feat(nodejs): support field/data type input in add_columns() method (#3114)

Add support for passing field/data type information into add_columns()
method, bringing parity with Python bindings. The method now accepts:

- AddColumnsSql[] - SQL expressions (existing functionality)
- Field - single Arrow field with explicit data type
- Field[] - array of Arrow fields with explicit data types
- Schema - Arrow schema with explicit data types

New columns added via Field/Schema are initialized with null values. All
field-based columns must be nullable due to null initialization.

Resolves #3107

---------

Signed-off-by: Pratik <pratikrocks.dey11@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>

docs/src/js/classes/Table.md

@@ -71,11 +71,12 @@ Add new columns with defined values.
 
 #### Parameters
 
-* **newColumnTransforms**: [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
-    pairs of column names and
-    the SQL expression to use to calculate the value of the new column. These
-    expressions will be evaluated for each row in the table, and can
-    reference existing columns in the table.
+* **newColumnTransforms**: `Field`<`any`> \| `Field`<`any`>[] \| `Schema`<`any`> \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
+    Either:
+    - An array of objects with column names and SQL expressions to calculate values
+    - A single Arrow Field defining one column with its data type (column will be initialized with null values)
+    - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
+    - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
 
 #### Returns
 

nodejs/__test__/table.test.ts

@@ -1259,6 +1259,98 @@ describe("schema evolution", function () {
     expect(await table.schema()).toEqual(expectedSchema);
   });
 
+  it("can add columns with schema for explicit data types", async function () {
+    const con = await connect(tmpDir.name);
+    const table = await con.createTable("vectors", [
+      { id: 1n, vector: [0.1, 0.2] },
+    ]);
+
+    // Define schema for new columns with explicit data types
+    // Note: All columns must be nullable when using addColumns with Schema
+    // because they are initially populated with null values
+    const newColumnsSchema = new Schema([
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+      new Field("rating", new Int32(), true),
+    ]);
+
+    const result = await table.addColumns(newColumnsSchema);
+    expect(result).toHaveProperty("version");
+    expect(result.version).toBe(2);
+
+    const expectedSchema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "vector",
+        new FixedSizeList(2, new Field("item", new Float32(), true)),
+        true,
+      ),
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+      new Field("rating", new Int32(), true),
+    ]);
+    expect(await table.schema()).toEqual(expectedSchema);
+
+    // Verify that new columns are populated with null values
+    const results = await table.query().toArray();
+    expect(results).toHaveLength(1);
+    expect(results[0].price).toBeNull();
+    expect(results[0].category).toBeNull();
+    expect(results[0].rating).toBeNull();
+  });
+
+  it("can add a single column using Field", async function () {
+    const con = await connect(tmpDir.name);
+    const table = await con.createTable("vectors", [
+      { id: 1n, vector: [0.1, 0.2] },
+    ]);
+
+    // Add a single field
+    const priceField = new Field("price", new Float64(), true);
+    const result = await table.addColumns(priceField);
+    expect(result).toHaveProperty("version");
+    expect(result.version).toBe(2);
+
+    const expectedSchema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "vector",
+        new FixedSizeList(2, new Field("item", new Float32(), true)),
+        true,
+      ),
+      new Field("price", new Float64(), true),
+    ]);
+    expect(await table.schema()).toEqual(expectedSchema);
+  });
+
+  it("can add multiple columns using array of Fields", async function () {
+    const con = await connect(tmpDir.name);
+    const table = await con.createTable("vectors", [
+      { id: 1n, vector: [0.1, 0.2] },
+    ]);
+
+    // Add multiple fields as array
+    const fields = [
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+    ];
+    const result = await table.addColumns(fields);
+    expect(result).toHaveProperty("version");
+    expect(result.version).toBe(2);
+
+    const expectedSchema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "vector",
+        new FixedSizeList(2, new Field("item", new Float32(), true)),
+        true,
+      ),
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+    ]);
+    expect(await table.schema()).toEqual(expectedSchema);
+  });
+
   it("can alter the columns in the schema", async function () {
     const con = await connect(tmpDir.name);
     const schema = new Schema([

nodejs/lancedb/table.ts

@@ -5,12 +5,15 @@ import {
   Table as ArrowTable,
   Data,
   DataType,
+  Field,
   IntoVector,
   MultiVector,
   Schema,
   dataTypeToJson,
   fromDataToBuffer,
+  fromTableToBuffer,
   isMultiVector,
+  makeEmptyTable,
   tableFromIPC,
 } from "./arrow";
 
