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synced 2026-09-04 12:38:38 +00:00
Compare commits
7 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| e0d6b9a4fa | |||
| 845868a343 | |||
| cc321e9801 | |||
| 7357d63e87 | |||
| 624a75edf7 | |||
| c7ea91f3ea | |||
| 8e24dd3828 |
Generated
+9
-8
@@ -5442,6 +5442,7 @@ dependencies = [
|
||||
"pprof 0.14.1",
|
||||
"rand 0.9.5",
|
||||
"random_word",
|
||||
"rayon",
|
||||
"regex",
|
||||
"reqwest 0.12.28",
|
||||
"rstest",
|
||||
@@ -7583,7 +7584,7 @@ version = "0.14.3"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "343d3bd7056eda839b03204e68deff7d1b13aba7af2b2fd16890697274262ee7"
|
||||
dependencies = [
|
||||
"heck 0.5.0",
|
||||
"heck 0.4.1",
|
||||
"itertools 0.14.0",
|
||||
"log",
|
||||
"multimap",
|
||||
@@ -8498,9 +8499,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "rkyv"
|
||||
version = "0.8.16"
|
||||
version = "0.8.17"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "73389e0c99e664f919275ab5b5b0471391fe9a8de61e1dff9b1eaf56a90f16e3"
|
||||
checksum = "815cc8a37159a463064825246cadb07961e25cd9885908606f6d08a98d8f8874"
|
||||
dependencies = [
|
||||
"bytecheck",
|
||||
"bytes",
|
||||
@@ -8517,9 +8518,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "rkyv_derive"
|
||||
version = "0.8.16"
|
||||
version = "0.8.17"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "5d2ed0b54125315fb36bd021e82d314d1c126548f871634b483f46b31d13cac6"
|
||||
checksum = "c0ed1a78a1b19d184b0daa629dd9a024573173ec7d485b287cb369fb3607cc1c"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
@@ -9277,7 +9278,7 @@ version = "0.8.9"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "c1c97747dbf44bb1ca44a561ece23508e99cb592e862f22222dcf42f51d1e451"
|
||||
dependencies = [
|
||||
"heck 0.5.0",
|
||||
"heck 0.4.1",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.117",
|
||||
@@ -9289,7 +9290,7 @@ version = "0.9.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "54254b8531cafa275c5e096f62d48c81435d1015405a91198ddb11e967301d40"
|
||||
dependencies = [
|
||||
"heck 0.5.0",
|
||||
"heck 0.4.1",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.117",
|
||||
@@ -9730,7 +9731,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "32497e9a4c7b38532efcdebeef879707aa9f794296a4f0244f6f69e9bc8574bd"
|
||||
dependencies = [
|
||||
"fastrand",
|
||||
"getrandom 0.4.2",
|
||||
"getrandom 0.3.4",
|
||||
"once_cell",
|
||||
"rustix",
|
||||
"windows-sys 0.61.2",
|
||||
|
||||
@@ -60,6 +60,7 @@ moka = { version = "0.12", features = ["future"] }
|
||||
object_store = "0.13.2"
|
||||
pin-project = "1.0.7"
|
||||
rand = "0.9"
|
||||
rayon = "1"
|
||||
snafu = "0.8"
|
||||
url = "2"
|
||||
num-traits = "0.2"
|
||||
|
||||
+6
-2
@@ -339,7 +339,9 @@ impl Table {
|
||||
let transforms = NewColumnTransform::SqlExpressions(transforms);
|
||||
let res = self
|
||||
.inner_ref()?
|
||||
.add_columns(transforms, None)
|
||||
.add_columns()
|
||||
.transform(transforms)
|
||||
.execute()
|
||||
.await
|
||||
.default_error()?;
|
||||
Ok(res.into())
|
||||
@@ -356,7 +358,9 @@ impl Table {
|
||||
let transforms = NewColumnTransform::AllNulls(schema);
|
||||
let res = self
|
||||
.inner_ref()?
|
||||
.add_columns(transforms, None)
|
||||
.add_columns()
|
||||
.transform(transforms)
|
||||
.execute()
|
||||
.await
|
||||
.default_error()?;
|
||||
Ok(res.into())
|
||||
|
||||
@@ -707,6 +707,9 @@ class LanceDBConnection(DBConnection):
|
||||
self._namespace_client_properties = namespace_client_properties
|
||||
if _inner is not None:
|
||||
self._conn = _inner
|
||||
# Native-derived wrappers resolve this in their async reconstruction
|
||||
# path so construction never synchronously re-enters LOOP.
|
||||
self._read_consistency_interval = read_consistency_interval
|
||||
self._cached_namespace_client = None
|
||||
return
|
||||
|
||||
@@ -756,11 +759,14 @@ class LanceDBConnection(DBConnection):
|
||||
# storage_options. Also, this class really shouldn't be holding any state
|
||||
# beyond _conn.
|
||||
self._conn = AsyncConnection(LOOP.run(do_connect()))
|
||||
# Keep property access synchronous so debugger introspection cannot wait on
|
||||
# the background loop while that thread is suspended at a breakpoint.
|
||||
self._read_consistency_interval = read_consistency_interval
|
||||
self._cached_namespace_client: Optional[LanceNamespace] = None
|
||||
|
||||
@property
|
||||
def read_consistency_interval(self) -> Optional[timedelta]:
|
||||
return LOOP.run(self._conn.get_read_consistency_interval())
|
||||
return self._read_consistency_interval
|
||||
|
||||
@property
|
||||
def session(self) -> Optional[Session]:
|
||||
@@ -771,8 +777,16 @@ class LanceDBConnection(DBConnection):
|
||||
return self._conn.uri
|
||||
|
||||
@classmethod
|
||||
def from_inner(cls, inner: LanceDbConnection):
|
||||
return cls(None, _inner=inner)
|
||||
def from_inner(
|
||||
cls,
|
||||
inner: LanceDbConnection,
|
||||
read_consistency_interval: Optional[timedelta],
|
||||
):
|
||||
return cls(
|
||||
None,
|
||||
read_consistency_interval=read_consistency_interval,
|
||||
_inner=inner,
|
||||
)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
return f"{self.__class__.__name__}(uri={self._conn.uri!r})"
|
||||
|
||||
@@ -769,6 +769,13 @@ class IvfPq:
|
||||
|
||||
The default value is 256.
