feat(nodejs): add order_by method to Query (#3123)

docs/src/js/classes/Query.md

@@ -343,6 +343,30 @@ This is useful for pagination.
 
 ***
 
+### orderBy()
+
+```ts
+orderBy(ordering): this
+```
+
+Sort the results by the specified column(s).
+
+#### Parameters
+
+* **ordering**: [`ColumnOrdering`](../interfaces/ColumnOrdering.md) \| [`ColumnOrdering`](../interfaces/ColumnOrdering.md)[]
+
+#### Returns
+
+`this`
+
+This query builder.
+
+#### Inherited from
+
+`StandardQueryBase.orderBy`
+
+***
+
 ### outputSchema()
 
 ```ts

docs/src/js/classes/VectorQuery.md

@@ -498,6 +498,30 @@ This is useful for pagination.
 
 ***
 
+### orderBy()
+
+```ts
+orderBy(ordering): this
+```
+
+Sort the results by the specified column(s).
+
+#### Parameters
+
+* **ordering**: [`ColumnOrdering`](../interfaces/ColumnOrdering.md) \| [`ColumnOrdering`](../interfaces/ColumnOrdering.md)[]
+
+#### Returns
+
+`this`
+
+This query builder.
+
+#### Inherited from
+
+`StandardQueryBase.orderBy`
+
+***
+
 ### outputSchema()
 
 ```ts

docs/src/js/globals.md

@@ -51,6 +51,7 @@
 - [AlterColumnsResult](interfaces/AlterColumnsResult.md)
 - [ClientConfig](interfaces/ClientConfig.md)
 - [ColumnAlteration](interfaces/ColumnAlteration.md)
+- [ColumnOrdering](interfaces/ColumnOrdering.md)
 - [CompactionStats](interfaces/CompactionStats.md)
 - [ConnectNamespaceOptions](interfaces/ConnectNamespaceOptions.md)
 - [ConnectionOptions](interfaces/ConnectionOptions.md)

docs/src/js/interfaces/ColumnOrdering.md

@@ -0,0 +1,31 @@
+[**@lancedb/lancedb**](../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../globals.md) / ColumnOrdering
+
+# Interface: ColumnOrdering
+
+## Properties
+
+### ascending?
+
+```ts
+optional ascending: boolean;
+```
+
+***
+
+### columnName
+
+```ts
+columnName: string;
+```
+
+***
+
+### nullsFirst?
+
+```ts
+optional nullsFirst: boolean;
+```

