$bottom - Amazon DocumentDB
Services or capabilities described in AWS documentation might vary by Region. To see the differences applicable to the AWS European Sovereign Cloud Region, see the AWS European Sovereign Cloud User Guide.

$bottom

New from version 8.0.1.

Use the $bottom accumulator in the $group stage to return the lowest-ranked document per group according to a specified sort order.

Parameters

  • sortBy: A document specifying the sort order. Use 1 for ascending or -1 for descending.

  • output: An expression that specifies the fields to return from the bottom document.

Example (MongoDB Shell)

The following example shows how to use the $bottom accumulator to find the bottom sale (lowest quantity) per item in a sales collection.

Create sample documents

db.sales.insertMany([ { item: "abc", quantity: 10, price: 5 }, { item: "abc", quantity: 5, price: 8 }, { item: "xyz", quantity: 15, price: 3 }, { item: "xyz", quantity: 7, price: 6 } ])

Query example

db.sales.aggregate([ { $group: { _id: "$item", bottomSale: { $bottom: { sortBy: { quantity: -1 }, output: { quantity: "$quantity", price: "$price" } } } } } ])

Output

[ { "_id": "xyz", "bottomSale": { "quantity": 7, "price": 6 } }, { "_id": "abc", "bottomSale": { "quantity": 5, "price": 8 } } ]

Window operator usage example (MongoDB Shell)

New from version 8.0.2.

The $bottom operator can also be used as a window operator in the $setWindowFields stage. In this context, it returns the output from the bottom-ranked document (according to the operator's own sortBy) among the documents in each window. You specify the operator under the output field, and optionally define the window boundaries with a window document.

Note

When used as a window operator in $setWindowFields, $bottom is limited to 100 MB of intermediate data. An operation that exceeds this limit returns an error.

Create sample documents

db.matchScores.insertMany([ { _id: 1, player: "Alice", round: 1, score: 20 }, { _id: 2, player: "Alice", round: 2, score: 35 }, { _id: 3, player: "Alice", round: 3, score: 28 }, { _id: 4, player: "Bob", round: 1, score: 15 }, { _id: 5, player: "Bob", round: 2, score: 40 } ]);

Query example

The following example partitions the documents by player, sorts each partition by round, and returns the lowest-scoring round seen from the start of the partition through the current document.

db.matchScores.aggregate([ { $setWindowFields: { partitionBy: "$player", sortBy: { round: 1 }, output: { worstRoundSoFar: { $bottom: { sortBy: { score: -1 }, output: { round: "$round", score: "$score" } }, window: { documents: ["unbounded", "current"] } } } } } ]);

Output

[ { "_id": 1, "player": "Alice", "round": 1, "score": 20, "worstRoundSoFar": { "round": 1, "score": 20 } }, { "_id": 2, "player": "Alice", "round": 2, "score": 35, "worstRoundSoFar": { "round": 1, "score": 20 } }, { "_id": 3, "player": "Alice", "round": 3, "score": 28, "worstRoundSoFar": { "round": 1, "score": 20 } }, { "_id": 4, "player": "Bob", "round": 1, "score": 15, "worstRoundSoFar": { "round": 1, "score": 15 } }, { "_id": 5, "player": "Bob", "round": 2, "score": 40, "worstRoundSoFar": { "round": 1, "score": 15 } } ]

Each document is augmented with worstRoundSoFar, the lowest-scoring round within its partition up to and including the current document.

Code examples

To view a code example for using the $bottom operator, choose the tab for the language that you want to use. The following examples show both accumulator usage (in $group) and window operator usage (in $setWindowFields):

Node.js
const { MongoClient } = require('mongodb'); async function example() { const uri = 'mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false'; const client = new MongoClient(uri); try { await client.connect(); const db = client.db('test'); // Accumulator usage: bottom document per group const sales = db.collection('sales'); await sales.insertMany([ { item: "abc", quantity: 10, price: 5 }, { item: "abc", quantity: 5, price: 8 }, { item: "xyz", quantity: 15, price: 3 }, { item: "xyz", quantity: 7, price: 6 } ]); const accumulatorResult = await sales.aggregate([ { $group: { _id: "$item", bottomSale: { $bottom: { sortBy: { quantity: -1 }, output: { quantity: "$quantity", price: "$price" } } } } } ]).toArray(); console.log('Accumulator result:', accumulatorResult); // Window operator usage: worst round so far within each partition const matchScores = db.collection('matchScores'); await matchScores.insertMany([ { _id: 1, player: "Alice", round: 1, score: 20 }, { _id: 2, player: "Alice", round: 2, score: 35 }, { _id: 3, player: "Alice", round: 3, score: 28 }, { _id: 4, player: "Bob", round: 1, score: 15 }, { _id: 5, player: "Bob", round: 2, score: 40 } ]); const windowResult = await matchScores.aggregate([ { $setWindowFields: { partitionBy: "$player", sortBy: { round: 1 }, output: { worstRoundSoFar: { $bottom: { sortBy: { score: -1 }, output: { round: "$round", score: "$score" } }, window: { documents: ["unbounded", "current"] } } } } } ]).toArray(); console.log('Window result:', windowResult); } catch (error) { console.error('Error:', error); } finally { await client.close(); } } example();
Python
from pymongo import MongoClient from pprint import pprint def example(): client = None try: client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false') db = client['test'] # Accumulator usage: bottom document per group sales = db['sales'] sales.insert_many([ { 'item': 'abc', 'quantity': 10, 'price': 5 }, { 'item': 'abc', 'quantity': 5, 'price': 8 }, { 'item': 'xyz', 'quantity': 15, 'price': 3 }, { 'item': 'xyz', 'quantity': 7, 'price': 6 } ]) accumulator_result = list(sales.aggregate([ { '$group': { '_id': '$item', 'bottomSale': { '$bottom': { 'sortBy': { 'quantity': -1 }, 'output': { 'quantity': '$quantity', 'price': '$price' } } } } } ])) pprint(accumulator_result) # Window operator usage: worst round so far within each partition match_scores = db['matchScores'] match_scores.insert_many([ { '_id': 1, 'player': 'Alice', 'round': 1, 'score': 20 }, { '_id': 2, 'player': 'Alice', 'round': 2, 'score': 35 }, { '_id': 3, 'player': 'Alice', 'round': 3, 'score': 28 }, { '_id': 4, 'player': 'Bob', 'round': 1, 'score': 15 }, { '_id': 5, 'player': 'Bob', 'round': 2, 'score': 40 } ]) window_result = list(match_scores.aggregate([ { '$setWindowFields': { 'partitionBy': '$player', 'sortBy': { 'round': 1 }, 'output': { 'worstRoundSoFar': { '$bottom': { 'sortBy': { 'score': -1 }, 'output': { 'round': '$round', 'score': '$score' } }, 'window': { 'documents': ['unbounded', 'current'] } } } } } ])) pprint(window_result) except Exception as e: print(f"An error occurred: {e}") finally: if client: client.close() example()