|
||||
|
||||
seed: int, optional
|
||||
Seed used for deterministic sampling and training. Given identical data in
|
||||
the same row order and identical index parameters, the same seed produces
|
||||
the same IVF centroids and PQ codebook. This option is supported for local
|
||||
CPU index builds; remote and accelerator builds reject it explicitly. If
|
||||
omitted, training remains random.
|
||||
|
||||
target_partition_size: int, default is 8192
|
||||
|
||||
The target size of each partition.
|
||||
@@ -783,11 +790,18 @@ class IvfPq:
|
||||
num_bits: int = 8
|
||||
max_iterations: int = 50
|
||||
sample_rate: int = 256
|
||||
seed: Optional[int] = None
|
||||
target_partition_size: Optional[int] = None
|
||||
# Name of the accelerator (e.g. "cuda") to use for IVF training. When set,
|
||||
# create_index() dispatches to pylance to build the index on the accelerator.
|
||||
accelerator: Optional[str] = None
|
||||
|
||||
def __post_init__(self):
|
||||
if self.seed is not None and self.accelerator is not None:
|
||||
raise ValueError(
|
||||
"IvfPq seed is not supported with accelerator-based index training"
|
||||
)
|
||||
|
||||
|
||||
@dataclass
|
||||
class IvfRq:
|
||||
|
||||
@@ -226,7 +226,7 @@ class PermutationBuilder:
|
||||
|
||||
async def do_execute():
|
||||
inner_tbl = await self._async.execute()
|
||||
return LanceTable.from_inner(inner_tbl)
|
||||
return await LanceTable.from_inner(inner_tbl)
|
||||
|
||||
return LOOP.run(do_execute())
|
||||
|
||||
|
||||
@@ -2182,11 +2182,15 @@ class LanceTable(Table):
|
||||
return self.name
|
||||
|
||||
@classmethod
|
||||
def from_inner(cls, tbl: LanceDBTable):
|
||||
from .db import LanceDBConnection
|
||||
async def from_inner(cls, tbl: LanceDBTable):
|
||||
from .db import AsyncConnection, LanceDBConnection
|
||||
|
||||
async_tbl = AsyncTable(tbl)
|
||||
conn = LanceDBConnection.from_inner(tbl.database())
|
||||
inner_conn = tbl.database()
|
||||
read_consistency_interval = await AsyncConnection(
|
||||
inner_conn
|
||||
).get_read_consistency_interval()
|
||||
conn = LanceDBConnection.from_inner(inner_conn, read_consistency_interval)
|
||||
return cls(
|
||||
conn,
|
||||
async_tbl.name,
|
||||
@@ -2758,6 +2762,11 @@ class LanceTable(Table):
|
||||
if config is not None and hasattr(config, "accelerator"):
|
||||
acc = getattr(config, "accelerator", None)
|
||||
if acc is not None:
|
||||
if isinstance(config, IvfPq) and config.seed is not None:
|
||||
raise ValueError(
|
||||
"IvfPq seed is not supported with accelerator-based "
|
||||
"index training"
|
||||
)
|
||||
# Dispatch to pylance for GPU acceleration
|
||||
index_type_map = {
|
||||
"IvfFlat": "IVF_FLAT",
|
||||
|
||||
@@ -77,6 +77,23 @@ def test_sync_repr_does_not_use_background_loop(tmp_path, monkeypatch):
|
||||
assert repr(table) == f"LanceTable(name='test', _conn={db!r})"
|
||||
|
||||
|
||||
def test_read_consistency_interval_does_not_use_background_loop(tmp_path, monkeypatch):
|
||||
from lancedb.background_loop import LOOP
|
||||
from lancedb.db import LanceDBConnection
|
||||
|
||||
consistency_interval = timedelta(seconds=5)
|
||||
db = lancedb.connect(tmp_path, read_consistency_interval=consistency_interval)
|
||||
db_from_inner = LanceDBConnection.from_inner(db._inner, consistency_interval)
|
||||
|
||||
def fail_run(*args, **kwargs):
|
||||
raise AssertionError("properties should not use the Python background loop")
|
||||
|
||||
monkeypatch.setattr(LOOP, "run", fail_run)
|
||||
|
||||
assert db.read_consistency_interval == consistency_interval
|
||||
assert db_from_inner.read_consistency_interval == consistency_interval
|
||||
|
||||
|
||||
def test_ingest_pd(tmp_path):
|
||||
db = lancedb.connect(tmp_path)
|
||||
|
||||
|
||||
@@ -26,7 +26,7 @@ from lancedb.index import (
|
||||
HnswFlat,
|
||||
FTS,
|
||||
)
|
||||
from lancedb.table import IndexStatistics
|
||||
from lancedb.table import IndexStatistics, LanceTable
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
@@ -375,7 +375,7 @@ async def test_create_vector_index(some_table: AsyncTable):
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_4bit_ivfpq_index(some_table: AsyncTable):
|
||||
# Can create
|
||||
await some_table.create_index("vector", config=IvfPq(num_bits=4))
|
||||
await some_table.create_index("vector", config=IvfPq(num_bits=4, seed=42))
|
||||
# Can recreate if replace=True
|
