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https://github.com/lancedb/lancedb.git
synced 2026-08-26 07:58:31 +00:00
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6 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 71a2a0c720 | |||
| 56585ccaf7 | |||
| e5ea48c433 | |||
| 024bf9f569 | |||
| 0d582eb612 | |||
| b3f813d8df |
@@ -270,7 +270,8 @@ def _iter_projection_pairs(
|
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if isinstance(expr, str):
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yield name, expr
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elif isinstance(expr, Expr):
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yield name, expr.to_sql()
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source = expr._column_name()
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yield name, source if source is not None else expr.to_sql()
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return
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for column in projection:
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if isinstance(column, str):
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@@ -280,7 +281,8 @@ def _iter_projection_pairs(
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if isinstance(expr, str):
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yield name, expr
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elif isinstance(expr, Expr):
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yield name, expr.to_sql()
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source = expr._column_name()
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yield name, source if source is not None else expr.to_sql()
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def _set_blob_column(tbl: pa.Table, output_name: str, blobs: pa.Array) -> pa.Table:
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@@ -87,6 +87,7 @@ class PyExpr:
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def contains(self, substr: "PyExpr") -> "PyExpr": ...
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def isin(self, values: List["PyExpr"]) -> "PyExpr": ...
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def cast(self, data_type: pa.DataType) -> "PyExpr": ...
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def column_name(self) -> Optional[str]: ...
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def to_sql(self) -> str: ...
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def expr_col(name: str) -> PyExpr: ...
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@@ -578,6 +579,7 @@ class PyQueryRequest:
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filter: Optional[Union[str, bytes]]
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full_text_search: Optional[FullTextQuery]
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select: Optional[Union[str, List[str]]]
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select_source_columns: Optional[Dict[str, str]]
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fast_search: Optional[bool]
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with_row_id: Optional[bool]
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use_lsm: Optional[bool]
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@@ -248,6 +248,10 @@ class Expr:
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# ── utilities ────────────────────────────────────────────────────────────
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def _column_name(self) -> str | None:
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"""Return the source name when this is a bare column expression."""
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return self._inner.column_name()
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def to_sql(self) -> str:
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"""Render the expression as a SQL string (useful for debugging)."""
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return self._inner.to_sql()
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@@ -311,7 +315,7 @@ def func(name: str, *args: ExprLike) -> Expr:
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--------
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>>> from lancedb.expr import col, func
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>>> func("lower", col("name"))
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Expr(lower(name))
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Expr(lower(`name`))
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"""
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inner_args = [_coerce(a)._inner for a in args]
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return Expr(expr_func(name, inner_args))
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@@ -169,6 +169,12 @@ def _projection_to_scanner_kwargs(columns: QueryProjection) -> Dict[str, Any]:
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return {"columns": projection}
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def _query_request_projection(req: "PyQueryRequest") -> QueryProjection:
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if req.select_source_columns is not None:
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return req.select_source_columns
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return req.select
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def _scanner_kwargs_for_query(
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query: Query,
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blob_mode: BlobMode,
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@@ -2777,15 +2783,16 @@ class AsyncQueryBase(object):
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req = self._inner.to_query_request()
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schema = await self._table.schema()
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projection = _query_request_projection(req)
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self._blob_auto_row_id = blob_auto_row_id_for_scan(
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schema,
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req.select,
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projection,
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with_row_id=self._with_row_id,
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)
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if not self._blob_auto_row_id:
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self._blob_paths = ()
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return
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self._blob_paths = tuple(blob_v2_projection_sources(schema, req.select).keys())
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self._blob_paths = tuple(blob_v2_projection_sources(schema, projection).keys())
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self._inner.with_row_id()
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def select(self, columns: Union[List[str], dict[str, str]]) -> Self:
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@@ -3876,14 +3883,15 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
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blob_paths: tuple[str, ...] = ()
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if self._table is not None:
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schema = await self._table.schema()
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projection = _query_request_projection(req)
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blob_auto_row_id = blob_auto_row_id_for_scan(
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schema,
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req.select,
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projection,
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with_row_id=self._with_row_id,
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)
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if blob_auto_row_id:
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blob_paths = tuple(
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blob_v2_projection_sources(schema, req.select).keys()
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blob_v2_projection_sources(schema, projection).keys()
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)
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self._blob_auto_row_id = blob_auto_row_id
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self._blob_paths = blob_paths
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@@ -36,6 +36,7 @@ from lancedb._lancedb import (
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UpdateResult,
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)
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from lancedb.embeddings.base import EmbeddingFunctionConfig
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from lancedb.expr import Expr
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from lancedb.index import (
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FTS,
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BTree,
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@@ -855,7 +856,7 @@ class RemoteTable(Table):
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def update(
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self,
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where: Optional[str] = None,
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where: Optional[Union[str, Expr]] = None,
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values: Optional[dict] = None,
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*,
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values_sql: Optional[Dict[str, str]] = None,
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@@ -866,9 +867,11 @@ class RemoteTable(Table):
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Parameters
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----------
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where: str, optional
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The SQL where clause to use when updating rows. For example, 'x = 2'
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or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
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where: str or [Expr][lancedb.expr.Expr], optional
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The filter condition. Can be a SQL string or a type-safe
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[Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
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[lit][lancedb.expr.lit]. The filter must not be empty, or it will
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error.
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values: dict, optional
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The values to update. The keys are the column names and the values
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are the values to set.
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@@ -1692,7 +1692,7 @@ class Table(ABC):
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@abstractmethod
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def update(
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self,
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where: Optional[str] = None,
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where: Optional[Union[str, Expr]] = None,
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values: Optional[dict] = None,
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*,
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values_sql: Optional[Dict[str, str]] = None,
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@@ -1707,9 +1707,11 @@ class Table(ABC):
|
||||
|
||||
Parameters
|
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----------
|
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where: str, optional
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The SQL where clause to use when updating rows. For example, 'x = 2'
|
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or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
|
||||
where: str or [Expr][lancedb.expr.Expr], optional
|
||||
The filter condition. Can be a SQL string or a type-safe
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[Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
|
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[lit][lancedb.expr.lit]. The filter must not be empty, or it will
|
||||
error.
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values: dict, optional
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The values to update. The keys are the column names and the values
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are the values to set.