@@ -391,15 +394,16 @@ export abstract class Table {
   abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
   /**
    * Add new columns with defined values.
-   * @param {AddColumnsSql[]} newColumnTransforms pairs of column names and
-   * the SQL expression to use to calculate the value of the new column. These
-   * expressions will be evaluated for each row in the table, and can
-   * reference existing columns in the table.
+   * @param {AddColumnsSql[] | Field | Field[] | Schema} newColumnTransforms Either:
+   *   - An array of objects with column names and SQL expressions to calculate values
+   *   - A single Arrow Field defining one column with its data type (column will be initialized with null values)
+   *   - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
+   *   - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
    * @returns {Promise<AddColumnsResult>} A promise that resolves to an object
    * containing the new version number of the table after adding the columns.
    */
   abstract addColumns(
-    newColumnTransforms: AddColumnsSql[],
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
   ): Promise<AddColumnsResult>;
 
   /**
@@ -804,9 +808,40 @@ export class LocalTable extends Table {
   // TODO: Support BatchUDF
 
   async addColumns(
-    newColumnTransforms: AddColumnsSql[],
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
   ): Promise<AddColumnsResult> {
-    return await this.inner.addColumns(newColumnTransforms);
+    // Handle single Field -> convert to array of Fields
+    if (newColumnTransforms instanceof Field) {
+      newColumnTransforms = [newColumnTransforms];
+    }
+
+    // Handle array of Fields -> convert to Schema
+    if (
+      Array.isArray(newColumnTransforms) &&
+      newColumnTransforms.length > 0 &&
+      newColumnTransforms[0] instanceof Field
+    ) {
+      const fields = newColumnTransforms as Field[];
+      newColumnTransforms = new Schema(fields);
+    }
+
+    // Handle Schema -> use schema-based approach
+    if (newColumnTransforms instanceof Schema) {
+      const schema = newColumnTransforms;
+      // Convert schema to buffer using Arrow IPC format
+      const emptyTable = makeEmptyTable(schema);
+      const schemaBuf = await fromTableToBuffer(emptyTable);
+      return await this.inner.addColumnsWithSchema(schemaBuf);
+    }
+
+    // Handle SQL expressions (existing functionality)
+    if (Array.isArray(newColumnTransforms)) {
+      return await this.inner.addColumns(
+        newColumnTransforms as AddColumnsSql[],
+      );
+    }
+
+    throw new Error("Invalid input type for addColumns");
   }
 
   async alterColumns(

nodejs/src/table.rs

@@ -3,7 +3,7 @@
 
 use std::collections::HashMap;
 
-use lancedb::ipc::ipc_file_to_batches;
+use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};
 use lancedb::table::{
     AddDataMode, ColumnAlteration as LanceColumnAlteration, Duration, NewColumnTransform,
     OptimizeAction, OptimizeOptions, Table as LanceDbTable,
@@ -279,6 +279,23 @@ impl Table {
         Ok(res.into())
     }
 
+    #[napi(catch_unwind)]
+    pub async fn add_columns_with_schema(
+        &self,
+        schema_buf: Buffer,
+    ) -> napi::Result<AddColumnsResult> {
+        let schema = ipc_file_to_schema(schema_buf.to_vec())
+            .map_err(|e| napi::Error::from_reason(format!("Failed to read IPC schema: {}", e)))?;
+
+        let transforms = NewColumnTransform::AllNulls(schema);
+        let res = self
+            .inner_ref()?
+            .add_columns(transforms, None)
+            .await
+            .default_error()?;
+        Ok(res.into())
+    }
+
     #[napi(catch_unwind)]
     pub async fn alter_columns(
         &self,