||||
await some_table.create_index("vector", config=IvfPq(num_bits=4), replace=True)
|
||||
# Can't recreate if replace=False
|
||||
@@ -395,6 +395,16 @@ async def test_create_4bit_ivfpq_index(some_table: AsyncTable):
|
||||
assert stats.num_indices == 1
|
||||
|
||||
|
||||
def test_seeded_ivfpq_rejects_accelerator():
|
||||
with pytest.raises(ValueError, match="seed is not supported with accelerator"):
|
||||
IvfPq(seed=42, accelerator="cuda")
|
||||
|
||||
config = IvfPq(seed=42)
|
||||
config.accelerator = "cuda"
|
||||
with pytest.raises(ValueError, match="seed is not supported with accelerator"):
|
||||
object.__new__(LanceTable).create_index("vector", config=config)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_ivfrq_index(some_table: AsyncTable):
|
||||
await some_table.create_index("vector", config=IvfRq(num_bits=1))
|
||||
|
||||
@@ -6,6 +6,7 @@ import math
|
||||
import pytest
|
||||
|
||||
from lancedb import DBConnection, Table, connect
|
||||
from lancedb.background_loop import LOOP
|
||||
from lancedb.permutation import Permutation, Permutations, permutation_builder
|
||||
|
||||
|
||||
@@ -31,6 +32,25 @@ def test_split_random_ratios(mem_db):
|
||||
assert 65 <= split_1_count <= 75 # ~70% ± tolerance
|
||||
|
||||
|
||||
def test_execute_does_not_reenter_background_loop(tmp_path, monkeypatch):
|
||||
import threading
|
||||
|
||||
db = connect(tmp_path)
|
||||
tbl = db.create_table("test_table", pa.table({"x": range(10)}))
|
||||
original_run = LOOP.run
|
||||
|
||||
def fail_on_reentry(future):
|
||||
assert threading.current_thread() is not LOOP.thread
|
||||
return original_run(future)
|
||||
|
||||
monkeypatch.setattr(LOOP, "run", fail_on_reentry)
|
||||
|
||||
permutation_tbl = permutation_builder(tbl).execute()
|
||||
|
||||
assert permutation_tbl.count_rows() == 10
|
||||
assert permutation_tbl._conn.read_consistency_interval is None
|
||||
|
||||
|
||||
def test_split_random_counts(mem_db):
|
||||
"""Test random splitting with absolute counts."""
|
||||
tbl = mem_db.create_table(
|
||||
|
||||
@@ -6,6 +6,7 @@ import os
|
||||
import sys
|
||||
import threading
|
||||
import warnings
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from datetime import date, datetime, timedelta
|
||||
from time import sleep
|
||||
from typing import List
|
||||
@@ -2124,6 +2125,27 @@ def test_delete(mem_db: DBConnection):
|
||||
assert table.to_arrow()["id"].to_pylist() == [1]
|
||||
|
||||
|
||||
def test_concurrent_deletes_are_thread_safe(mem_db: DBConnection):
|
||||
num_workers = 8
|
||||
table = mem_db.create_table(
|
||||
"my_table", data=[{"id": row_id} for row_id in range(num_workers)]
|
||||
)
|
||||
barrier = threading.Barrier(num_workers)
|
||||
|
||||
def delete(row_id: int):
|
||||
barrier.wait()
|
||||
return table.delete(f"id = {row_id}")
|
||||
|
||||
with ThreadPoolExecutor(max_workers=num_workers) as pool:
|
||||
results = list(pool.map(delete, range(num_workers)))
|
||||
|
||||
assert all(result.num_deleted_rows == 1 for result in results)
|
||||
assert sorted(result.version for result in results) == list(
|
||||
range(2, num_workers + 2)
|
||||
)
|
||||
assert table.count_rows() == 0
|
||||
|
||||
|
||||
def test_delete_expr(mem_db: DBConnection):
|
||||
table = mem_db.create_table(
|
||||
"my_table",
|
||||
|
||||
@@ -90,6 +90,9 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
|
||||
.max_iterations(params.max_iterations)
|
||||
.sample_rate(params.sample_rate)
|
||||
.num_bits(params.num_bits);
|
||||
if let Some(seed) = params.seed {
|
||||
ivf_pq_builder = ivf_pq_builder.seed(seed);
|
||||
}
|
||||
if let Some(num_partitions) = params.num_partitions {
|
||||
ivf_pq_builder = ivf_pq_builder.num_partitions(num_partitions);
|
||||
}
|
||||
@@ -232,6 +235,7 @@ struct IvfPqParams {
|
||||
num_bits: u32,
|
||||
max_iterations: u32,
|
||||
sample_rate: u32,
|
||||
seed: Option<u64>,
|
||||
target_partition_size: Option<u32>,
|
||||
}
|
||||
|
||||
|
||||
+15
-2
@@ -745,6 +745,9 @@ impl Table {
|
||||
|
||||
#[allow(private_interfaces)]
|
||||
pub fn delete(self_: PyRef<'_, Self>, condition: PredicateArg) -> PyResult<Bound<'_, PyAny>> {
|
||||
// Do not hold the Python borrow across the await. The cloned Rust table
|
||||
// handle is thread-safe and allows deletes on the same Python table to
|
||||
// run concurrently without PyO3 reporting "Already borrowed".