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@@ -1727,6 +1729,7 @@ class Table(ABC):
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Examples
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--------
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>>> import lancedb
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>>> from lancedb.expr import col
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>>> import pandas as pd
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>>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1.0, 2], [3, 4], [5, 6]]})
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>>> db = lancedb.connect("./.lancedb")
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@@ -1736,7 +1739,7 @@ class Table(ABC):
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0 1 [1.0, 2.0]
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1 2 [3.0, 4.0]
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2 3 [5.0, 6.0]
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>>> table.update(where="x = 2", values={"vector": [10.0, 10]})
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>>> table.update(where=col("x") == 2, values={"vector": [10.0, 10]})
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UpdateResult(rows_updated=1, version=2)
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>>> table.to_pandas()
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x vector
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@@ -3651,7 +3654,7 @@ class LanceTable(Table):
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def update(
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self,
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where: Optional[str] = None,
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where: Optional[Union[str, Expr]] = None,
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||||
values: Optional[dict] = None,
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*,
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values_sql: Optional[Dict[str, str]] = None,
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||||
@@ -3662,9 +3665,11 @@ class LanceTable(Table):
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|
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Parameters
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----------
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where: str, optional
|
||||
The SQL where clause to use when updating rows. For example, 'x = 2'
|
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or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
|
||||
where: str or [Expr][lancedb.expr.Expr], optional
|
||||
The filter condition. Can be a SQL string or a type-safe
|
||||
[Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
|
||||
[lit][lancedb.expr.lit]. The filter must not be empty, or it will
|
||||
error.
|
||||
values: dict, optional
|
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The values to update. The keys are the column names and the values
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are the values to set.
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@@ -3682,6 +3687,7 @@ class LanceTable(Table):
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Examples
|
||||
--------
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||||
>>> import lancedb
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>>> from lancedb.expr import col
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>>> import pandas as pd
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>>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1.0, 2], [3, 4], [5, 6]]})
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>>> db = lancedb.connect("./.lancedb")
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@@ -3691,7 +3697,7 @@ class LanceTable(Table):
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0 1 [1.0, 2.0]
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1 2 [3.0, 4.0]
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2 3 [5.0, 6.0]
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>>> table.update(where="x = 2", values={"vector": [10.0, 10]})
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>>> table.update(where=col("x") == 2, values={"vector": [10.0, 10]})
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UpdateResult(rows_updated=1, version=2)
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>>> table.to_pandas()
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x vector
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@@ -5690,7 +5696,7 @@ class AsyncTable:
|
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self,
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updates: Optional[Dict[str, Any]] = None,
|
||||
*,
|
||||
where: Optional[str] = None,
|
||||
where: Optional[Union[str, Expr]] = None,
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||||
updates_sql: Optional[Dict[str, str]] = None,
|
||||
) -> UpdateResult:
|
||||
"""
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@@ -5705,9 +5711,11 @@ class AsyncTable:
|
||||
The updates to apply. The keys should be the name of the column to
|
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update. The values should be the new values to assign. This is
|
||||
required unless updates_sql is supplied.
|
||||
where: str, optional
|
||||
An SQL filter that controls which rows are updated. For example, 'x = 2'
|
||||
or 'x IN (1, 2, 3)'. Only rows that satisfy this filter will be udpated.
|
||||
where: str or [Expr][lancedb.expr.Expr], optional
|
||||
The filter condition. Can be a SQL string or a type-safe
|
||||
[Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
|
||||
[lit][lancedb.expr.lit]. Only rows that satisfy this filter will
|
||||
be updated.
|
||||
updates_sql: dict, optional
|
||||
The updates to apply, expressed as SQL expression strings. The keys should
|
||||
be column names. The values should be SQL expressions. These can be SQL
|
||||
@@ -5725,13 +5733,14 @@ class AsyncTable:
|
||||
--------
|
||||
>>> import asyncio
|
||||
>>> import lancedb
|
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>>> from lancedb.expr import col
|
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>>> import pandas as pd
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>>> async def demo_update():
|
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... data = pd.DataFrame({"x": [1, 2], "vector": [[1, 2], [3, 4]]})
|
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... db = await lancedb.connect_async("./.lancedb")
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... table = await db.create_table("my_table", data)
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... # x is [1, 2], vector is [[1, 2], [3, 4]]
