perf(NODE-5906): optimize toArray to use batches

src/cursor/abstract_cursor.ts

@@ -296,8 +296,8 @@ export abstract class AbstractCursor<
   }
 
   /** Returns current buffered documents */
-  readBufferedDocuments(number?: number): TSchema[] {
-    const bufferedDocs: TSchema[] = [];
+  readBufferedDocuments(number?: number): NonNullable<TSchema>[] {
+    const bufferedDocs: NonNullable<TSchema>[] = [];
     const documentsToRead = Math.min(
       number ?? this.documents?.length ?? 0,
       this.documents?.length ?? 0
@@ -312,6 +312,7 @@ export abstract class AbstractCursor<
 
     return bufferedDocs;
   }
+
   async *[Symbol.asyncIterator](): AsyncGenerator<TSchema, void, void> {
     if (this.isClosed) {
       return;
@@ -475,13 +476,22 @@ export abstract class AbstractCursor<
    * cursor.rewind() can be used to reset the cursor.
    */
   async toArray(): Promise<TSchema[]> {
-    const array = [];
+    const array: TSchema[] = [];
+    // at the end of the loop (since readBufferedDocuments is called) the buffer will be empty
+    // then, the 'await of' syntax will run a getMore call
     for await (const document of this) {
       array.push(document);
+      const docs = this.readBufferedDocuments();
+      if (this.transform != null) {
+        for (const doc of docs) {
+          array.push(await this.transformDocument(doc));
+        }
+      } else {
+        array.push(...docs);
+      }
     }
     return array;
   }
-
   /**
    * Add a cursor flag to the cursor
    *
@@ -822,7 +832,7 @@ export abstract class AbstractCursor<
   }
 
   /** @internal */
-  private async transformDocument(document: NonNullable<TSchema>): Promise<TSchema> {
+  private async transformDocument(document: NonNullable<TSchema>): Promise<NonNullable<TSchema>> {
     if (this.transform == null) return document;
 
     try {

test/benchmarks/mongoBench/suites/multiBench.js

@@ -155,6 +155,67 @@ function makeMultiBench(suite) {
         })
         .teardown(dropDb)
         .teardown(disconnectClient)
+    )
+    .benchmark('aggregateAMillionDocumentsAndToArray', benchmark =>
+      benchmark
+        .taskSize(16)
+        .setup(makeClient)
+        .setup(connectClient)
+        .setup(initDb)
+        .setup(dropDb)
+        .task(async function () {
+          await this.db
+            .aggregate([
+              { $documents: [{}] },
+              {
+                $set: {
+                  field: {
+                    $reduce: {
+                      input: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
+                      initialValue: [0],
+                      in: { $concatArrays: ['$$value', '$$value'] }
+                    }
+                  }
+                }
+              },
+              { $unwind: '$field' },
+              { $limit: 1000000 }
+            ])
+            .toArray();
+        })
+        .teardown(dropDb)
+        .teardown(disconnectClient)
+    )
+    .benchmark('aggregateAMillionTweetsAndToArray', benchmark =>
+      benchmark
+        .taskSize(1500)
+        .setup(makeLoadJSON('tweet.json'))
+        .setup(makeClient)
+        .setup(connectClient)
+        .setup(initDb)
+        .setup(dropDb)
+        .task(async function () {
+          await this.db
+            .aggregate([
+              { $documents: [this.doc] },
+              {
+                $set: {
+                  id: {
+                    $reduce: {
+                      input: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
+                      initialValue: [0],
+                      in: { $concatArrays: ['$$value', '$$value'] }
+                    }
+                  }
+                }
+              },
+              { $unwind: '$id' },
+              { $limit: 1000000 }
+            ])
+            .toArray();
+        })
+        .teardown(dropDb)
+        .teardown(disconnectClient)
     );
 }
 

test/integration/node-specific/abstract_cursor.test.ts

@@ -5,6 +5,7 @@ import { Transform } from 'stream';
 import { inspect } from 'util';
 
 import {
+  AbstractCursor,
   type Collection,
   type FindCursor,
   MongoAPIError,
@@ -361,4 +362,37 @@ describe('class AbstractCursor', function () {
       });
     });
   });
+
+  describe('toArray', () => {
+    let nextSpy;
+    let client: MongoClient;
+    let cursor: AbstractCursor;
+    let col: Collection;
+    const numBatches = 10;
+    const batchSize = 4;
+
+    beforeEach(async function () {
+      client = this.configuration.newClient();
+      col = client.db().collection('test');
+      await col.deleteMany({});
+      for (let i = 0; i < numBatches; i++) {
+        await col.insertMany([{ a: 1 }, { a: 2 }, { a: 3 }, { a: 4 }]);
+      }
+      nextSpy = sinon.spy(AbstractCursor.prototype, 'next');
+    });
+
+    afterEach(async function () {
+      sinon.restore();
+      await cursor.close();
+      await client.close();
+    });
+
+    it('iterates per batch not per document', async () => {
+      cursor = client.db().collection('test').find({}, { batchSize });
+      await cursor.toArray();
+      expect(nextSpy.callCount).to.equal(numBatches + 1);
+      const numDocuments = numBatches * batchSize;
+      expect(nextSpy.callCount).to.be.lessThan(numDocuments);
+    });
+  });
 });