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
let result = match &condition {
|
||||
@@ -1375,7 +1378,12 @@ impl Table {
|
||||
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
let result = inner.add_columns(definitions, None).await.infer_error()?;
|
||||
let result = inner
|
||||
.add_columns()
|
||||
.transform(definitions)
|
||||
.execute()
|
||||
.await
|
||||
.infer_error()?;
|
||||
Ok(AddColumnsResult::from(result))
|
||||
})
|
||||
}
|
||||
@@ -1389,7 +1397,12 @@ impl Table {
|
||||
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
let result = inner.add_columns(transform, None).await.infer_error()?;
|
||||
let result = inner
|
||||
.add_columns()
|
||||
.transform(transform)
|
||||
.execute()
|
||||
.await
|
||||
.infer_error()?;
|
||||
Ok(AddColumnsResult::from(result))
|
||||
})
|
||||
}
|
||||
|
||||
@@ -61,6 +61,7 @@ futures.workspace = true
|
||||
num-traits.workspace = true
|
||||
url.workspace = true
|
||||
rand.workspace = true
|
||||
rayon.workspace = true
|
||||
regex.workspace = true
|
||||
serde = { version = "^1" }
|
||||
serde_json = { version = "1" }
|
||||
|
||||
@@ -274,6 +274,8 @@ pub struct IvfPqIndexBuilder {
|
||||
pub(crate) sample_rate: u32,
|
||||
pub(crate) max_iterations: u32,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub(crate) seed: Option<u64>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub(crate) target_partition_size: Option<u32>,
|
||||
|
||||
// PQ
|
||||
@@ -292,6 +294,7 @@ impl Default for IvfPqIndexBuilder {
|
||||
num_bits: None,
|
||||
sample_rate: 256,
|
||||
max_iterations: 50,
|
||||
seed: None,
|
||||
target_partition_size: None,
|
||||
}
|
||||
}
|
||||
@@ -301,6 +304,30 @@ impl IvfPqIndexBuilder {
|
||||
impl_distance_type_setter!();
|
||||
impl_ivf_params_setter!();
|
||||
impl_pq_params_setter!();
|
||||
|
||||
/// Use a deterministic seed when sampling and training the IVF and PQ models.
|
||||
///
|
||||
/// Given identical data in the same row order and identical index parameters,
|
||||
/// using the same seed produces the same IVF centroids and PQ codebook. This is
|
||||
/// useful when independently-built tables need reproducible approximate-search
|
||||
/// results.
|
||||
///
|
||||
/// Seeded training is supported by native tables. Remote backends reject this
|
||||
/// option unless they can provide the same deterministic training contract.
|
||||
///
|
||||
/// If no seed is provided, index training uses random sampling and initialization.
|
||||
///
|
||||
/// # Examples
|
||||
///
|
||||
/// ```
|
||||
/// use lancedb::index::vector::IvfPqIndexBuilder;
|
||||
///
|
||||
/// let index = IvfPqIndexBuilder::default().seed(42);
|
||||
/// ```
|
||||
pub fn seed(mut self, seed: u64) -> Self {
|
||||
self.seed = Some(seed);
|
||||
self
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn suggested_num_sub_vectors(dim: u32) -> u32 {
|
||||
|
||||
@@ -339,6 +339,12 @@ impl<S: HttpSend> RemoteTable<S> {
|
||||
// Auto is special-cased since it needs schema inspection.
|
||||
let (index_type_str, params) = match &index.index {
|
||||
Index::IvfFlat(p) => ("IVF_FLAT", Some(to_json(p)?)),
|
||||
Index::IvfPq(p) if p.seed.is_some() => {
|
||||
return Err(Error::NotSupported {
|
||||
message: "Deterministic IVF PQ training is not supported on remote tables"
|
||||
.to_string(),
|
||||
});
|
||||
}
|
||||
Index::IvfPq(p) => ("IVF_PQ", Some(to_json(p)?)),
|
||||
Index::IvfSq(p) => ("IVF_SQ", Some(to_json(p)?)),
|
||||
Index::IvfHnswSq(p) => ("IVF_HNSW_SQ", Some(to_json(p)?)),
|
||||
@@ -3089,10 +3095,12 @@ mod tests {
|
||||
Box::pin(table.delete("false").map_ok(|_| ())),
|
||||
Box::pin(
|
||||
table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("x".into(), "y".into())]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"x".into(),
|
||||
"y".into(),
|
||||
)]))
|
||||
.execute()
|
||||
.map_ok(|_| ()),
|
||||
),
|
||||
Box::pin(async {
|
||||
@@ -5155,6 +5163,41 @@ mod tests {
|
||||
}
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_seeded_ivf_pq_is_rejected_for_remote_tables() {
|
||||
let table = Table::new_with_handler("my_table", |request| match request.url().path() {
|
||||
"/v1/table/my_table/describe/" => {
|
||||
let schema = Schema::new(vec![Field::new(
|
||||
"vector",
|
||||
DataType::FixedSizeList(
|
||||
Arc::new(Field::new("item", DataType::Float32, true)),
|
||||
8,
|
||||
),
|
||||
false,
|
||||
)]);
|
||||
http::Response::builder()
|
||||
.status(200)
|
||||
.body(describe_response(&schema))
|
||||
.unwrap()
|
||||
}
|
||||
path => panic!("Unexpected request for unsupported seeded index: {path}"),
|
||||
});
|
||||
|
||||
let error = table
|