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... await table.update({"vector": [10, 10]}, where="x = 2")
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... await table.update({"vector": [10, 10]}, where=col("x") == 2)
|
||||
... # x is [1, 2], vector is [[1, 2], [10, 10]]
|
||||
... await table.update(updates_sql={"x": "x + 1"})
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... # x is [2, 3], vector is [[1, 2], [10, 10]]
|
||||
@@ -5745,7 +5754,8 @@ class AsyncTable:
|
||||
if updates is not None:
|
||||
updates_sql = {k: value_to_sql(v) for k, v in updates.items()}
|
||||
|
||||
return await self._inner.update(updates_sql, where)
|
||||
predicate = where.to_sql() if isinstance(where, Expr) else where
|
||||
return await self._inner.update(updates_sql, predicate)
|
||||
|
||||
async def add_columns(
|
||||
self, transforms: dict[str, str] | pa.field | List[pa.field] | pa.Schema
|
||||
|
||||
@@ -8,7 +8,12 @@ import pyarrow.compute as pc
|
||||
import pytest
|
||||
|
||||
import lancedb
|
||||
from lancedb._blob import read_row_ids_from_hits, stash_auto_row_ids
|
||||
from lancedb._blob import (
|
||||
blob_v2_projection_sources,
|
||||
read_row_ids_from_hits,
|
||||
stash_auto_row_ids,
|
||||
)
|
||||
from lancedb.expr import col
|
||||
from lancedb.index import FTS
|
||||
from lancedb.schema import blob_column_paths, blob_v2_column_paths
|
||||
|
||||
@@ -70,6 +75,14 @@ def test_blob_v2_column_paths_include_list_children():
|
||||
]
|
||||
|
||||
|
||||
def test_blob_v2_projection_sources_use_typed_column_name():
|
||||
schema = pa.schema([lancedb.blob("blob")])
|
||||
|
||||
assert blob_v2_projection_sources(schema, {"blob_alias": col("blob")}) == {
|
||||
"blob_alias": "blob"
|
||||
}
|
||||
|
||||
|
||||
def _legacy_v1_table(name):
|
||||
db = lancedb.connect("memory:///")
|
||||
schema = pa.schema(
|
||||
@@ -166,6 +179,20 @@ async def test_async_table_to_pandas_descriptions_mode_omits_row_id():
|
||||
assert set(descriptor.keys()) == {"kind", "position", "size", "blob_id", "blob_uri"}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_async_typed_blob_projection_preserves_source_column():
|
||||
db = await lancedb.connect_async("memory:///typed_blob_projection")
|
||||
schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("blob")])
|
||||
table = await db.create_table("typed_blob_projection", schema=schema)
|
||||
await table.add([{"id": 1, "blob": b"alpha"}])
|
||||
|
||||
hits = await table.query().select({"blob_alias": col("blob")}).to_arrow()
|
||||
|
||||
assert "_lance_row_id" in hits.schema.field("blob_alias").type.names
|
||||
blobs = await table.fetch_blobs("blob", hits)
|
||||
assert blobs.to_pylist() == [b"alpha"]
|
||||
|
||||
|
||||
def test_fetch_blobs_round_trip():
|
||||
table = _blob_table(
|
||||
"round_trip",
|
||||
@@ -403,6 +430,50 @@ async def test_blob_v2_hybrid_fetch_blobs_async():
|
||||
assert {blobs[i].as_py() for i in range(len(blobs))} == {b"alpha", b"beta"}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_async_hybrid_typed_blob_projection_preserves_source_column():
|
||||
db = await lancedb.connect_async("memory:///hybrid_typed_blob")
|
||||
schema = pa.schema(
|
||||
[
|
||||
pa.field("id", pa.int64()),
|
||||
pa.field("text", pa.utf8()),
|
||||
pa.field("vector", pa.list_(pa.float32(), list_size=2)),
|
||||
lancedb.blob("blob"),
|
||||
]
|
||||
)
|
||||
table = await db.create_table("hybrid_typed_blob", schema=schema)
|
||||
await table.add(
|
||||
[
|
||||
{
|
||||
"id": 1,
|
||||
"text": "hello alpha",
|
||||
"vector": [1.0, 0.0],
|
||||
"blob": b"alpha",
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"text": "hello beta",
|
||||
"vector": [0.9, 0.1],
|
||||
"blob": b"beta",
|
||||
},
|
||||
]
|
||||
)
|
||||
await table.create_index("text", config=FTS(with_position=False))
|
||||
|
||||
hits = await (
|
||||
table.query()
|
||||
.nearest_to([1.0, 0.0])
|
||||
.nearest_to_text("hello")
|
||||
.select({"blob_alias": col("blob")})
|
||||
.limit(2)
|
||||
.to_arrow()
|
||||
)
|
||||
|
||||
assert "_lance_row_id" in hits.schema.field("blob_alias").type.names
|
||||
blobs = await table.fetch_blobs("blob", hits)
|
||||
assert {blobs[i].as_py() for i in range(len(blobs))} == {b"alpha", b"beta"}
|
||||
|
||||
|
||||
def test_blob_file_seek_read_and_read_range():
|
||||
payload = _identifiable_payload(1024)
|
||||
table = _blob_table("seek_read", [{"id": 1, "image": payload}])
|
||||
|
||||
@@ -52,7 +52,7 @@ class TestExprConstruction:
|
||||
def test_func(self):
|
||||
e = func("lower", col("name"))
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "lower(name)"
|
||||
assert e.to_sql() == "lower(`name`)"
|
||||
|
||||
def test_func_unknown_raises(self):
|
||||
with pytest.raises(Exception):
|
||||
@@ -115,7 +115,7 @@ class TestExprOperators:
|
||||
def test_and_operator(self):
|
||||
e = (col("age") > lit(18)) & (col("status") == lit("active"))
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "((age > 18) AND (status = 'active'))"
|
||||
assert e.to_sql() == "((age > 18) AND (`status` = 'active'))"
|
||||
|
||||
def test_or_operator(self):
|
||||
e = (col("a") == lit(1)) | (col("b") == lit(2))
|
||||
@@ -166,7 +166,7 @@ class TestExprOperators:
|
||||
def test_coerce_plain_str(self):
|
||||
e = col("name") == "alice"
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "(name = 'alice')"
|
||||
assert e.to_sql() == "(`name` = 'alice')"
|
||||
|
||||
def test_reflexive_comparisons(self):
|
||||
# 10 < col("age") swaps to col("age") > 10
|
||||
@@ -198,85 +198,85 @@ class TestExprBytesLiteral:
|
||||
|
||||
def test_bytes_equality_expr_sql(self):
|
||||
e = col("data") == lit(b"\xca\xfe")
|
||||
assert e.to_sql() == "(data = X'CAFE')"
|
||||
assert e.to_sql() == "(`data` = X'CAFE')"
|
||||
|
||||
def test_bytes_ne_expr_sql(self):
|
||||
e = col("data") != lit(b"\xff")
|
||||
assert e.to_sql() == "(data <> X'FF')"
|
||||
assert e.to_sql() == "(`data` <> X'FF')"
|
||||
|
||||
def test_bytes_compound_expr_sql(self):
|
||||
e = (col("data") == lit(b"\x01")) & (col("id") > lit(5))
|
||||
assert e.to_sql() == "((data = X'01') AND (id > 5))"
|
||||
assert e.to_sql() == "((`data` = X'01') AND (id > 5))"
|
||||
|
||||
def test_bytes_in_function_call(self):
|
||||
# Regression test: binary literals inside scalar function calls
|
||||
# used to fail because DataFusion's unparser does not support Binary
|
||||
# scalars. Now handled via a placeholder-substitution rewrite.
|
||||
e = func("contains", col("data"), lit(b"\xff"))
|
||||
assert e.to_sql() == "contains(data, X'FF')"
|
||||
assert e.to_sql() == "contains(`data`, X'FF')"
|
||||
|
||||
def test_bytes_in_not(self):
|
||||
e = ~(col("data") == lit(b"\xff"))
|
||||
assert e.to_sql() == "NOT (data = X'FF')"
|
||||
assert e.to_sql() == "NOT (`data` = X'FF')"
|
||||
|
||||
|
||||
