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feat: support distributed analyze plan metrics in clients (#3675)

Browse Source 
Adds client-side support for analyze_plan distributed metrics modes
across Rust, Python, and TypeScript clients. Defaults to aggregate for
backward compatibility and sends the remote distributed_metrics
parameter only when a non-default mode is requested.
This commit is contained in:
Jack Ye
2026-07-15 21:21:40 -07:00
committed by GitHub
parent 00c4a7b843
commit 37032151d3
22 changed files with 396 additions and 75 deletions
Download Patch File Download Diff File Expand all files Collapse all files
python/pyproject.toml
+3 -2
View File
@@ -61,10 +61,11 @@ tests = [
"duckdb>=0.9.0",
"pytz>=2023.3",
"polars>=0.19, <=1.3.0",
"pyarrow<25",
"pyarrow-stubs>=16.0",
"pylance>=5.0.0b5",
"pylance>=7,<8",
"requests>=2.31.0",
"datafusion>=52,<53",
"datafusion>=53,<54",
"opentelemetry-sdk>=1.30.0",
]
dev = [
python/python/lancedb/_lancedb.pyi
+16 -1
View File
@@ -30,6 +30,7 @@ from .types import BaseTokenizerType
IvfHnswPq: type[HnswPq] = HnswPq
IvfHnswSq: type[HnswSq] = HnswSq
IvfHnswFlat: type[HnswFlat] = HnswFlat
AnalyzePlanDistributedMetrics = Literal["aggregate", "per_worker", "full"]
class MetricPoint:
name: str
@@ -393,7 +394,9 @@ class Query:
self, max_batch_length: Optional[int], timeout: Optional[timedelta]
) -> RecordBatchStream: ...
async def explain_plan(self, verbose: Optional[bool]) -> str: ...
async def analyze_plan(self) -> str: ...
async def analyze_plan(
self, distributed_metrics: Optional[AnalyzePlanDistributedMetrics] = None
) -> str: ...
def to_query_request(self) -> PyQueryRequest: ...
class TakeQuery:
@@ -401,6 +404,10 @@ class TakeQuery:
def with_row_id(self): ...
async def output_schema(self) -> pa.Schema: ...
async def execute(self) -> RecordBatchStream: ...
async def explain_plan(self, verbose: Optional[bool]) -> str: ...
async def analyze_plan(
self, distributed_metrics: Optional[AnalyzePlanDistributedMetrics] = None
) -> str: ...
def to_query_request(self) -> PyQueryRequest: ...
class FTSQuery:
@@ -421,6 +428,10 @@ class FTSQuery:
async def execute(
self, max_batch_length: Optional[int], timeout: Optional[timedelta]
) -> RecordBatchStream: ...
async def explain_plan(self, verbose: Optional[bool]) -> str: ...
async def analyze_plan(
self, distributed_metrics: Optional[AnalyzePlanDistributedMetrics] = None
) -> str: ...
def to_query_request(self) -> PyQueryRequest: ...
class VectorQuery:
@@ -443,6 +454,10 @@ class VectorQuery:
def bypass_vector_index(self): ...
def nearest_to_text(self, query: dict) -> HybridQuery: ...
def order_by(self, ordering: Optional[List[ColumnOrdering]]): ...
async def explain_plan(self, verbose: Optional[bool]) -> str: ...
async def analyze_plan(
self, distributed_metrics: Optional[AnalyzePlanDistributedMetrics] = None
) -> str: ...
def to_query_request(self) -> PyQueryRequest: ...
class HybridQuery:
python/python/lancedb/query.py
+71 -12
View File
@@ -79,6 +79,7 @@ if TYPE_CHECKING:
from typing_extensions import Self
T = TypeVar("T", bound="LanceModel")
AnalyzePlanDistributedMetrics = Literal["aggregate", "per_worker", "full"]
@runtime_checkable
@@ -1372,7 +1373,9 @@ class LanceQueryBuilder(ABC):
self._order_by = ordering
return self
def analyze_plan(self) -> str:
def analyze_plan(
self, distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate"
) -> str:
"""
Run the query and return its execution plan with runtime metrics.
@@ -1410,12 +1413,22 @@ class LanceQueryBuilder(ABC):
fragments_scanned=..., ranges_scanned=1, rows_scanned=1,
bytes_read=..., iops=..., requests=..., task_wait_time=...]
Parameters
----------
distributed_metrics : Literal["aggregate", "per_worker", "full"]
Defaults to "aggregate".
How distributed worker metrics are displayed for remote query plans.
"aggregate" preserves the legacy summary, "per_worker" shows each
worker separately, and "full" includes both.
Returns
-------
plan : str
The physical query execution plan with runtime metrics.