||||
.create_index(
|
||||
&["vector"],
|
||||
Index::IvfPq(IvfPqIndexBuilder::default().seed(42)),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap_err();
|
||||
assert!(matches!(
|
||||
error,
|
||||
Error::NotSupported { message }
|
||||
if message.contains("not supported on remote tables")
|
||||
));
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_index_returns_job() {
|
||||
let describe_calls = std::sync::Arc::new(std::sync::atomic::AtomicUsize::new(0));
|
||||
@@ -6388,13 +6431,12 @@ mod tests {
|
||||
});
|
||||
|
||||
let result = table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![
|
||||
("b".into(), "a + 1".into()),
|
||||
("x".into(), "cast(NULL as int32)".into()),
|
||||
]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![
|
||||
("b".into(), "a + 1".into()),
|
||||
("x".into(), "cast(NULL as int32)".into()),
|
||||
]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -7119,10 +7161,12 @@ mod tests {
|
||||
}
|
||||
"add_columns" => {
|
||||
let _ = table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("c".into(), "a + 1".into())]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"c".into(),
|
||||
"a + 1".into(),
|
||||
)]))
|
||||
.execute()
|
||||
.await;
|
||||
}
|
||||
"drop_columns" => {
|
||||
@@ -9880,10 +9924,12 @@ mod tests {
|
||||
.await
|
||||
.unwrap();
|
||||
branch
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("b".into(), "a + 1".into())]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"b".into(),
|
||||
"a + 1".into(),
|
||||
)]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
branch
|
||||
|
||||
@@ -65,6 +65,7 @@ use crate::utils::{PatchReadParam, PatchWriteParam, resolve_arrow_field_path};
|
||||
use self::dataset::DatasetConsistencyWrapper;
|
||||
use self::merge::MergeInsertBuilder;
|
||||
|
||||
pub mod add_columns;
|
||||
mod add_data;
|
||||
pub mod branch_merge;
|
||||
mod create_index;
|
||||
@@ -79,6 +80,7 @@ pub mod schema_evolution;
|
||||
pub mod update;
|
||||
pub mod write_progress;
|
||||
use crate::index::waiter::wait_for_index;
|
||||
pub use add_columns::AddColumnsBuilder;
|
||||
#[cfg(feature = "remote")]
|
||||
pub(crate) use add_data::PreprocessingOutput;
|
||||
pub use add_data::{AddDataBuilder, AddDataMode, AddResult, NaNVectorBehavior};
|
||||
@@ -1620,12 +1622,8 @@ impl Table {
|
||||
}
|
||||
|
||||
/// Add new columns to the table, providing values to fill in.
|
||||
pub async fn add_columns(
|
||||
&self,
|
||||
transforms: NewColumnTransform,
|
||||
read_columns: Option<Vec<String>>,
|
||||
) -> Result<AddColumnsResult> {
|
||||
self.inner.add_columns(transforms, read_columns).await
|
||||
pub fn add_columns(&self) -> AddColumnsBuilder {
|
||||
AddColumnsBuilder::new(self.inner.clone())
|
||||
}
|
||||
|
||||
/// Change a column's name or nullability.
|
||||
|
||||
@@ -0,0 +1,161 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
//! Builder for adding columns to a table.
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
use lance::dataset::NewColumnTransform;
|
||||
|
||||
use super::BaseTable;
|
||||
use super::schema_evolution::AddColumnsResult;
|
||||
use crate::{Error, Result};
|
||||
|
||||
/// Adds columns to a table. See [`Table::add_columns`](super::Table::add_columns).
|
||||
pub struct AddColumnsBuilder {
|
||||
parent: Arc<dyn BaseTable>,
|
||||
transform: Option<NewColumnTransform>,
|
||||
read_columns: Option<Vec<String>>,
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for AddColumnsBuilder {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.debug_struct("AddColumnsBuilder")
|
||||
.field("parent", &self.parent)
|
||||
.field("has_transform", &self.transform.is_some())
|
||||
.field("read_columns", &self.read_columns)
|
||||
.finish()
|
||||
}
|
||||
}
|
||||
|
||||
impl AddColumnsBuilder {
|
||||
pub(crate) fn new(parent: Arc<dyn BaseTable>) -> Self {
|
||||
Self {
|
||||
parent,
|
||||
transform: None,
|
||||
read_columns: None,
|
||||
}
|
||||
}
|
||||
|
||||
/// Set how the new columns' values are produced. Required.
|
||||
pub fn transform(mut self, transform: NewColumnTransform) -> Self {
|
||||
self.transform = Some(transform);
|
||||
self
|
||||
}
|
||||
|
||||
/// Limit which existing columns a [`NewColumnTransform::BatchUDF`] mapper
|
||||
/// receives. Every other transform determines what it reads, so setting
|
||||
/// this alongside one is an error rather than a silent no-op.
|
||||
pub fn read_columns(mut self, columns: impl IntoIterator<Item = impl Into<String>>) -> Self {
|
||||
self.read_columns = Some(columns.into_iter().map(Into::into).collect());
|
||||
self
|
||||
}
|
||||
|
||||
/// Add the columns.