class TestExprStringMethods:
|
||||
def test_lower(self):
|
||||
e = col("name").lower()
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "lower(name)"
|
||||
assert e.to_sql() == "lower(`name`)"
|
||||
|
||||
def test_upper(self):
|
||||
e = col("name").upper()
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "upper(name)"
|
||||
assert e.to_sql() == "upper(`name`)"
|
||||
|
||||
def test_contains(self):
|
||||
e = col("text").contains(lit("hello"))
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "contains(text, 'hello')"
|
||||
assert e.to_sql() == "contains(`text`, 'hello')"
|
||||
|
||||
def test_contains_with_str_coerce(self):
|
||||
e = col("text").contains("hello")
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "contains(text, 'hello')"
|
||||
assert e.to_sql() == "contains(`text`, 'hello')"
|
||||
|
||||
def test_chained_lower_eq(self):
|
||||
e = col("name").lower() == lit("alice")
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "(lower(name) = 'alice')"
|
||||
assert e.to_sql() == "(lower(`name`) = 'alice')"
|
||||
|
||||
|
||||
class TestExprCast:
|
||||
def test_cast_string(self):
|
||||
e = col("id").cast("string")
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "CAST(id AS VARCHAR)"
|
||||
assert e.to_sql() == "arrow_cast(id, 'Utf8')"
|
||||
|
||||
def test_cast_int32(self):
|
||||
e = col("score").cast("int32")
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "CAST(score AS INTEGER)"
|
||||
assert e.to_sql() == "arrow_cast(score, 'Int32')"
|
||||
|
||||
def test_cast_float64(self):
|
||||
e = col("val").cast("float64")
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "CAST(val AS DOUBLE)"
|
||||
assert e.to_sql() == "arrow_cast(val, 'Float64')"
|
||||
|
||||
def test_cast_pyarrow_type(self):
|
||||
e = col("score").cast(pa.int32())
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "CAST(score AS INTEGER)"
|
||||
assert e.to_sql() == "arrow_cast(score, 'Int32')"
|
||||
|
||||
def test_cast_pyarrow_float64(self):
|
||||
e = col("val").cast(pa.float64())
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "CAST(val AS DOUBLE)"
|
||||
assert e.to_sql() == "arrow_cast(val, 'Float64')"
|
||||
|
||||
def test_cast_pyarrow_string(self):
|
||||
e = col("id").cast(pa.string())
|
||||
assert isinstance(e, Expr)
|
||||
assert e.to_sql() == "CAST(id AS VARCHAR)"
|
||||
assert e.to_sql() == "arrow_cast(id, 'Utf8')"
|
||||
|
||||
def test_cast_pyarrow_and_string_equivalent(self):
|
||||
# pa.int32() and "int32" should produce equivalent SQL
|
||||
@@ -597,14 +597,14 @@ class TestExprIsin:
|
||||
def test_isin_strs(self):
|
||||
assert (
|
||||
col("status").isin(["active", "pending"]).to_sql()
|
||||
== "status IN ('active', 'pending')"
|
||||
== "`status` IN ('active', 'pending')"
|
||||
)
|
||||
|
||||
def test_isin_coerces_and_mixes(self):
|
||||
assert col("id").isin([lit(1), 2]).to_sql() == "id IN (1, 2)"
|
||||
|
||||
def test_isin_empty(self):
|
||||
assert col("id").isin([]).to_sql() == "id IN ()"
|
||||
assert col("id").isin([]).to_sql() == "false"
|
||||
|
||||
def test_isin_filter(self, simple_table):
|
||||
result = simple_table.search().where(col("id").isin([1, 3, 5])).to_arrow()
|
||||
|
||||
@@ -11,6 +11,7 @@ import warnings
|
||||
import weakref
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from datetime import date, datetime, timedelta
|
||||
from decimal import Decimal
|
||||
from time import sleep
|
||||
from typing import List
|
||||
from unittest.mock import patch
|
||||
@@ -336,6 +337,21 @@ async def test_update_async(mem_db_async: AsyncConnection):
|
||||
assert await table.count_rows("id == 10") == 1
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_update_expr_filter_literals_async(mem_db_async: AsyncConnection):
|
||||
values = ["5", "4.66e-84", "it's"]
|
||||
table = await mem_db_async.create_table(
|
||||
"update_expr_literals",
|
||||
data=[{"field": value, "result": "original"} for value in values],
|
||||
)
|
||||
|
||||
for value in values:
|
||||
update_res = await table.update({"result": value}, where=col("field") == value)
|
||||
assert update_res.rows_updated == 1
|
||||
|
||||
assert (await table.to_arrow())["result"].to_pylist() == values
|
||||
|
||||
|
||||
def test_create_table(mem_db: DBConnection):
|
||||
schema = pa.schema(
|
||||
{
|
||||
@@ -2282,6 +2298,148 @@ def test_update(mem_db: DBConnection):
|
||||
assert np.allclose(v, np.array([[1.2, 1.9], [1.1, 1.1]]))
|
||||
|
||||
|
||||
def test_update_expr_filter_literals(mem_db: DBConnection):
|
||||
values = ["5", "4.66e-84", "it's"]
|
||||
table = mem_db.create_table(
|
||||
"update_expr_literals",
|
||||
data=[{"field": value, "result": "original"} for value in values],
|
||||
)
|
||||
|
||||
for value in values:
|
||||
update_res = table.update(where=col("field") == value, values={"result": value})
|
||||
assert update_res.rows_updated == 1
|
||||
|
||||
assert table.to_arrow()["result"].to_pylist() == values
|
||||
|
||||
|
||||
def test_update_expr_filter_preserves_typed_semantics(mem_db: DBConnection):
|
||||
low = Decimal("1.234567890123456789")
|
||||
high = Decimal("1.234567890123456790")
|
||||
decimal_schema = pa.schema(
|
||||
[("val", pa.decimal128(19, 18)), ("result", pa.string())]
|
||||
)
|
||||
decimal_table = mem_db.create_table(
|
||||
"update_expr_decimal",
|
||||
pa.table(
|
||||
{"val": [low, high], "result": ["old", "old"]},
|
||||
schema=decimal_schema,
|
||||
),
|
||||
)
|
||||
predicate = col("val") < lit(high)
|
||||
assert decimal_table.search().where(predicate).to_arrow().num_rows == 1
|
||||
result = decimal_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 1
|
||||
|
||||
keyword_table = mem_db.create_table(
|
||||
"update_expr_keyword", [{"null": 1, "result": "old"}]
|
||||
)
|
||||
predicate = col("null") == 1
|
||||
assert keyword_table.search().where(predicate).to_arrow().num_rows == 1
|
||||
result = keyword_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 1
|
||||
|
||||
empty_in_table = mem_db.create_table(
|
||||
"update_expr_empty_in", [{"id": 1, "result": "old"}]
|
||||
)
|
||||
predicate = col("id").isin([])
|
||||
assert empty_in_table.search().where(predicate).to_arrow().num_rows == 0
|
||||
result = empty_in_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 0
|
||||
|
||||
marker = "__lancedb_binary_placeholder_0__"
|
||||
binary_schema = pa.schema(
|
||||
[("payload", pa.binary()), ("text", pa.string()), ("result", pa.string())]
|
||||
)
|
||||
binary_table = mem_db.create_table(
|
||||
"update_expr_binary",
|
||||
pa.table(
|
||||
{
|
||||
"payload": [b"\x01", b"\x02"],
|
||||
"text": ["other", marker],
|
||||
"result": ["old", "old"],
|
||||
},
|
||||
schema=binary_schema,
|
||||
),
|
||||
)
|
||||
predicate = (col("payload") == lit(b"\x01")) | (col("text") == marker)
|
||||