"""
return self._table._analyze_plan(self.to_query_object())
return self._table._analyze_plan(
self.to_query_object(), distributed_metrics=distributed_metrics
)
def vector(self, vector: Union[np.ndarray, list]) -> Self:
"""Set the vector to search for.
@@ -2581,9 +2594,17 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
indented_fts = "\n".join(" " + line for line in fts_plan.splitlines())
return f"{reranker_label}\n {indented_vector}\n {indented_fts}"
def analyze_plan(self):
def analyze_plan(
self, distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate"
) -> str:
"""Execute the query and display with runtime metrics.
Parameters
----------
distributed_metrics : Literal["aggregate", "per_worker", "full"]
Defaults to "aggregate".
How distributed worker metrics are displayed for remote query plans.
Returns
-------
plan : str
@@ -2591,9 +2612,19 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
self._create_query_builders()
results = ["Vector Search Plan:"]
results.append(self._table._analyze_plan(self._vector_query.to_query_object()))
results.append(
self._table._analyze_plan(
self._vector_query.to_query_object(),
distributed_metrics=distributed_metrics,
)
)
results.append("FTS Search Plan:")
results.append(self._table._analyze_plan(self._fts_query.to_query_object()))
results.append(
self._table._analyze_plan(
self._fts_query.to_query_object(),
distributed_metrics=distributed_metrics,
)
)
return "\n".join(results)
def _create_query_builders(self):
@@ -3080,14 +3111,22 @@ class AsyncQueryBase(object):
""" # noqa: E501
return await self._inner.explain_plan(verbose)
async def analyze_plan(self):
async def analyze_plan(
self, distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate"
) -> str:
"""Execute the query and display with runtime metrics.
Parameters
----------
distributed_metrics : Literal["aggregate", "per_worker", "full"]
Defaults to "aggregate".
How distributed worker metrics are displayed for remote query plans.
Returns
-------
plan : str
"""
return await self._inner.analyze_plan()
return await self._inner.analyze_plan(distributed_metrics)
class AsyncStandardQuery(AsyncQueryBase):
@@ -3866,7 +3905,9 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
indented_fts = "\n".join(" " + line for line in fts_plan.splitlines())
return f"{self._reranker}\n {indented_vector}\n {indented_fts}"
async def analyze_plan(self):
async def analyze_plan(
self, distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate"
) -> str:
"""
Execute the query and return the physical execution plan with runtime metrics.
@@ -3875,14 +3916,24 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
elapsed time, I/O stats, and more. It’s useful for debugging and
performance analysis.
Parameters
----------
distributed_metrics : Literal["aggregate", "per_worker", "full"]
Defaults to "aggregate".
How distributed worker metrics are displayed for remote query plans.
Returns
-------
plan : str
"""
results = ["Vector Search Query:"]
results.append(await self._inner.to_vector_query().analyze_plan())
results.append(
await self._inner.to_vector_query().analyze_plan(distributed_metrics)
)
results.append("FTS Search Query:")
results.append(await self._inner.to_fts_query().analyze_plan())
results.append(
await self._inner.to_fts_query().analyze_plan(distributed_metrics)
)
return "\n".join(results)
@@ -4166,14 +4217,22 @@ class BaseQueryBuilder(object):
""" # noqa: E501
return LOOP.run(self._inner.explain_plan(verbose))
def analyze_plan(self):
def analyze_plan(
self, distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate"
) -> str:
"""Execute the query and display with runtime metrics.
Parameters
----------
distributed_metrics : Literal["aggregate", "per_worker", "full"]
Defaults to "aggregate".
How distributed worker metrics are displayed for remote query plans.
Returns
-------
plan : str
"""
return LOOP.run(self._inner.analyze_plan())
return LOOP.run(self._inner.analyze_plan(distributed_metrics))
class LanceTakeQueryBuilder(BaseQueryBuilder):
python/python/lancedb/remote/table.py
+15 -3
View File
@@ -56,7 +56,12 @@ from lancedb.merge import LanceMergeInsertBuilder
from lancedb.embeddings import EmbeddingFunctionRegistry
from lancedb.table import _normalize_progress
from ..query import LanceVectorQueryBuilder, LanceQueryBuilder, LanceTakeQueryBuilder
from ..query import (
AnalyzePlanDistributedMetrics,
LanceQueryBuilder,
LanceTakeQueryBuilder,
LanceVectorQueryBuilder,
)
from ..table import AsyncTable, BlobMode, Branches, IndexStatistics, Query, Table, Tags
from ..types import BaseTokenizerType
@@ -718,8 +723,15 @@ class RemoteTable(Table):
def _explain_plan(self, query: Query, verbose: Optional[bool] = False) -> str:
return LOOP.run(self._table._explain_plan(query, verbose))
def _analyze_plan(self, query: Query) -> str:
return LOOP.run(self._table._analyze_plan(query))
def _analyze_plan(
self,
query: Query,
*,
distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate",
) -> str:
return LOOP.run(
self._table._analyze_plan(query, distributed_metrics=distributed_metrics)
)
def _output_schema(self, query: Query) -> pa.Schema:
return LOOP.run(self._table._output_schema(query))
python/python/lancedb/table.py
+23 -5
View File
@@ -73,6 +73,7 @@ from .expr import Expr
from .merge import LanceMergeInsertBuilder
from .pydantic import LanceModel, model_to_dict
from .query import (
AnalyzePlanDistributedMetrics,
AsyncFTSQuery,
AsyncHybridQuery,
AsyncQuery,
@@ -1552,7 +1553,12 @@ class Table(ABC):
def _explain_plan(self, query: Query, verbose: Optional[bool] = False) -> str: ...