|
||||
pub async fn execute(self) -> Result<AddColumnsResult> {
|
||||
let Self {
|
||||
parent,
|
||||
transform,
|
||||
read_columns,
|
||||
} = self;
|
||||
|
||||
let Some(transform) = transform else {
|
||||
return Err(Error::InvalidInput {
|
||||
message: "add_columns requires a transform".into(),
|
||||
});
|
||||
};
|
||||
|
||||
if read_columns.is_some() && !matches!(transform, NewColumnTransform::BatchUDF(_)) {
|
||||
return Err(Error::InvalidInput {
|
||||
message: "read_columns applies only to a BatchUDF transform; \
|
||||
every other transform determines what it reads"
|
||||
.into(),
|
||||
});
|
||||
}
|
||||
|
||||
parent.add_columns(transform, read_columns).await
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::{Int32Array, RecordBatch, record_batch};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use lance::dataset::{BatchUDF, NewColumnTransform};
|
||||
|
||||
use crate::Table;
|
||||
use crate::connect;
|
||||
|
||||
async fn table_with_two_columns(name: &str) -> Table {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
let batch = record_batch!(("x", Int32, [1, 2, 3]), ("y", Int32, [10, 20, 30])).unwrap();
|
||||
conn.create_table(name, batch).execute().await.unwrap()
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_requires_a_transform() {
|
||||
let table = table_with_two_columns("no_transform").await;
|
||||
let err = table.add_columns().execute().await.unwrap_err();
|
||||
assert!(
|
||||
err.to_string().contains("requires a transform"),
|
||||
"got: {err}"
|
||||
);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_read_columns_with_sql_expressions_is_rejected() {
|
||||
let table = table_with_two_columns("read_cols_sql").await;
|
||||
let err = table
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"doubled".into(),
|
||||
"x * 2".into(),
|
||||
)]))
|
||||
.read_columns(["x"])
|
||||
.execute()
|
||||
.await
|
||||
.unwrap_err();
|
||||
assert!(err.to_string().contains("BatchUDF"), "got: {err}");
|
||||
|
||||
let schema = table.schema().await.unwrap();
|
||||
assert!(
|
||||
schema.field_with_name("doubled").is_err(),
|
||||
"a rejected call must not commit"
|
||||
);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_read_columns_limits_what_a_batch_udf_sees() {
|
||||
let table = table_with_two_columns("read_cols_udf").await;
|
||||
|
||||
let output_schema = Arc::new(Schema::new(vec![Field::new("sum", DataType::Int32, true)]));
|
||||
let mapper_schema = output_schema.clone();
|
||||
let udf = BatchUDF {
|
||||
mapper: Box::new(move |batch: &RecordBatch| {
|
||||
assert!(batch.column_by_name("x").is_some());
|
||||
assert!(batch.column_by_name("y").is_none(), "y was not requested");
|
||||
let x = batch["x"].as_any().downcast_ref::<Int32Array>().unwrap();
|
||||
let doubled: Int32Array = x.iter().map(|v| v.map(|v| v * 2)).collect();
|
||||
Ok(RecordBatch::try_new(
|
||||
mapper_schema.clone(),
|
||||
vec![Arc::new(doubled)],
|
||||
)?)
|
||||
}),
|
||||
output_schema,
|
||||
result_checkpoint: None,
|
||||
};
|
||||
|
||||
table
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::BatchUDF(udf))
|
||||
.read_columns(["x"])
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let schema = table.schema().await.unwrap();
|
||||
assert!(schema.field_with_name("sum").is_ok());
|
||||
}
|
||||
}
|
||||
@@ -576,10 +576,12 @@ mod tests {
|
||||
|
||||
// Add a new physical column AFTER the embedding column.
|
||||
table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("score".into(), "42.0".into())]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"score".into(),
|
||||
"42.0".into(),
|
||||
)]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -683,7 +685,9 @@ mod tests {
|
||||
true,
|
||||
)]));
|
||||
table
|
||||
.add_columns(NewColumnTransform::AllNulls(nested_schema), None)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::AllNulls(nested_schema))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -193,10 +193,12 @@ mod tests {
|
||||
|
||||
// Add a computed column
|
||||
let result = table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("doubled".into(), "id * 2".into())]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"doubled".into(),
|
||||
"id * 2".into(),
|
||||
)]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -251,13 +253,12 @@ mod tests {
|
||||
|
||||
// Add multiple columns at once
|
||||
table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![
|
||||
("y".into(), "x + 1".into()),
|
||||
("z".into(), "x * x".into()),
|
||||
]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![
|
||||
("y".into(), "x + 1".into()),
|
||||
("z".into(), "x * x".into()),
|
||||
]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -283,10 +284,12 @@ mod tests {
|
||||
|
||||
// Add a column with a constant value
|
||||
table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("constant".into(), "42".into())]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"constant".into(),
|
||||
"42".into(),
|
||||
)]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -659,10 +662,12 @@ mod tests {
|
||||
|
||||
// Add column increments version
|
||||
let add_result = table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("c".into(), "a + b".into())]),
|
||||
None,
|
||||
)
|
||||
.add_columns()
|
||||
.transform(NewColumnTransform::SqlExpressions(vec![(
|
||||
"c".into(),
|
||||
"a + b".into(),
|
||||
)]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert!(add_result.version > v1);
|
||||
|
||||
@@ -9,14 +9,17 @@ use arrow_array::{
|
||||
};
|
||||
use arrow_schema::{DataType, Field, Fields, Schema};
|
||||
use futures::TryStreamExt;
|
||||
use lance::Dataset;
|
||||
use lance_encoding::version::LanceFileVersion;
|
||||
use lancedb::{
|
||||
Connection, Error, Result, Table,
|
||||
blob::{BlobRangeRequest, blob},
|
||||
connect, connect_namespace,
|
||||
database::listing::OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS,
|
||||
database::listing::{
|
||||
ListingDatabaseOptions, NewTableConfig, OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS,
|
||||
},
|
||||
query::{ExecutableQuery, QueryBase},
|
||||
table::{AddDataMode, CompactionOptions, OptimizeAction},
|
||||
table::{AddDataMode, CompactionOptions, OptimizeAction, OptimizeStats},
|
||||
};
|
||||
use tempfile::tempdir;
|
||||
|
||||
@@ -1075,3 +1078,252 @@ async fn fetch_blob_files_aligns_across_fragments_with_nulls_and_dups() -> Resul
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Rows exercising the null/empty interleavings from
|
||||
/// <https://github.com/lancedb/lancedb/issues/3744>: a payload, a null, a valid
|
||||
/// empty value, then payloads whose descriptors a fragment rewrite used to zero.
