_not_matched_by_source_condition);
}
future_into_py(self_.py(), async move {
builder.execute(Box::new(batches)).await.infer_error()?;
Ok(())
})
}
pub fn uses_v2_manifest_paths(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner
.as_native()
.ok_or_else(|| PyValueError::new_err("This cannot be run on a remote table"))?
.uses_v2_manifest_paths()
.await
.infer_error()
})
}
pub fn migrate_manifest_paths_v2(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner
.as_native()
.ok_or_else(|| PyValueError::new_err("This cannot be run on a remote table"))?
.migrate_manifest_paths_v2()
.await
.infer_error()
})
}
pub fn add_columns(
self_: PyRef<'_, Self>,
definitions: Vec<(String, String)>,
) -> PyResult<Bound<'_, PyAny>> {
let definitions = NewColumnTransform::SqlExpressions(definitions);
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.add_columns(definitions, None).await.infer_error()?;
Ok(())
})
}
pub fn alter_columns<'a>(
self_: PyRef<'a, Self>,
alterations: Vec<Bound<PyDict>>,
) -> PyResult<Bound<'a, PyAny>> {
let alterations = alterations
.iter()
.map(|alteration| {
let path = alteration
.get_item("path")?
.ok_or_else(|| PyValueError::new_err("Missing path"))?
.extract()?;
let rename = {
// We prefer rename, but support name for backwards compatibility
let rename = if let Ok(Some(rename)) = alteration.get_item("rename") {
Some(rename)
} else {
alteration.get_item("name")?
};
rename.map(|name| name.extract()).transpose()?
};
let nullable = alteration
.get_item("nullable")?
.map(|val| val.extract())
.transpose()?;
let data_type = alteration
.get_item("data_type")?
.map(|val| DataType::from_pyarrow_bound(&val))
.transpose()?;
Ok(ColumnAlteration {
path,
rename,
nullable,
data_type,
})
})
.collect::<PyResult<Vec<_>>>()?;
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.alter_columns(&alterations).await.infer_error()?;
Ok(())
})
}
pub fn drop_columns(self_: PyRef<Self>, columns: Vec<String>) -> PyResult<Bound<PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let column_refs = columns.iter().map(String::as_str).collect::<Vec<&str>>();
inner.drop_columns(&column_refs).await.infer_error()?;
Ok(())
})
}
pub fn replace_field_metadata<'a>(
self_: PyRef<'a, Self>,
field_name: String,
metadata: &Bound<'_, PyDict>,
) -> PyResult<Bound<'a, PyAny>> {
let mut new_metadata = HashMap::<String, String>::new();
for (column_name, value) in metadata.into_iter() {
let key: String = column_name.extract()?;
let value: String = value.extract()?;
new_metadata.insert(key, value);
}
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let native_tbl = inner
.as_native()
.ok_or_else(|| PyValueError::new_err("This cannot be run on a remote table"))?;
let schema = native_tbl.manifest().await.infer_error()?.schema;
let field = schema
.field(&field_name)
.ok_or_else(|| PyKeyError::new_err(format!("Field {} not found", field_name)))?;
native_tbl
.replace_field_metadata(vec![(field.id as u32, new_metadata)])
.await
.infer_error()?;
Ok(())
})
}
}
#[derive(FromPyObject)]
#[pyo3(from_item_all)]
pub struct MergeInsertParams {
on: Vec<String>,
when_matched_update_all: bool,
when_matched_update_all_condition: Option<String>,
when_not_matched_insert_all: bool,
when_not_matched_by_source_delete: bool,
when_not_matched_by_source_condition: Option<String>,
}