assert binary_table.search().where(predicate).to_arrow().num_rows == 2
|
||||
result = binary_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 2
|
||||
|
||||
nonfinite_table = mem_db.create_table(
|
||||
"update_expr_nonfinite",
|
||||
[{"x": 1.0, "result": "old"}, {"x": 2.0, "result": "old"}],
|
||||
)
|
||||
predicate = col("x") < float("inf")
|
||||
assert nonfinite_table.search().where(predicate).to_arrow().num_rows == 2
|
||||
result = nonfinite_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 2
|
||||
|
||||
float16_table = mem_db.create_table(
|
||||
"update_expr_float16",
|
||||
[{"x": 1.0, "result": "old"}, {"x": 3.0, "result": "old"}],
|
||||
)
|
||||
predicate = col("x").cast(pa.float16()) < 2.0
|
||||
assert float16_table.search().where(predicate).to_arrow().num_rows == 1
|
||||
result = float16_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 1
|
||||
|
||||
string_cast_table = mem_db.create_table(
|
||||
"update_expr_string_cast",
|
||||
[{"x": 1, "result": "old"}, {"x": 2, "result": "old"}],
|
||||
)
|
||||
predicate = col("x").cast("string") == "1"
|
||||
assert string_cast_table.search().where(predicate).to_arrow().num_rows == 1
|
||||
result = string_cast_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 1
|
||||
|
||||
quoted_identifier_schema = pa.schema(
|
||||
[("payload", pa.binary()), ("odd'name", pa.int64()), ("result", pa.string())]
|
||||
)
|
||||
quoted_identifier_table = mem_db.create_table(
|
||||
"update_expr_quoted_identifier",
|
||||
pa.table(
|
||||
{"payload": [b"\x01"], "odd'name": [1], "result": ["old"]},
|
||||
schema=quoted_identifier_schema,
|
||||
),
|
||||
)
|
||||
predicate = (col("payload") == lit(b"\x01")) & (col("odd'name") == 1)
|
||||
assert quoted_identifier_table.search().where(predicate).to_arrow().num_rows == 1
|
||||
result = quoted_identifier_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 1
|
||||
|
||||
decimal256_schema = pa.schema(
|
||||
[("val", pa.decimal256(40, 2)), ("result", pa.string())]
|
||||
)
|
||||
decimal256_table = mem_db.create_table(
|
||||
"update_expr_decimal256",
|
||||
pa.table(
|
||||
{
|
||||
"val": [Decimal("1.00"), Decimal("3.00")],
|
||||
"result": ["old", "old"],
|
||||
},
|
||||
schema=decimal256_schema,
|
||||
),
|
||||
)
|
||||
predicate = col("val") < lit(Decimal("2.00")).cast(pa.decimal256(40, 2))
|
||||
assert decimal256_table.search().where(predicate).to_arrow().num_rows == 1
|
||||
result = decimal256_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 1
|
||||
|
||||
binary_empty_table = mem_db.create_table(
|
||||
"update_expr_binary_empty",
|
||||
pa.table(
|
||||
{"payload": [b"\x01", b"\x02"], "result": ["old", "old"]},
|
||||
schema=pa.schema([("payload", pa.binary()), ("result", pa.string())]),
|
||||
),
|
||||
)
|
||||
predicate = (col("payload") == lit(b"\x01")).isin([])
|
||||
assert binary_empty_table.search().where(predicate).to_arrow().num_rows == 0
|
||||
assert predicate.to_sql() == "false"
|
||||
result = binary_empty_table.update(where=predicate, values={"result": "new"})
|
||||
assert result.rows_updated == 0
|
||||
|
||||
|
||||
def test_update_with_arrow_scalar(mem_db: DBConnection):
|
||||
schema = pa.schema({"id": pa.int64(), "vector": pa.list_(pa.float32(), 4)})
|
||||
table = mem_db.create_table("my_table", schema=schema)
|
||||
|
||||
@@ -130,6 +130,14 @@ impl PyExpr {
|
||||
|
||||
// ── utilities ────────────────────────────────────────────────────────────
|
||||
|
||||
/// Return the referenced column name for a bare column expression.
|
||||
fn column_name(&self) -> Option<String> {
|
||||
match &self.0 {
|
||||
DfExpr::Column(column) if column.relation.is_none() => Some(column.name.clone()),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
|
||||
/// Render the expression as a SQL string (useful for debugging).
|
||||
fn to_sql(&self) -> PyResult<String> {
|
||||
lancedb::expr::expr_to_sql_string(&self.0).map_err(|e| PyValueError::new_err(e.to_string()))
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
use std::time::Duration;
|
||||
|
||||
@@ -292,6 +293,7 @@ pub struct PyQueryRequest {
|
||||
pub filter: Option<PyQueryFilter>,
|
||||
pub full_text_search: Option<PyLanceDB<FtsQuery>>,
|
||||
pub select: PySelect,
|
||||
pub select_source_columns: Option<HashMap<String, String>>,
|
||||
pub fast_search: Option<bool>,
|
||||
pub with_row_id: Option<bool>,
|
||||
pub use_lsm: Option<bool>,
|
||||
@@ -322,6 +324,7 @@ impl From<AnyQuery> for PyQueryRequest {
|
||||
full_text_search: query_request
|
||||
.full_text_search
|
||||
.map(|fts| PyLanceDB(fts.query)),
|
||||
select_source_columns: PySelect::source_columns(&query_request.select),
|
||||
select: PySelect(query_request.select),
|
||||
fast_search: Some(query_request.fast_search),
|
||||
with_row_id: Some(query_request.with_row_id),
|
||||
@@ -347,6 +350,7 @@ impl From<AnyQuery> for PyQueryRequest {
|
||||
offset: vector_query.base.offset,
|
||||
filter: vector_query.base.filter.map(PyQueryFilter),
|
||||
full_text_search: None,
|
||||
select_source_columns: PySelect::source_columns(&vector_query.base.select),
|
||||
select: PySelect(vector_query.base.select),
|
||||
fast_search: Some(vector_query.base.fast_search),
|
||||
with_row_id: Some(vector_query.base.with_row_id),
|
||||
@@ -379,6 +383,25 @@ impl From<AnyQuery> for PyQueryRequest {
|
||||
#[derive(Clone)]
|
||||
pub struct PySelect(Select);
|
||||
|
||||
impl PySelect {
|
||||
fn source_columns(select: &Select) -> Option<HashMap<String, String>> {
|
||||
match select {
|
||||
Select::Expr(pairs) => Some(
|
||||
pairs
|
||||
.iter()
|
||||
.filter_map(|(output, expr)| match expr {
|
||||
lancedb::expr::DfExpr::Column(column) if column.relation.is_none() => {
|
||||
Some((output.clone(), column.name.clone()))
|
||||
}
|
||||
_ => None,
|
||||
})
|
||||
.collect(),
|
||||
),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'py> IntoPyObject<'py> for PySelect {
|
||||
type Target = PyAny;
|
||||
type Output = Bound<'py, Self::Target>;
|
||||
|
||||
+120
-4
@@ -156,7 +156,7 @@ mod tests {
|
||||
use datafusion_common::ScalarValue;
|
||||
let expr = col("data").eq(lit(ScalarValue::Binary(Some(vec![0xca, 0xfe]))));
|
||||
let sql = expr_to_sql_string(&expr).unwrap();
|
||||
assert_eq!(sql, "(data = X'CAFE')");
|
||||
assert_eq!(sql, "(`data` = X'CAFE')");
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -166,7 +166,7 @@ mod tests {
|
||||
let int_expr = col("id").gt(lit(5i64));
|
||||
let combined = bin_expr.and(int_expr);
|
||||
let sql = expr_to_sql_string(&combined).unwrap();
|
||||
assert_eq!(sql, "((data = X'01') AND (id > 5))");
|
||||
assert_eq!(sql, "((`data` = X'01') AND (id > 5))");
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -184,7 +184,7 @@ mod tests {
|
||||
// serialized correctly (regression test for placeholder rewrite path).