nodejs/__test__/query.test.ts

@@ -109,3 +109,209 @@ describe("Query outputSchema", () => {
     expect(schema.fields.length).toBe(3);
   });
 });
+
+describe("Query orderBy", () => {
+  let tmpDir: tmp.DirResult;
+  let table: Table;
+
+  beforeEach(async () => {
+    tmpDir = tmp.dirSync({ unsafeCleanup: true });
+    const db = await connect(tmpDir.name);
+
+    // Create table with numeric data for sorting
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field("score", new Float32(), true),
+      new Field("name", new Utf8(), true),
+    ]);
+
+    const data = makeArrowTable(
+      [
+        { id: 1n, score: 3.5, name: "charlie" },
+        { id: 2n, score: 1.2, name: "alice" },
+        { id: 3n, score: 2.8, name: "bob" },
+        { id: 4n, score: 0.5, name: "david" },
+        { id: 5n, score: 4.1, name: "eve" },
+      ],
+      { schema },
+    );
+    table = await db.createTable("test", data);
+  });
+
+  afterEach(() => {
+    tmpDir.removeCallback();
+  });
+
+  it("should sort by single column ascending", async () => {
+    const results = await table
+      .query()
+      .orderBy({ columnName: "score", ascending: true, nullsFirst: false })
+      .toArray();
+
+    expect(results.length).toBe(5);
+    // Verify ascending order
+    expect(results[0].score).toBeCloseTo(0.5, 0.001);
+    expect(results[1].score).toBeCloseTo(1.2, 0.001);
+    expect(results[2].score).toBeCloseTo(2.8, 0.001);
+    expect(results[3].score).toBeCloseTo(3.5, 0.001);
+    expect(results[4].score).toBeCloseTo(4.1, 0.001);
+  });
+
+  it("should sort by single column descending", async () => {
+    const results = await table
+      .query()
+      .orderBy({ columnName: "score", ascending: false, nullsFirst: false })
+      .toArray();
+
+    expect(results.length).toBe(5);
+    // Verify descending order
+    expect(results[0].score).toBeCloseTo(4.1, 0.001);
+    expect(results[1].score).toBeCloseTo(3.5, 0.001);
+    expect(results[2].score).toBeCloseTo(2.8, 0.001);
+    expect(results[3].score).toBeCloseTo(1.2, 0.001);
+    expect(results[4].score).toBeCloseTo(0.5, 0.001);
+  });
+
+  it("should use ascending as default direction", async () => {
+    const results = await table
+      .query()
+      .orderBy({ columnName: "score" })
+      .toArray();
+
+    expect(results.length).toBe(5);
+    // Verify ascending order (default)
+    expect(results[0].score).toBeCloseTo(0.5, 0.001);
+    expect(results[1].score).toBeCloseTo(1.2, 0.001);
+    expect(results[2].score).toBeCloseTo(2.8, 0.001);
+    expect(results[3].score).toBeCloseTo(3.5, 0.001);
+    expect(results[4].score).toBeCloseTo(4.1, 0.001);
+  });
+
+  it("should sort by string column", async () => {
+    const results = await table
+      .query()
+      .orderBy({ columnName: "name" })
+      .toArray();
+
+    expect(results.length).toBe(5);
+    // Verify alphabetical order
+    expect(results[0].name).toBe("alice");
+    expect(results[1].name).toBe("bob");
+    expect(results[2].name).toBe("charlie");
+    expect(results[3].name).toBe("david");
+    expect(results[4].name).toBe("eve");
+  });
+
+  it("should support method chaining with where", async () => {
+    const results = await table
+      .query()
+      .where("score > 2.0")
+      .orderBy({ columnName: "score" })
+      .toArray();
+    expect(results.length).toBe(3);
+    // Verify filtered and sorted
+    expect(results[0].score).toBeCloseTo(2.8, 0.001);
+    expect(results[1].score).toBeCloseTo(3.5, 0.001);
+    expect(results[2].score).toBeCloseTo(4.1, 0.001);
+  });
+
+  it("should support method chaining with limit", async () => {
+    const results = await table
+      .query()
+      .orderBy({ columnName: "score", ascending: false })
+      .limit(3)
+      .toArray();
+
+    expect(results.length).toBe(3);
+    // Verify top 3 in descending order
+    expect(results[0].score).toBeCloseTo(4.1, 0.001);
+    expect(results[1].score).toBeCloseTo(3.5, 0.001);
+    expect(results[2].score).toBeCloseTo(2.8, 0.001);
+  });
+
+  it("should support method chaining with offset", async () => {
+    const results = await table
+      .query()
+      .orderBy({ columnName: "score" })
+      .offset(2)
+      .limit(2)
+      .toArray();
+
+    expect(results.length).toBe(2);
+    // Verify results skip first 2 and take next 2
+    expect(results[0].score).toBeCloseTo(2.8, 0.001);
+    expect(results[1].score).toBeCloseTo(3.5, 0.001);
+  });
+
+  it("should support method chaining with select", async () => {
+    const results = await table
+      .query()
+      .orderBy({ columnName: "name" })
+      .select(["name", "score"])
+      .toArray();
+
+    expect(results.length).toBe(5);
+    // Verify only selected columns are present
+    expect(Object.keys(results[0])).toEqual(["name", "score"]);
+    expect(Object.keys(results[4])).toEqual(["name", "score"]);
+    // Verify sorted by name
+    expect(results[0].name).toBe("alice");
+    expect(results[4].name).toBe("eve");
+  });
+
+  it("should support complex method chaining", async () => {
+    const results = await table
+      .query()
+      .where("score > 1.0")
+      .orderBy({ columnName: "score", ascending: false })
+      .limit(3)
+      .select(["id", "score", "name"])
+      .toArray();
+
+    expect(results.length).toBe(3);
+    // Verify filtered, sorted, limited, and projected
+    expect(results[0].score).toBeCloseTo(4.1, 0.001);
+    expect(results[1].score).toBeCloseTo(3.5, 0.001);
+    expect(results[2].score).toBeCloseTo(2.8, 0.001);
+    expect(Object.keys(results[0])).toEqual(["id", "score", "name"]);
+  });
+
+  it("should support multi-column ordering and null placement", async () => {
+    const schema = new Schema([
+      new Field("group", new Int64(), true),
+      new Field("score", new Float32(), true),
+      new Field("name", new Utf8(), true),
+    ]);
+
+    const data = makeArrowTable(
+      [
+        { group: 1n, score: null, name: "z" },
+        { group: 1n, score: 1.0, name: "b" },
+        { group: 1n, score: 1.0, name: "a" },
+        { group: 2n, score: 0.5, name: "c" },
+      ],
+      { schema },
+    );
+    const nullTable = await (await connect(tmpDir.name)).createTable(
+      "test_multi_order",
+      data,
+      { mode: "overwrite" },
+    );
+
+    const results = await nullTable
+      .query()
+      .orderBy([
+        { columnName: "group", ascending: true, nullsFirst: false },
+        { columnName: "score", ascending: true, nullsFirst: true },
+        { columnName: "name", ascending: true, nullsFirst: false },
+      ])
+      .toArray();
+
+    expect(results.map((r) => [r.group, r.score, r.name])).toEqual([
+      [1n, null, "z"],
+      [1n, 1.0, "a"],
+      [1n, 1.0, "b"],
+      [2n, 0.5, "c"],
+    ]);
+  });
+});