|
||||
fn null_empty_input_batch() -> RecordBatch {
|
||||
let owned = [
|
||||
Some(dedicated_blob_bytes(1)),
|
||||
None,
|
||||
Some(Vec::new()),
|
||||
Some(dedicated_blob_bytes(4)),
|
||||
Some(dedicated_blob_bytes(5)),
|
||||
Some(dedicated_blob_bytes(6)),
|
||||
];
|
||||
let payloads: Vec<Option<&[u8]>> = owned.iter().map(|payload| payload.as_deref()).collect();
|
||||
binary_input_batch(&[1, 2, 3, 4, 5, 6], &payloads)
|
||||
}
|
||||
|
||||
/// One `(id, Some((payload length, first byte)))` per live row, or `(id, None)`
|
||||
/// for a null blob. Comparing lengths and first bytes keeps failure output
|
||||
/// readable where comparing whole payloads would not.
|
||||
type BlobSummary = Vec<(i64, Option<(usize, Option<u8>)>)>;
|
||||
|
||||
/// The rows [`null_empty_input_batch`] leaves behind after `id IN (1, 4)` is
|
||||
/// deleted: a null, a valid empty value, and the two payloads that follow them.
|
||||
fn expected_null_empty_survivors() -> BlobSummary {
|
||||
vec![
|
||||
(2, None),
|
||||
(3, Some((0, None))),
|
||||
(5, Some((DEDICATED_BLOB_LEN, Some(5)))),
|
||||
(6, Some((DEDICATED_BLOB_LEN, Some(6)))),
|
||||
]
|
||||
}
|
||||
|
||||
/// `optimize()` only rewrites a fragment when lance's compaction planner selects
|
||||
/// it — here because the delete pushes the fragment past
|
||||
/// `materialize_deletions_threshold` (0.1 by default; these tests delete 2 of 6
|
||||
/// rows). Without this check, a planner or threshold change upstream would leave
|
||||
/// both regression tests green while no rewrite happened at all.
|
||||
fn assert_compacted(stats: &OptimizeStats) {
|
||||
let metrics = stats
|
||||
.compaction
|
||||
.as_ref()
|
||||
.expect("OptimizeAction::All runs compaction");
|
||||
assert!(
|
||||
metrics.fragments_removed >= 1,
|
||||
"optimize() rewrote no fragment, so this test proves nothing: {metrics:?}"
|
||||
);
|
||||
}
|
||||
|
||||
fn summarize(rows: &[(i64, Option<Vec<u8>>)]) -> BlobSummary {
|
||||
rows.iter()
|
||||
.map(|(id, payload)| {
|
||||
(
|
||||
*id,
|
||||
payload
|
||||
.as_ref()
|
||||
.map(|bytes| (bytes.len(), bytes.first().copied())),
|
||||
)
|
||||
})
|
||||
.collect()
|
||||
}
|
||||
|
||||
async fn sorted_id_rowid(table: &Table) -> Result<Vec<(i64, u64)>> {
|
||||
let mut pairs = collect_id_rowid(table).await?;
|
||||
pairs.sort_by_key(|(id, _)| *id);
|
||||
Ok(pairs)
|
||||
}
|
||||
|
||||
/// `{position, size}` descriptors of a legacy v1 blob column, keyed by `id`.
|
||||
async fn v1_blob_descriptors(table: &Table) -> Result<Vec<(i64, Option<(u64, u64)>)>> {
|
||||
let batches = table
|
||||
.query()
|
||||
.execute()
|
||||
.await?
|
||||
.try_collect::<Vec<_>>()
|
||||
.await?;
|
||||
let batch = arrow_select::concat::concat_batches(&batches[0].schema(), &batches).unwrap();
|
||||
let ids = batch
|
||||
.column_by_name("id")
|
||||
.unwrap()
|
||||
.as_any()
|
||||
.downcast_ref::<Int64Array>()
|
||||
.unwrap();
|
||||
let descriptors = batch
|
||||
.column_by_name("image")
|
||||
.unwrap()
|
||||
.as_any()
|
||||
.downcast_ref::<StructArray>()
|
||||
.expect("v1 blob column reads back as a descriptor struct");
|
||||
let position = descriptors
|
||||
.column_by_name("position")
|
||||
.unwrap()
|
||||
.as_any()
|
||||
.downcast_ref::<UInt64Array>()
|
||||
.unwrap();
|
||||
let size = descriptors
|
||||
.column_by_name("size")
|
||||
.unwrap()
|
||||
.as_any()
|
||||
.downcast_ref::<UInt64Array>()
|
||||
.unwrap();
|
||||
let mut rows: Vec<(i64, Option<(u64, u64)>)> = (0..batch.num_rows())
|
||||
.map(|row| {
|
||||
let descriptor =
|
||||
(!descriptors.is_null(row)).then(|| (position.value(row), size.value(row)));
|
||||
(ids.value(row), descriptor)
|
||||
})
|
||||
.collect();
|
||||
rows.sort_by_key(|(id, _)| *id);
|
||||
Ok(rows)
|
||||
}
|
||||
|
||||
/// Payload bytes of every live row of a legacy v1 blob column, keyed by `id`.
|
||||
/// [`Table::fetch_blobs`] rejects v1 columns, so read them through lance.
|
||||
async fn v1_blob_payloads(dataset_uri: &str, table: &Table) -> Result<Vec<(i64, Option<Vec<u8>>)>> {
|
||||
let pairs = sorted_id_rowid(table).await?;
|
||||
let row_ids: Vec<u64> = pairs.iter().map(|(_, row_id)| *row_id).collect();
|
||||
let dataset = Arc::new(Dataset::open(dataset_uri).await?);
|
||||
let files = dataset.take_blobs(&row_ids, "image").await?;
|
||||
assert_eq!(
|
||||
files.len(),
|
||||
pairs.len(),
|
||||
"take_blobs returned {} handles for {} live rows",
|
||||
files.len(),
|
||||
pairs.len()
|
||||
);
|
||||
let mut rows = Vec::with_capacity(pairs.len());
|
||||
for ((id, _), file) in pairs.iter().zip(files) {
|
||||
let payload = match file {
|
||||
Some(file) => Some(file.read().await?.to_vec()),
|
||||
None => None,
|
||||
};
|
||||
rows.push((*id, payload));
|
||||
}
|
||||
Ok(rows)
|
||||
}
|
||||
|
||||
/// Length and first byte of every live blob v2 value, keyed by `id`.