|
||||
let expr = contains(col("data"), lit(ScalarValue::Binary(Some(vec![0xff]))));
|
||||
let sql = expr_to_sql_string(&expr).unwrap();
|
||||
assert_eq!(sql, "contains(data, X'FF')");
|
||||
assert_eq!(sql, "contains(`data`, X'FF')");
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -195,7 +195,7 @@ mod tests {
|
||||
.eq(lit(ScalarValue::Binary(Some(vec![0xab, 0xcd]))))
|
||||
.not();
|
||||
let sql = expr_to_sql_string(&expr).unwrap();
|
||||
assert_eq!(sql, "NOT (data = X'ABCD')");
|
||||
assert_eq!(sql, "NOT (`data` = X'ABCD')");
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -205,6 +205,122 @@ mod tests {
|
||||
assert!(sql.contains("IN"), "expected IN in: {}", sql);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_empty_is_in() {
|
||||
let expr = is_in(col("id"), vec![]);
|
||||
assert_eq!(expr_to_sql_string(&expr).unwrap(), "false");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_empty_is_in_discards_binary_children() {
|
||||
use datafusion_common::ScalarValue;
|
||||
|
||||
let expr = is_in(
|
||||
col("payload").eq(lit(ScalarValue::Binary(Some(vec![0x01])))),
|
||||
vec![],
|
||||
);
|
||||
assert_eq!(expr_to_sql_string(&expr).unwrap(), "false");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_keyword_identifier() {
|
||||
let expr = col("null").eq(lit(1i64));
|
||||
assert_eq!(expr_to_sql_string(&expr).unwrap(), "(`null` = 1)");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_decimal_literal_preserves_type() {
|
||||
use datafusion_common::ScalarValue;
|
||||
|
||||
let expr = col("val").lt(lit(ScalarValue::Decimal128(
|
||||
Some(1_234_567_890_123_456_790),
|
||||
19,
|
||||
18,
|
||||
)));
|
||||
let sql = expr_to_sql_string(&expr).unwrap();
|
||||
assert_eq!(
|
||||
sql,
|
||||
"(val < arrow_cast('1.234567890123456790', 'Decimal128(19, 18)'))"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_non_finite_float_literal_preserves_type() {
|
||||
let expr = col("x").lt(lit(f64::INFINITY));
|
||||
assert_eq!(
|
||||
expr_to_sql_string(&expr).unwrap(),
|
||||
"(x < arrow_cast('inf', 'Float64'))"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_cast_uses_arrow_type_name() {
|
||||
let string = expr_cast(col("x"), DataType::Utf8);
|
||||
assert_eq!(
|
||||
expr_to_sql_string(&string).unwrap(),
|
||||
"arrow_cast(x, 'Utf8')"
|
||||
);
|
||||
|
||||
let int32 = expr_cast(col("x"), DataType::Int32);
|
||||
assert_eq!(
|
||||
expr_to_sql_string(&int32).unwrap(),
|
||||
"arrow_cast(x, 'Int32')"
|
||||
);
|
||||
|
||||
let expr = expr_cast(col("x"), DataType::Float16).lt(lit(2.0));
|
||||
assert_eq!(
|
||||
expr_to_sql_string(&expr).unwrap(),
|
||||
"(arrow_cast(x, 'Float16') < 2.0)"
|
||||
);
|
||||
|
||||
let decimal = expr_cast(lit("2.00"), DataType::Decimal256(40, 2));
|
||||
assert_eq!(
|
||||
expr_to_sql_string(&decimal).unwrap(),
|
||||
"arrow_cast('2.00', 'Decimal256(40, 2)')"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_binary_placeholder_does_not_rewrite_user_string() {
|
||||
use datafusion_common::ScalarValue;
|
||||
|
||||
let marker = "__lancedb_binary_placeholder_0__";
|
||||
let expr = col("payload")
|
||||
.eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
|
||||
.or(col("text").eq(lit(marker)));
|
||||
assert_eq!(
|
||||
expr_to_sql_string(&expr).unwrap(),
|
||||
"((payload = X'01') OR (`text` = '__lancedb_binary_placeholder_0__'))"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_binary_binding_skips_quoted_identifiers() {
|
||||
use datafusion_common::ScalarValue;
|
||||
|
||||
let expr = col("payload")
|
||||
.eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
|
||||
.and(col("odd'name").eq(lit(1i64)))
|
||||
.and(col("odd`'name").eq(lit(2i64)));
|
||||
assert_eq!(
|
||||
expr_to_sql_string(&expr).unwrap(),
|
||||
"(((payload = X'01') AND (`odd'name` = 1)) AND (`odd``'name` = 2))"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_binary_placeholder_collision_search_is_linear() {
|
||||
use datafusion_common::ScalarValue;
|
||||
|
||||
let collision_shaped = format!("__lancedb_binary_placeholder_0__{}", "_".repeat(64_000));
|
||||
let expr = col("payload")
|
||||
.eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
|
||||
.and(col("text").eq(lit(collision_shaped.clone())));
|
||||
let sql = expr_to_sql_string(&expr).unwrap();
|
||||
assert!(sql.contains("X'01'"));
|
||||
assert!(sql.contains(&format!("'{collision_shaped}'")));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_multiple_binary_literals() {
|
||||
use datafusion_common::ScalarValue;
|
||||
|
||||
+218
-41
@@ -1,9 +1,19 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
use std::collections::{HashMap, HashSet};
|
||||
|
||||
use arrow_array::types::{
|
||||
Decimal32Type, Decimal64Type, Decimal128Type, Decimal256Type, DecimalType,
|
||||
};
|
||||
use arrow_schema::DataType;
|
||||
use datafusion_common::ScalarValue;
|
||||
use datafusion_common::tree_node::{Transformed, TreeNode, TreeNodeRecursion};
|
||||
use datafusion_expr::Expr;
|
||||
use datafusion_functions::core::expr_fn::{
|
||||
arrow_cast as datafusion_arrow_cast, arrow_try_cast as datafusion_arrow_try_cast,
|
||||
};
|
||||
use datafusion_sql::sqlparser::keywords::ALL_KEYWORDS;
|
||||
use datafusion_sql::unparser::{self, dialect::Dialect};
|
||||
|
||||
/// Unparser dialect that matches the quoting style expected by the Lance SQL
|
||||
@@ -21,11 +31,13 @@ struct LanceSqlDialect;
|
||||
|
||||
impl Dialect for LanceSqlDialect {
|
||||
fn identifier_quote_style(&self, identifier: &str) -> Option<char> {
|
||||
let needs_quote = identifier.chars().any(|c| c.is_ascii_uppercase())
|
||||
|| !identifier
|
||||
.chars()
|
||||
.enumerate()
|
||||
.all(|(i, c)| c == '_' || c.is_ascii_alphabetic() || (i > 0 && c.is_ascii_digit()));
|
||||
let identifier_upper = identifier.to_ascii_uppercase();
|
||||
let needs_quote =
|
||||
(identifier_upper != "ID" && ALL_KEYWORDS.contains(&identifier_upper.as_str()))
|
||||
|| identifier.chars().any(|c| c.is_ascii_uppercase())
|
||||
|| !identifier.chars().enumerate().all(|(i, c)| {
|
||||
c == '_' || c.is_ascii_alphabetic() || (i > 0 && c.is_ascii_digit())
|
||||
});
|
||||
if needs_quote { Some('`') } else { None }
|
||||
}
|
||||
}
|
||||
@@ -39,24 +51,128 @@ fn bytes_to_hex_sql(bytes: &[u8]) -> String {
|
||||
format!("X'{hex}'")
|
||||
}
|
||||
|
||||
/// Returns true if *expr* contains a `Binary` or `LargeBinary` scalar literal
|
||||
/// anywhere in its subtree. DataFusion's SQL unparser cannot serialize those
|
||||
/// variants, so we route such expressions through a placeholder-substitution
|
||||
/// path that emits SQL `X'...'` byte-string literals.