nodejs/examples/filtering.test.ts

@@ -38,5 +38,14 @@ test("filtering examples", async () => {
     // --8<-- [start:sql_search]
     await tbl.query().where("id = 10").limit(10).toArray();
     // --8<-- [end:sql_search]
+
+    // --8<-- [start:orderby_search]
+    await tbl
+      .query()
+      .where("id > 10")
+      .orderBy({ columnName: "id", ascending: false })
+      .limit(5)
+      .toArray();
+    // --8<-- [end:orderby_search]
   });
 });

nodejs/lancedb/index.ts

@@ -82,6 +82,7 @@ export {
   VectorQuery,
   TakeQuery,
   QueryExecutionOptions,
+  ColumnOrdering,
   FullTextSearchOptions,
   RecordBatchIterator,
   FullTextQuery,

nodejs/lancedb/query.ts

@@ -79,6 +79,12 @@ export interface QueryExecutionOptions {
   timeoutMs?: number;
 }
 
+export interface ColumnOrdering {
+  columnName: string;
+  ascending?: boolean;
+  nullsFirst?: boolean;
+}
+
 /**
  * Options that control the behavior of a full text search
  */
@@ -417,6 +423,21 @@ export class StandardQueryBase<
     return this;
   }
 
+  /**
+   * Sort the results by the specified column(s).
+   * @returns This query builder.
+   */
+  orderBy(ordering: ColumnOrdering | ColumnOrdering[]): this {
+    const orderings = Array.isArray(ordering) ? ordering : [ordering];
+    const normalized = orderings.map((o) => ({
+      columnName: o.columnName,
+      ascending: o.ascending ?? true,
+      nullsFirst: o.nullsFirst ?? false,
+    }));
+    this.doCall((inner) => inner.orderBy(normalized));
+    return this;
+  }
+
   /**
    * Skip searching un-indexed data. This can make search faster, but will miss
    * any data that is not yet indexed.

nodejs/src/query.rs

@@ -3,6 +3,12 @@
 
 use std::sync::Arc;
 
+use crate::error::NapiErrorExt;
+use crate::error::convert_error;
+use crate::iterator::RecordBatchIterator;
+use crate::rerankers::RerankHybridCallbackArgs;
+use crate::rerankers::Reranker;
+use crate::util::{parse_distance_type, schema_to_buffer};
 use arrow_array::{
     Array, Float16Array as ArrowFloat16Array, Float32Array as ArrowFloat32Array,
     Float64Array as ArrowFloat64Array, UInt8Array as ArrowUInt8Array,
@@ -19,16 +25,27 @@ use lancedb::query::QueryBase;
 use lancedb::query::QueryExecutionOptions;
 use lancedb::query::Select;
 use lancedb::query::TakeQuery as LanceDbTakeQuery;
-use lancedb::query::VectorQuery as LanceDbVectorQuery;
+use lancedb::query::{ColumnOrdering as LanceDbColumnOrdering, VectorQuery as LanceDbVectorQuery};
 use napi::bindgen_prelude::*;
 use napi_derive::napi;
 
-use crate::error::NapiErrorExt;
-use crate::error::convert_error;
-use crate::iterator::RecordBatchIterator;
-use crate::rerankers::RerankHybridCallbackArgs;
-use crate::rerankers::Reranker;
-use crate::util::{parse_distance_type, schema_to_buffer};
+#[napi(object)]
+pub struct ColumnOrdering {
+    pub ascending: bool,
+    pub nulls_first: bool,
+    pub column_name: String,
+}
+
+impl From<ColumnOrdering> for LanceDbColumnOrdering {
+    fn from(value: ColumnOrdering) -> Self {
+        match (value.ascending, value.nulls_first) {
+            (true, true) => Self::asc_nulls_first(value.column_name),
+            (true, false) => Self::asc_nulls_last(value.column_name),
+            (false, true) => Self::desc_nulls_first(value.column_name),
+            (false, false) => Self::desc_nulls_last(value.column_name),
+        }
+    }
+}
 
 fn bytes_to_arrow_array(data: Uint8Array, dtype: String) -> napi::Result<Arc<dyn Array>> {
     let buf = arrow_buffer::Buffer::from(data.to_vec());
@@ -128,6 +145,18 @@ impl Query {
         self.inner = self.inner.clone().with_row_id();
     }
 
+    #[napi]
+    pub fn order_by(&mut self, ordering: Option<Vec<ColumnOrdering>>) -> napi::Result<()> {
+        let ordering = ordering.map(|ordering| {
+            ordering
+                .into_iter()
+                .map(LanceDbColumnOrdering::from)
+                .collect()
+        });
+        self.inner = self.inner.clone().order_by(ordering);
+        Ok(())
+    }
+
     #[napi(catch_unwind)]
     pub async fn output_schema(&self) -> napi::Result<Buffer> {
         let schema = self.inner.output_schema().await.default_error()?;
@@ -328,6 +357,18 @@ impl VectorQuery {
         Ok(())
     }
 