@abstractmethod
def _analyze_plan(self, query: Query) -> str: ...
def _analyze_plan(
self,
query: Query,
*,
distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate",
) -> str: ...
@abstractmethod
def _output_schema(self, query: Query) -> pa.Schema: ...
@@ -3630,8 +3636,15 @@ class LanceTable(Table):
def _explain_plan(self, query: Query, verbose: Optional[bool] = False) -> str:
return LOOP.run(self._table._explain_plan(query, verbose))
def _analyze_plan(self, query: Query) -> str:
return LOOP.run(self._table._analyze_plan(query))
def _analyze_plan(
self,
query: Query,
*,
distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate",
) -> str:
return LOOP.run(
self._table._analyze_plan(query, distributed_metrics=distributed_metrics)
)
def _output_schema(self, query: Query) -> pa.Schema:
return LOOP.run(self._table._output_schema(query))
@@ -5390,10 +5403,15 @@ class AsyncTable:
async_query = self._sync_query_to_async(query)
return await async_query.explain_plan(verbose)
async def _analyze_plan(self, query: Query) -> str:
async def _analyze_plan(
self,
query: Query,
*,
distributed_metrics: AnalyzePlanDistributedMetrics = "aggregate",
) -> str:
# This method is used by the sync table
async_query = self._sync_query_to_async(query)
return await async_query.analyze_plan()
return await async_query.analyze_plan(distributed_metrics)
async def _output_schema(self, query: Query) -> pa.Schema:
async_query = self._sync_query_to_async(query)
python/python/tests/test_hybrid_query.py
+10 -2
View File
@@ -196,18 +196,26 @@ async def test_analyze_plan(table: AsyncTable):
def test_hybrid_phrase_query_is_preserved_in_analyze_plan():
table = mock.Mock()
analyzed_queries = []
table._analyze_plan.side_effect = lambda query: analyzed_queries.append(query) or ""
distributed_metric_modes = []
def capture_query(query, *, distributed_metrics="aggregate"):
analyzed_queries.append(query)
distributed_metric_modes.append(distributed_metrics)
return ""
table._analyze_plan.side_effect = capture_query
(
LanceHybridQueryBuilder(table)
.vector([0.1, 0.2])
.text("puppy runs")
.phrase_query()
.analyze_plan()
.analyze_plan(distributed_metrics="full")
)
assert len(analyzed_queries) == 2
assert analyzed_queries[1].full_text_query.query == '"puppy runs"'
assert distributed_metric_modes == ["full", "full"]
@pytest.fixture
python/src/query.rs
+48 -8
View File
@@ -19,6 +19,7 @@ use lancedb::index::scalar::{
BooleanQuery, BoostQuery, FtsQuery, FullTextSearchQuery, MatchQuery, MultiMatchQuery, Occur,
Operator, PhraseQuery,
};
use lancedb::query::AnalyzePlanDistributedMetrics;
use lancedb::query::QueryBase;
use lancedb::query::QueryExecutionOptions;
use lancedb::query::QueryFilter;
@@ -42,6 +43,25 @@ use pyo3::{Borrowed, FromPyObject, exceptions::PyRuntimeError};
use pyo3::{PyErr, pyclass};
use pyo3::{exceptions::PyValueError, intern};
fn analyze_plan_options(distributed_metrics: Option<&str>) -> PyResult<QueryExecutionOptions> {
let analyze_plan_distributed_metrics = match distributed_metrics.unwrap_or("aggregate") {
"aggregate" => AnalyzePlanDistributedMetrics::Aggregate,
"per_worker" => AnalyzePlanDistributedMetrics::PerWorker,
"full" => AnalyzePlanDistributedMetrics::Full,
mode => {
return Err(PyValueError::new_err(format!(
"Invalid distributed_metrics value '{}'. Expected one of: \
'aggregate', 'per_worker', 'full'",
mode
)));
}
};
let mut options = QueryExecutionOptions::default();
options.analyze_plan_distributed_metrics = analyze_plan_distributed_metrics;
Ok(options)
}
impl<'a, 'py> FromPyObject<'a, 'py> for PyLanceDB<FtsQuery> {
type Error = PyErr;
@@ -571,11 +591,16 @@ impl Query {
})
}
pub fn analyze_plan(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
#[pyo3(signature = (distributed_metrics=None))]
pub fn analyze_plan(
self_: PyRef<'_, Self>,
distributed_metrics: Option<String>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
let options = analyze_plan_options(distributed_metrics.as_deref())?;