|
||||
fn has_binary_literal(expr: &Expr) -> bool {
|
||||
let mut found = false;
|
||||
fn string_literals(expr: &Expr) -> HashSet<String> {
|
||||
let mut literals = HashSet::new();
|
||||
let _ = expr.apply(&mut |e: &Expr| {
|
||||
if matches!(
|
||||
e,
|
||||
Expr::Literal(ScalarValue::Binary(_) | ScalarValue::LargeBinary(_), _)
|
||||
) {
|
||||
found = true;
|
||||
Ok(TreeNodeRecursion::Stop)
|
||||
} else {
|
||||
Ok(TreeNodeRecursion::Continue)
|
||||
if let Expr::Literal(
|
||||
ScalarValue::Utf8(Some(value))
|
||||
| ScalarValue::LargeUtf8(Some(value))
|
||||
| ScalarValue::Utf8View(Some(value)),
|
||||
_,
|
||||
) = e
|
||||
{
|
||||
literals.insert(value.clone());
|
||||
}
|
||||
Ok(TreeNodeRecursion::Continue)
|
||||
});
|
||||
found
|
||||
literals
|
||||
}
|
||||
|
||||
fn typed_string_literal(value: String, data_type: DataType) -> Expr {
|
||||
datafusion_arrow_cast(
|
||||
Expr::Literal(ScalarValue::Utf8(Some(value)), None),
|
||||
Expr::Literal(ScalarValue::Utf8(Some(data_type.to_string())), None),
|
||||
)
|
||||
}
|
||||
|
||||
fn next_binary_placeholder(user_strings: &HashSet<String>, next_id: &mut usize) -> String {
|
||||
loop {
|
||||
let placeholder = format!("{BINARY_PLACEHOLDER_PREFIX}{}__", *next_id);
|
||||
*next_id += 1;
|
||||
if !user_strings.contains(&placeholder) {
|
||||
return placeholder;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn bind_binary_literals(
|
||||
sql: &str,
|
||||
mut bindings: HashMap<String, Vec<u8>>,
|
||||
) -> crate::Result<String> {
|
||||
let bytes = sql.as_bytes();
|
||||
let mut output = Vec::with_capacity(bytes.len());
|
||||
let mut index = 0;
|
||||
|
||||
// Walk SQL string tokens once. Placeholders are plain, unescaped string
|
||||
// literals, so this remains linear even when user strings are large or
|
||||
// deliberately resemble the placeholder prefix.
|
||||
while index < bytes.len() {
|
||||
if bytes[index] == b'`' {
|
||||
let identifier_start = index;
|
||||
index += 1;
|
||||
let mut identifier_end = None;
|
||||
while index < bytes.len() {
|
||||
if bytes[index] == b'`' {
|
||||
if index + 1 < bytes.len() && bytes[index + 1] == b'`' {
|
||||
index += 2;
|
||||
} else {
|
||||
index += 1;
|
||||
identifier_end = Some(index);
|
||||
break;
|
||||
}
|
||||
} else {
|
||||
index += 1;
|
||||
}
|
||||
}
|
||||
|
||||
let Some(identifier_end) = identifier_end else {
|
||||
return Err(crate::Error::InvalidInput {
|
||||
message: "unterminated identifier while binding binary literal".to_string(),
|
||||
});
|
||||
};
|
||||
output.extend_from_slice(&bytes[identifier_start..identifier_end]);
|
||||
continue;
|
||||
}
|
||||
|
||||
if bytes[index] != b'\'' {
|
||||
output.push(bytes[index]);
|
||||
index += 1;
|
||||
continue;
|
||||
}
|
||||
|
||||
let literal_start = index;
|
||||
index += 1;
|
||||
let content_start = index;
|
||||
let mut escaped = false;
|
||||
let mut content_end = None;
|
||||
while index < bytes.len() {
|
||||
if bytes[index] == b'\'' {
|
||||
if index + 1 < bytes.len() && bytes[index + 1] == b'\'' {
|
||||
escaped = true;
|
||||
index += 2;
|
||||
} else {
|
||||
content_end = Some(index);
|
||||
index += 1;
|
||||
break;
|
||||
}
|
||||
} else {
|
||||
index += 1;
|
||||
}
|
||||
}
|
||||
|
||||
let Some(content_end) = content_end else {
|
||||
return Err(crate::Error::InvalidInput {
|
||||
message: "unterminated string while binding binary literal".to_string(),
|
||||
});
|
||||
};
|
||||
|
||||
let placeholder = &sql[content_start..content_end];
|
||||
if !escaped && let Some(value) = bindings.remove(placeholder) {
|
||||
output.extend_from_slice(bytes_to_hex_sql(&value).as_bytes());
|
||||
} else {
|
||||
output.extend_from_slice(&bytes[literal_start..index]);
|
||||
}
|
||||
}
|
||||
|
||||
if !bindings.is_empty() {
|
||||
return Err(crate::Error::InvalidInput {
|
||||
message: "failed to bind binary literal while serializing expression".to_string(),
|
||||
});
|
||||
}
|
||||
|
||||
String::from_utf8(output).map_err(|e| crate::Error::InvalidInput {
|
||||
message: format!("failed to bind binary literal: {e}"),
|
||||
})
|
||||
}
|
||||
|
||||
fn run_unparser(expr: &Expr) -> crate::Result<String> {
|
||||
@@ -69,25 +185,37 @@ fn run_unparser(expr: &Expr) -> crate::Result<String> {
|
||||
}
|
||||
|
||||
pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
|
||||
// Fast path: no binary literals — DataFusion's unparser handles everything.