+    #[napi]
+    pub fn order_by(&mut self, ordering: Option<Vec<ColumnOrdering>>) -> napi::Result<()> {
+        let ordering = ordering.map(|ordering| {
+            ordering
+                .into_iter()
+                .map(LanceDbColumnOrdering::from)
+                .collect()
+        });
+        self.inner = self.inner.clone().order_by(ordering);
+        Ok(())
+    }
+
     #[napi(catch_unwind)]
     pub async fn output_schema(&self) -> napi::Result<Buffer> {
         let schema = self.inner.output_schema().await.default_error()?;

python/python/lancedb/_lancedb.pyi

@@ -255,6 +255,11 @@ class RecordBatchStream:
     def __aiter__(self) -> "RecordBatchStream": ...
     async def __anext__(self) -> pa.RecordBatch: ...
 
+class ColumnOrdering(TypedDict):
+    column_name: str
+    ascending: bool
+    nulls_first: bool
+
 class Query:
     def where(self, filter: str): ...
     def where_expr(self, expr: PyExpr): ...
@@ -268,6 +273,7 @@ class Query:
     def postfilter(self): ...
     def nearest_to(self, query_vec: pa.Array) -> VectorQuery: ...
     def nearest_to_text(self, query: dict) -> FTSQuery: ...
+    def order_by(self, ordering: Optional[List[ColumnOrdering]]): ...
     async def output_schema(self) -> pa.Schema: ...
     async def execute(
         self, max_batch_length: Optional[int], timeout: Optional[timedelta]
@@ -296,6 +302,7 @@ class FTSQuery:
     def get_query(self) -> str: ...
     def add_query_vector(self, query_vec: pa.Array) -> None: ...
     def nearest_to(self, query_vec: pa.Array) -> HybridQuery: ...
+    def order_by(self, ordering: Optional[List[ColumnOrdering]]): ...
     async def output_schema(self) -> pa.Schema: ...
     async def execute(
         self, max_batch_length: Optional[int], timeout: Optional[timedelta]
@@ -321,6 +328,7 @@ class VectorQuery:
     def maximum_nprobes(self, maximum_nprobes: int): ...
     def bypass_vector_index(self): ...
     def nearest_to_text(self, query: dict) -> HybridQuery: ...
+    def order_by(self, ordering: Optional[List[ColumnOrdering]]): ...
     def to_query_request(self) -> PyQueryRequest: ...
 
 class HybridQuery:
@@ -339,6 +347,7 @@ class HybridQuery:
     def minimum_nprobes(self, minimum_nprobes: int): ...
     def maximum_nprobes(self, maximum_nprobes: int): ...
     def bypass_vector_index(self): ...
+    def order_by(self, ordering: Optional[List[ColumnOrdering]]): ...
     def to_vector_query(self) -> VectorQuery: ...
     def to_fts_query(self) -> FTSQuery: ...
     def get_limit(self) -> int: ...
@@ -368,6 +377,7 @@ class PyQueryRequest:
     bypass_vector_index: Optional[bool]
     postfilter: Optional[bool]
     norm: Optional[str]
+    order_by: Optional[List[ColumnOrdering]]
 
 class CompactionStats:
     fragments_removed: int

python/python/lancedb/query.py

@@ -92,6 +92,12 @@ def ensure_vector_query(
         return val
 
 
+class ColumnOrdering(pydantic.BaseModel):
+    column_name: str
+    ascending: bool = True
+    nulls_first: bool = False
+
+
 class FullTextQueryType(str, Enum):
     MATCH = "match"
     MATCH_PHRASE = "match_phrase"
@@ -504,6 +510,8 @@ class Query(pydantic.BaseModel):
     # Bypass the vector index and use a brute force search
     bypass_vector_index: Optional[bool] = None
 
+    order_by: Optional[List[ColumnOrdering]] = None
+
     @classmethod
     def from_inner(cls, req: PyQueryRequest) -> Self:
         query = cls()
@@ -524,6 +532,8 @@ class Query(pydantic.BaseModel):
         query.refine_factor = req.refine_factor
         query.bypass_vector_index = req.bypass_vector_index
         query.postfilter = req.postfilter
+        if req.order_by is not None:
+            query.order_by = [ColumnOrdering(**o) for o in req.order_by]
         if req.full_text_search is not None:
             query.full_text_query = FullTextSearchQuery(
                 columns=None,
@@ -572,9 +582,22 @@ class LanceQueryBuilder(ABC):
             If "auto", the query type is inferred based on the query.
         vector_column_name: str
             The name of the vector column to use for vector search.
+        ordering_field_name: Optional[str]
+            .. deprecated:: 0.27.0
+                Use ``order_by()`` method instead.
+        fts_columns: Optional[Union[str, List[str]]]
+            The columns to search in for full text search.
         fast_search: bool
             Skip flat search of unindexed data.
         """
+        if ordering_field_name is not None:
+            import warnings
+
+            warnings.warn(
+                "ordering_field_name is deprecated, use .order_by() method instead.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
         # Check hybrid search first as it supports empty query pattern
         if query_type == "hybrid":
             # hybrid fts and vector query
@@ -671,6 +694,7 @@ class LanceQueryBuilder(ABC):
         self._text = None
         self._ef = None
         self._bypass_vector_index = None
+        self._order_by = None
 