future_into_py(self_.py(), async move {
inner
.analyze_plan()
.analyze_plan_with_options(options)
.await
.map_err(|e| PyRuntimeError::new_err(e.to_string()))
})
@@ -650,11 +675,16 @@ impl TakeQuery {
})
}
pub fn analyze_plan(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
#[pyo3(signature = (distributed_metrics=None))]
pub fn analyze_plan(
self_: PyRef<'_, Self>,
distributed_metrics: Option<String>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
let options = analyze_plan_options(distributed_metrics.as_deref())?;
future_into_py(self_.py(), async move {
inner
.analyze_plan()
.analyze_plan_with_options(options)
.await
.map_err(|e| PyRuntimeError::new_err(e.to_string()))
})
@@ -777,14 +807,19 @@ impl FTSQuery {
})
}
pub fn analyze_plan(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
#[pyo3(signature = (distributed_metrics=None))]
pub fn analyze_plan(
self_: PyRef<'_, Self>,
distributed_metrics: Option<String>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_
.inner
.clone()
.full_text_search(self_.fts_query.clone());
let options = analyze_plan_options(distributed_metrics.as_deref())?;
future_into_py(self_.py(), async move {
inner
.analyze_plan()
.analyze_plan_with_options(options)
.await
.map_err(|e| PyRuntimeError::new_err(e.to_string()))
})
@@ -958,11 +993,16 @@ impl VectorQuery {
})
}
pub fn analyze_plan(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
#[pyo3(signature = (distributed_metrics=None))]
pub fn analyze_plan(
self_: PyRef<'_, Self>,
distributed_metrics: Option<String>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
let options = analyze_plan_options(distributed_metrics.as_deref())?;
future_into_py(self_.py(), async move {
inner
.analyze_plan()
.analyze_plan_with_options(options)
.await
.map_err(|e| PyRuntimeError::new_err(e.to_string()))
})
python/uv.lock
Generated
+11 -9
View File
@@ -850,19 +850,19 @@ nvtx = [
[[package]]
name = "datafusion"
version = "52.3.0"
version = "53.0.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "pyarrow" },
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
]
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sdist = { url = "https://files.pythonhosted.org/packages/58/2b/0f96f12b70839c93930c4e17d767fc32b6c77d548c78784128049e944701/datafusion-53.0.0.tar.gz", hash = "sha256:ba9a5ec06b5453fbd8710d6aeeb515a8bcac4b6c140e254409bb53a5f322ef22", size = 224267, upload-time = "2026-04-13T00:45:02.686Z" }
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[[package]]
@@ -1931,6 +1931,7 @@ tests = [
{ name = "pandas", version = "2.3.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and python_full_version < '3.14'" },
{ name = "pandas", version = "3.0.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.14'" },
{ name = "polars" },
{ name = "pyarrow" },
{ name = "pyarrow-stubs" },
{ name = "pylance" },
{ name = "pytest" },
@@ -1950,7 +1951,7 @@ requires-dist = [
{ name = "botocore", marker = "extra == 'embeddings'", specifier = ">=1.31.57" },
{ name = "cohere", marker = "extra == 'embeddings'", specifier = ">=4.0" },
{ name = "colpali-engine", marker = "extra == 'embeddings'", specifier = ">=0.3.10" },
{ name = "datafusion", marker = "extra == 'tests'", specifier = ">=52,<53" },
{ name = "datafusion", marker = "extra == 'tests'", specifier = ">=53,<54" },
{ name = "deprecation", specifier = ">=2.1.0" },
{ name = "duckdb", marker = "extra == 'tests'", specifier = ">=0.9.0" },
{ name = "google-genai", marker = "extra == 'embeddings'", specifier = ">=1.0.0" },
@@ -1978,10 +1979,11 @@ requires-dist = [
{ name = "polars", marker = "extra == 'tests'", specifier = ">=0.19,<=1.3.0" },
{ name = "pre-commit", marker = "extra == 'dev'", specifier = ">=3.5.0" },
{ name = "pyarrow", specifier = ">=16" },
{ name = "pyarrow", marker = "extra == 'tests'", specifier = "<25" },
{ name = "pyarrow-stubs", marker = "extra == 'tests'", specifier = ">=16.0" },
{ name = "pydantic", specifier = ">=1.10" },
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