|
||||
async fn blob_v2_values(table: &Table) -> Result<BlobSummary> {
|
||||
let pairs = sorted_id_rowid(table).await?;
|
||||
let row_ids: Vec<u64> = pairs.iter().map(|(_, row_id)| *row_id).collect();
|
||||
let bytes = table.fetch_blobs("image", &row_ids).await?;
|
||||
Ok(pairs
|
||||
.iter()
|
||||
.enumerate()
|
||||
.map(|(slot, (id, _))| {
|
||||
let value = (!bytes.is_null(slot))
|
||||
.then(|| (bytes.value(slot).len(), bytes.value(slot).first().copied()));
|
||||
(*id, value)
|
||||
})
|
||||
.collect())
|
||||
}
|
||||
|
||||
/// Regression test for [#3744]: on storage 2.0 (legacy v1 descriptors),
|
||||
/// compaction rewrote every payload following a null or empty value in the same
|
||||
/// fragment as `{position: 0, size: 0}`, so the payload bytes read back as `b""`
|
||||
/// and the new fragment no longer referenced them at all.
|
||||
///
|
||||
/// [#3744]: https://github.com/lancedb/lancedb/issues/3744
|
||||
#[tokio::test]
|
||||
async fn optimize_preserves_v1_blob_payloads_with_null_and_empty() -> Result<()> {
|
||||
let tmp = tempdir().unwrap();
|
||||
let db_uri = tmp.path().to_str().unwrap().to_string();
|
||||
let db = connect(&db_uri)
|
||||
.database_options(&ListingDatabaseOptions {
|
||||
new_table_config: NewTableConfig {
|
||||
data_storage_version: Some(LanceFileVersion::V2_0),
|
||||
..Default::default()
|
||||
},
|
||||
..Default::default()
|
||||
})
|
||||
.execute()
|
||||
.await?;
|
||||
let legacy = Field::new("image", DataType::LargeBinary, true).with_metadata(
|
||||
std::collections::HashMap::from([("lance-encoding:blob".to_string(), "true".to_string())]),
|
||||
);
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("id", DataType::Int64, false),
|
||||
legacy,
|
||||
]));
|
||||
let table = db.create_empty_table("t", schema).execute().await?;
|
||||
table.add(null_empty_input_batch()).execute().await?;
|
||||
assert_eq!(
|
||||
storage_format_version(&table).await,
|
||||
LanceFileVersion::V2_0.resolve(),
|
||||
"v1 blob descriptors only exist below storage 2.2"
|
||||
);
|
||||
let dataset_uri = table.uri().await?;
|
||||
|
||||
// Any rewrite triggers it; deleting rows is the shape from the issue.
|
||||
table.delete("id IN (1, 4)").await?;
|
||||
let descriptors_before = v1_blob_descriptors(&table).await?;
|
||||
let before = v1_blob_payloads(&dataset_uri, &table).await?;
|
||||
assert_eq!(
|
||||
summarize(&before),
|
||||
expected_null_empty_survivors(),
|
||||
"test setup no longer produces the null/empty/payload mix"
|
||||
);
|
||||
|
||||
let stats = table.optimize(OptimizeAction::All).await?;
|
||||
assert_compacted(&stats);
|
||||
|
||||
let descriptors_after = v1_blob_descriptors(&table).await?;
|
||||
let after = v1_blob_payloads(&dataset_uri, &table).await?;
|
||||
assert_eq!(
|
||||
summarize(&after),
|
||||
summarize(&before),
|
||||
"optimize() lost blob payloads; descriptors before={descriptors_before:?} after={descriptors_after:?}"
|
||||
);
|
||||
assert!(after == before, "optimize() changed blob payload bytes");
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Regression test for the blob v2 half of [#3744]: compaction rewrote a valid
|
||||
/// empty value as null, destroying the null-vs-empty distinction.
|
||||
///
|
||||
/// [#3744]: https://github.com/lancedb/lancedb/issues/3744
|
||||
#[tokio::test]
|
||||
async fn optimize_preserves_blob_v2_null_and_empty_distinction() -> Result<()> {
|
||||
let tmp = tempdir().unwrap();
|
||||
let db = connect(tmp.path().to_str().unwrap()).execute().await?;
|
||||
let table = db
|
||||
.create_empty_table("t", blob_table_schema())
|
||||
.execute()
|
||||
.await?;
|
||||
table.add(null_empty_input_batch()).execute().await?;
|
||||
assert!(
|
||||
storage_format_version(&table).await >= LanceFileVersion::V2_2,
|
||||
"blob v2 columns require storage >= 2.2"
|
||||
);
|
||||
|
||||
table.delete("id IN (1, 4)").await?;
|
||||
let before = blob_v2_values(&table).await?;
|
||||
assert_eq!(
|
||||
before,
|
||||
expected_null_empty_survivors(),
|
||||
"test setup no longer produces the null/empty/payload mix"
|
||||
);
|
||||
|
||||
let stats = table.optimize(OptimizeAction::All).await?;
|
||||
assert_compacted(&stats);
|
||||
|
||||
assert_eq!(
|
||||
blob_v2_values(&table).await?,
|
||||
before,
|
||||
"optimize() changed blob v2 values"
|
||||
);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user