     @deprecation.deprecated(
         deprecated_in="0.3.1",
@@ -947,6 +971,24 @@ class LanceQueryBuilder(ABC):
         """  # noqa: E501
         return self._table._explain_plan(self.to_query_object(), verbose=verbose)
 
+    def order_by(self, ordering: Optional[List[ColumnOrdering]]) -> Self:
+        """
+        Set the ordering for the results.
+
+        Parameters
+        ----------
+        ordering: Optional[List[ColumnOrdering]]
+            The ordering to use for the results.  If None, then the default ordering
+            will be used.
+
+        Returns
+        -------
+        LanceQueryBuilder
+            The LanceQueryBuilder object.
+        """
+        self._order_by = ordering
+        return self
+
     def analyze_plan(self) -> str:
         """
         Run the query and return its execution plan with runtime metrics.
@@ -1314,6 +1356,7 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
             fast_search=self._fast_search,
             ef=self._ef,
             bypass_vector_index=self._bypass_vector_index,
+            order_by=self._order_by,
         )
 
     def to_batches(
@@ -1465,7 +1508,9 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
         super().__init__(table)
         self._query = query
         self._phrase_query = False
-        self.ordering_field_name = ordering_field_name
+        # Deprecated compatibility parameter. Native FTS ordering is now
+        # configured through order_by(); LanceQueryBuilder.create emits the warning.
+        _ = ordering_field_name
         self._reranker = None
         self._fast_search = fast_search
         if isinstance(fts_columns, str):
@@ -1514,6 +1559,7 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
             ),
             offset=self._offset,
             fast_search=self._fast_search,
+            order_by=self._order_by,
         )
 
     def output_schema(self) -> pa.Schema:
@@ -1579,6 +1625,7 @@ class LanceEmptyQueryBuilder(LanceQueryBuilder):
             limit=self._limit,
             with_row_id=self._with_row_id,
             offset=self._offset,
+            order_by=self._order_by,
         )
 
     def output_schema(self) -> pa.Schema:
@@ -2502,6 +2549,27 @@ class AsyncStandardQuery(AsyncQueryBase):
         self._inner.offset(offset)
         return self
 
+    def order_by(self, ordering: Optional[List[ColumnOrdering]]) -> Self:
+        """
+        Set the ordering for the results.
+
+        Parameters
+        ----------
+        ordering: Optional[List[ColumnOrdering]]
+            The ordering to use for the results.  If None, then the default ordering
+            will be used.
+        """
+        if ordering is None:
+            self._inner.order_by(None)
+        else:
+            self._inner.order_by(
+                [
+                    o.model_dump() if hasattr(o, "model_dump") else o.dict()
+                    for o in ordering
+                ]
+            )
+        return self
+
     def fast_search(self) -> Self:
         """
         Skip searching un-indexed data.

python/python/lancedb/table.py

@@ -4512,6 +4512,8 @@ class AsyncTable:
             async_query = async_query.fast_search()
         if query.with_row_id:
             async_query = async_query.with_row_id()
+        if query.order_by:
+            async_query = async_query.order_by(query.order_by)
 
         if query.vector:
             async_query = async_query.nearest_to(query.vector).distance_range(

python/python/tests/test_fts.py

@@ -29,6 +29,7 @@ from lancedb.query import (
     MultiMatchQuery,
     PhraseQuery,
     BooleanQuery,
+    ColumnOrdering,
     Occur,
     LanceFtsQueryBuilder,
 )
@@ -499,6 +500,36 @@ async def test_search_fts_specify_column_async(async_table):
         pass
 