|
||||
if !has_binary_literal(expr) {
|
||||
return run_unparser(expr);
|
||||
}
|
||||
|
||||
// Slow path: DataFusion's unparser cannot serialize `Binary`/`LargeBinary`
|
||||
// scalars, so we rewrite each one to a unique string-literal placeholder,
|
||||
// let the unparser do the rest of the work, then substitute the SQL
|
||||
// `X'...'` byte-string literal back in. This keeps the operator/function
|
||||
// serialization logic centralized in DataFusion and works for every
|
||||
// expression node type the unparser supports.
|
||||
let mut bindings: Vec<Vec<u8>> = Vec::new();
|
||||
// DataFusion's unparser needs a few adaptations before its SQL can be
|
||||
// reparsed by Lance without changing the typed expression's semantics:
|
||||
//
|
||||
// * decimal literals need an explicit cast to preserve precision and scale;
|
||||
// * casts need exact Arrow type names rather than SQL type aliases;
|
||||
// * an empty IN list is valid in DataFusion but invalid SQL;
|
||||
// * binary literals are unsupported by the unparser and need placeholders.
|
||||
// Eliminate empty membership expressions before visiting their children.
|
||||
// Otherwise a discarded binary child could leave behind a stale binding.
|
||||
let rewritten = expr
|
||||
.clone()
|
||||
.transform(|e: Expr| match e {
|
||||
Expr::InList(in_list) if in_list.list.is_empty() => Ok(Transformed::yes(
|
||||
Expr::Literal(ScalarValue::Boolean(Some(in_list.negated)), None),
|
||||
)),
|
||||
other => Ok(Transformed::no(other)),
|
||||
})
|
||||
.map_err(|e| crate::Error::InvalidInput {
|
||||
message: format!("failed to rewrite expression: {e}"),
|
||||
})?
|
||||
.data;
|
||||
|
||||
let user_strings = string_literals(&rewritten);
|
||||
let mut next_placeholder_id = 0;
|
||||
let mut binary_bindings = HashMap::new();
|
||||
let rewritten = rewritten
|
||||
.transform(|e: Expr| match e {
|
||||
Expr::Literal(ScalarValue::Binary(Some(bytes)), m)
|
||||
| Expr::Literal(ScalarValue::LargeBinary(Some(bytes)), m) => {
|
||||
let placeholder = format!("{}{}__", BINARY_PLACEHOLDER_PREFIX, bindings.len());
|
||||
bindings.push(bytes);
|
||||
let placeholder = next_binary_placeholder(&user_strings, &mut next_placeholder_id);
|
||||
binary_bindings.insert(placeholder.clone(), bytes);
|
||||
Ok(Transformed::yes(Expr::Literal(
|
||||
ScalarValue::Utf8(Some(placeholder)),
|
||||
m,
|
||||
@@ -97,6 +225,57 @@ pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
|
||||
| Expr::Literal(ScalarValue::LargeBinary(None), m) => {
|
||||
Ok(Transformed::yes(Expr::Literal(ScalarValue::Null, m)))
|
||||
}
|
||||
Expr::Literal(ScalarValue::Decimal32(Some(value), precision, scale), _m) => {
|
||||
let value = Decimal32Type::format_decimal(value, precision, scale);
|
||||
Ok(Transformed::yes(typed_string_literal(
|
||||
value,
|
||||
DataType::Decimal32(precision, scale),
|
||||
)))
|
||||
}
|
||||
Expr::Literal(ScalarValue::Decimal64(Some(value), precision, scale), _m) => {
|
||||
let value = Decimal64Type::format_decimal(value, precision, scale);
|
||||
Ok(Transformed::yes(typed_string_literal(
|
||||
value,
|
||||
DataType::Decimal64(precision, scale),
|
||||
)))
|
||||
}
|
||||
Expr::Literal(ScalarValue::Decimal128(Some(value), precision, scale), _m) => {
|
||||
let value = Decimal128Type::format_decimal(value, precision, scale);
|
||||
Ok(Transformed::yes(typed_string_literal(
|
||||
value,
|
||||
DataType::Decimal128(precision, scale),
|
||||
)))
|
||||
}
|
||||
Expr::Literal(ScalarValue::Decimal256(Some(value), precision, scale), _m) => {
|
||||
let value = Decimal256Type::format_decimal(value, precision, scale);
|
||||
Ok(Transformed::yes(typed_string_literal(
|
||||
value,
|
||||
DataType::Decimal256(precision, scale),
|
||||
)))
|
||||
}
|
||||
Expr::Literal(ScalarValue::Float16(Some(value)), _m) if !value.is_finite() => Ok(
|
||||
Transformed::yes(typed_string_literal(value.to_string(), DataType::Float16)),
|
||||
),
|
||||
Expr::Literal(ScalarValue::Float32(Some(value)), _m) if !value.is_finite() => Ok(
|
||||
Transformed::yes(typed_string_literal(value.to_string(), DataType::Float32)),
|
||||
),
|
||||
Expr::Literal(ScalarValue::Float64(Some(value)), _m) if !value.is_finite() => Ok(
|
||||
Transformed::yes(typed_string_literal(value.to_string(), DataType::Float64)),
|
||||
),
|
||||
Expr::Cast(cast) => Ok(Transformed::yes(datafusion_arrow_cast(
|
||||
*cast.expr,
|
||||
Expr::Literal(
|
||||
ScalarValue::Utf8(Some(cast.field.data_type().to_string())),
|
||||
None,
|
||||
),
|
||||
))),
|
||||
Expr::TryCast(cast) => Ok(Transformed::yes(datafusion_arrow_try_cast(
|
||||
*cast.expr,
|
||||
Expr::Literal(
|
||||
ScalarValue::Utf8(Some(cast.field.data_type().to_string())),
|
||||
None,
|
||||
),
|
||||
))),
|
||||
other => Ok(Transformed::no(other)),
|
||||
})
|
||||
.map_err(|e| crate::Error::InvalidInput {
|
||||
@@ -104,12 +283,10 @@ pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
|
||||
})?
|
||||
.data;
|
||||
|
||||
let mut sql = run_unparser(&rewritten)?;
|
||||
for (i, bytes) in bindings.iter().enumerate() {
|
||||
// The unparser quotes string literals with single quotes, so the
|
||||
// placeholder appears as `'__lancedb_binary_placeholder_<i>__'`.
|
||||
let quoted = format!("'{}{}__'", BINARY_PLACEHOLDER_PREFIX, i);
|
||||
sql = sql.replace("ed, &bytes_to_hex_sql(bytes));
|
||||
let sql = run_unparser(&rewritten)?;
|
||||
if binary_bindings.is_empty() {
|
||||
Ok(sql)
|
||||
} else {
|
||||
bind_binary_literals(&sql, binary_bindings)
|
||||
}
|
||||
Ok(sql)
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user