 
+def test_search_order_by_descending(table):
+    table.create_fts_index("text")
+    rows = (
+        table.search("puppy")
+        .order_by([ColumnOrdering(column_name="count", ascending=False)])
+        .limit(20)
+        .select(["text", "count"])
+        .to_list()
+    )
+
+    for r in rows:
+        assert "puppy" in r["text"]
+    assert sorted(rows, key=lambda x: x["count"], reverse=True) == rows
+
+
+def test_search_order_by_ascending(table):
+    table.create_fts_index("text")
+    rows = (
+        table.search("puppy")
+        .order_by([ColumnOrdering(column_name="count", ascending=True)])
+        .limit(20)
+        .select(["text", "count"])
+        .to_list()
+    )
+
+    for r in rows:
+        assert "puppy" in r["text"]
+    assert sorted(rows, key=lambda x: x["count"]) == rows
+
+
 def test_create_index_from_table(tmp_path, table):
     table.create_fts_index("text")
     df = table.search("puppy").limit(5).select(["text"]).to_pandas()

python/python/tests/test_query.py

@@ -25,6 +25,7 @@ from lancedb.query import (
     AsyncHybridQuery,
     AsyncQueryBase,
     AsyncVectorQuery,
+    ColumnOrdering,
     LanceVectorQueryBuilder,
     MatchQuery,
     PhraseQuery,
@@ -164,6 +165,71 @@ def test_offset(table):
     assert len(results_with_offset.to_pandas()) == 1
 
 
+def test_order_by_plain_query(mem_db):
+    table = mem_db.create_table(
+        "test_order_by",
+        pa.table(
+            {
+                "group": [1, 1, 1, 2],
+                "score": [None, 1.0, 1.0, 0.5],
+                "name": ["z", "b", "a", "c"],
+            }
+        ),
+    )
+
+    res = (
+        table.search()
+        .order_by(
+            [
+                ColumnOrdering(column_name="group", ascending=True, nulls_first=False),
+                ColumnOrdering(column_name="score", ascending=True, nulls_first=True),
+                ColumnOrdering(column_name="name", ascending=True, nulls_first=False),
+            ]
+        )
+        .to_arrow()
+    )
+
+    assert res.select(["group", "score", "name"]).to_pylist() == [
+        {"group": 1, "score": None, "name": "z"},
+        {"group": 1, "score": 1.0, "name": "a"},
+        {"group": 1, "score": 1.0, "name": "b"},
+        {"group": 2, "score": 0.5, "name": "c"},
+    ]
+
+
+@pytest.mark.asyncio
+async def test_order_by_async_query(mem_db_async: AsyncConnection):
+    table = await mem_db_async.create_table(
+        "test_order_by_async",
+        pa.table(
+            {
+                "group": [1, 1, 1, 2],
+                "score": [None, 1.0, 1.0, 0.5],
+                "name": ["z", "b", "a", "c"],
+            }
+        ),
+    )
+
+    res = await (
+        table.query()
+        .order_by(
+            [
+                ColumnOrdering(column_name="group", ascending=True, nulls_first=False),
+                ColumnOrdering(column_name="score", ascending=True, nulls_first=True),
+                ColumnOrdering(column_name="name", ascending=True, nulls_first=False),
+            ]
+        )
+        .to_arrow()
+    )
+
+    assert res.select(["group", "score", "name"]).to_pylist() == [
+        {"group": 1, "score": None, "name": "z"},
+        {"group": 1, "score": 1.0, "name": "a"},
+        {"group": 1, "score": 1.0, "name": "b"},
+        {"group": 2, "score": 0.5, "name": "c"},
+    ]
+
+
 def test_query_builder(table):
     rs = (
         LanceVectorQueryBuilder(table, [0, 0], "vector")

python/python/tests/test_remote_db.py

@@ -16,6 +16,7 @@ from packaging.version import Version
 
 import lancedb
 from lancedb.conftest import MockTextEmbeddingFunction
+from lancedb.query import ColumnOrdering
 from lancedb.remote import ClientConfig
 from lancedb.remote.errors import HttpError, RetryError
 import pytest
@@ -660,6 +661,18 @@ def test_query_sync_maximal():
             "ef": None,
             "filter": "id > 0",
             "columns": ["id", "name"],
+            "order_by": [
+                {
+                    "column_name": "score",
+                    "ascending": False,
+                    "nulls_first": True,
+                },
+                {
+                    "column_name": "id",
+                    "ascending": True,
+                    "nulls_first": False,
+                },
+            ],
             "vector_column": "vector2",
             "fast_search": True,
             "with_row_id": True,
@@ -677,6 +690,14 @@ def test_query_sync_maximal():
             .refine_factor(10)
             .nprobes(5)
             .where("id > 0", prefilter=True)
+            .order_by(
+                [
+                    ColumnOrdering(
+                        column_name="score", ascending=False, nulls_first=True
+                    ),
+                    ColumnOrdering(column_name="id", ascending=True, nulls_first=False),
+                ]
+            )
             .with_row_id(True)
             .select(["id", "name"])
             .to_list()

python/src/query.rs

@@ -23,7 +23,7 @@ use lancedb::query::QueryBase;
 use lancedb::query::QueryExecutionOptions;
 use lancedb::query::QueryFilter;
 use lancedb::query::{
-    ExecutableQuery, Query as LanceDbQuery, Select, TakeQuery as LanceDbTakeQuery,
+    ColumnOrdering, ExecutableQuery, Query as LanceDbQuery, Select, TakeQuery as LanceDbTakeQuery,
     VectorQuery as LanceDbVectorQuery,
 };
 use lancedb::table::AnyQuery;
@@ -207,6 +207,48 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
 #[derive(Clone)]
 pub struct PyQueryVectors(Vec<Arc<dyn Array>>);
 
+#[derive(Clone, FromPyObject)]
+#[pyo3(from_item_all)]
+pub struct PyColumnOrdering {
+    pub column_name: String,
+    pub ascending: bool,
+    pub nulls_first: bool,
+}
+
+impl From<ColumnOrdering> for PyColumnOrdering {
+    fn from(ordering: ColumnOrdering) -> Self {
+        Self {
+            column_name: ordering.column_name,
+            ascending: ordering.ascending,
+            nulls_first: ordering.nulls_first,
+        }
+    }
+}
+
+impl From<PyColumnOrdering> for ColumnOrdering {
+    fn from(ordering: PyColumnOrdering) -> Self {
+        Self {
+            column_name: ordering.column_name,
+            ascending: ordering.ascending,
+            nulls_first: ordering.nulls_first,
+        }
+    }
+}
+
+impl<'py> IntoPyObject<'py> for PyColumnOrdering {
+    type Target = PyDict;
+    type Output = Bound<'py, Self::Target>;
+    type Error = PyErr;
+
+    fn into_pyobject(self, py: pyo3::Python<'py>) -> PyResult<Self::Output> {
+        let dict = PyDict::new(py);
+        dict.set_item("column_name", self.column_name)?;
+        dict.set_item("ascending", self.ascending)?;
+        dict.set_item("nulls_first", self.nulls_first)?;
+        Ok(dict)
+    }
+}
+
 impl<'py> IntoPyObject<'py> for PyQueryVectors {
     type Target = PyList;
     type Output = Bound<'py, Self::Target>;
@@ -246,6 +288,7 @@ pub struct PyQueryRequest {
     pub bypass_vector_index: Option<bool>,
     pub postfilter: Option<bool>,
     pub norm: Option<String>,
+    pub order_by: Option<Vec<PyColumnOrdering>>,
 }
 
 impl From<AnyQuery> for PyQueryRequest {
@@ -273,6 +316,9 @@ impl From<AnyQuery> for PyQueryRequest {
                 bypass_vector_index: None,
                 postfilter: None,
                 norm: None,
+                order_by: query_request
+                    .order_by
+                    .map(|order_by| order_by.into_iter().map(PyColumnOrdering::from).collect()),
             },
             AnyQuery::VectorQuery(vector_query) => Self {
                 limit: vector_query.base.limit,
@@ -297,6 +343,10 @@ impl From<AnyQuery> for PyQueryRequest {
                 bypass_vector_index: Some(!vector_query.use_index),
                 postfilter: Some(!vector_query.base.prefilter),
                 norm: vector_query.base.norm.map(|n| n.to_string()),
+                order_by: vector_query
+                    .base
+                    .order_by
+                    .map(|order_by| order_by.into_iter().map(PyColumnOrdering::from).collect()),
             },
         }
     }
@@ -475,6 +525,13 @@ impl Query {
         })
     }
 
+    pub fn order_by(&mut self, ordering: Option<Vec<PyColumnOrdering>>) -> PyResult<()> {
+        let ordering =
+            ordering.map(|ordering| ordering.into_iter().map(ColumnOrdering::from).collect());
+        self.inner = self.inner.clone().order_by(ordering);
+        Ok(())
+    }
+
     #[pyo3(signature = ())]
     pub fn output_schema(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
         let inner = self_.inner.clone();
@@ -647,6 +704,13 @@ impl FTSQuery {
         self.inner = self.inner.clone().offset(offset as usize);
     }
 
+    pub fn order_by(&mut self, ordering: Option<Vec<PyColumnOrdering>>) -> PyResult<()> {
+        let ordering =
+            ordering.map(|ordering| ordering.into_iter().map(ColumnOrdering::from).collect());
+        self.inner = self.inner.clone().order_by(ordering);
+        Ok(())
+    }
+
     pub fn fast_search(&mut self) {
         self.inner = self.inner.clone().fast_search();
     }
@@ -782,6 +846,13 @@ impl VectorQuery {
         self.inner = self.inner.clone().offset(offset as usize);
     }
 
+    pub fn order_by(&mut self, ordering: Option<Vec<PyColumnOrdering>>) -> PyResult<()> {
+        let ordering =
+            ordering.map(|ordering| ordering.into_iter().map(ColumnOrdering::from).collect());
+        self.inner = self.inner.clone().order_by(ordering);
+        Ok(())
+    }
+
     pub fn fast_search(&mut self) {
         self.inner = self.inner.clone().fast_search();
     }
@@ -954,6 +1025,12 @@ impl HybridQuery {
         self.inner_fts.offset(offset);
     }
 
+    pub fn order_by(&mut self, ordering: Option<Vec<PyColumnOrdering>>) -> PyResult<()> {
+        self.inner_vec.order_by(ordering.clone())?;
+        self.inner_fts.order_by(ordering)?;
+        Ok(())
+    }
+
     pub fn fast_search(&mut self) {
         self.inner_vec.fast_search();
         self.inner_fts.fast_search();

rust/lancedb/src/query.rs

@@ -11,6 +11,8 @@ use datafusion_expr::Expr;
 use datafusion_physical_plan::ExecutionPlan;
 use futures::{FutureExt, TryFutureExt, TryStreamExt, stream, try_join};
 use half::f16;
+/// Re-export Lance ColumnOrdering type for use in query ordering
+pub use lance::dataset::scanner::ColumnOrdering;
 use lance::dataset::{ROW_ID, scanner::DatasetRecordBatchStream};
 use lance_arrow::RecordBatchExt;
 use lance_datafusion::exec::execute_plan;
@@ -510,6 +512,11 @@ pub trait QueryBase {
     /// the scores are converted to ranks and then normalized. If "Score", the
     /// scores are normalized directly.
     fn norm(self, norm: NormalizeMethod) -> Self;
+
+    /// Sort the results by the specified column(s).
+    ///
+    /// This allows ordering query results by one or more columns in either ascending or descending order.
+    fn order_by(self, ordering: Option<Vec<ColumnOrdering>>) -> Self;
 }
 
 pub trait HasQuery {
@@ -574,6 +581,11 @@ impl<T: HasQuery> QueryBase for T {
         self.mut_query().norm = Some(norm);
         self
     }
+
+    fn order_by(mut self, ordering: Option<Vec<ColumnOrdering>>) -> Self {
+        self.mut_query().order_by = ordering;
+        self
+    }
 }
 
 /// Options for controlling the execution of a query
@@ -750,6 +762,11 @@ pub struct QueryRequest {
     ///
     /// By default, this is false (scoring columns are auto-projected for backward compatibility).
     pub disable_scoring_autoprojection: bool,
+
+    /// Sort the results by the specified column(s).
+    ///
+    /// This allows ordering query results by one or more columns in either ascending or descending order.
+    pub order_by: Option<Vec<ColumnOrdering>>,
 }
 
 impl Default for QueryRequest {
@@ -766,6 +783,7 @@ impl Default for QueryRequest {
             reranker: None,
             norm: None,
             disable_scoring_autoprojection: false,
+            order_by: None,
         }
     }
 }

rust/lancedb/src/remote/table.rs

@@ -518,6 +518,21 @@ impl<S: HttpSend> RemoteTable<S> {
             }
         }
 
+        if let Some(order_by) = &params.order_by {
+            body["order_by"] = serde_json::Value::Array(
+                order_by
+                    .iter()
+                    .map(|o| {
+                        serde_json::json!({
+                            "column_name": o.column_name,
+                            "ascending": o.ascending,
+                            "nulls_first": o.nulls_first,
+                        })
+                    })
+                    .collect(),
+            );
+        }
+
         Ok(())
     }
 
@@ -2078,7 +2093,7 @@ mod tests {
     use crate::{
         DistanceType, Error, Table,
         index::{Index, IndexStatistics, IndexType, vector::IvfPqIndexBuilder},
-        query::{ExecutableQuery, QueryBase},
+        query::{ColumnOrdering, ExecutableQuery, QueryBase},
         remote::ARROW_FILE_CONTENT_TYPE,
     };
 
@@ -2988,6 +3003,18 @@ mod tests {
                 "distance_type": "cosine",
                 "bypass_vector_index": true,
                 "columns": ["a", "b"],
+                "order_by": [
+                    {
+                        "column_name": "score",
+                        "ascending": false,
+                        "nulls_first": true,
+                    },
+                    {
+                        "column_name": "id",
+                        "ascending": true,
+                        "nulls_first": false,
+                    }
+                ],
                 "nprobes": 12,
                 "minimum_nprobes": 12,
                 "maximum_nprobes": 12,
@@ -3019,6 +3046,10 @@ mod tests {
             .limit(42)
             .offset(10)
             .select(Select::columns(&["a", "b"]))
+            .order_by(Some(vec![
+                ColumnOrdering::desc_nulls_first("score".to_string()),
+                ColumnOrdering::asc_nulls_last("id".to_string()),
+            ]))
             .nearest_to(vec![0.1, 0.2, 0.3])
             .unwrap()
             .column("my_vector")

rust/lancedb/src/table/query.rs

@@ -242,6 +242,10 @@ pub async fn create_plan(
         scanner.disable_scoring_autoprojection();
     }
 
+    if let Some(order_by) = &query.base.order_by {
+        scanner.order_by(Some(order_by.clone()))?;
+    }
+
     Ok(scanner.create_plan().await?)
 }