Aggregate

Import restaurants collection

wget https://www.dropbox.com/s/iovpcb7hc3gc4n4/primer-dataset.json

mongoimport --uri "mongodb+srv://admatic:admatic123@admatic-cluster-7qyyr.mongodb.net/admatic-db" \
    --collection restaurants --drop --file primer-dataset.json

2019-02-25T17:56:09.864+0000    connected to: localhost
2019-02-25T17:56:09.979+0000    dropping: admatic-db.restaurants
2019-02-25T17:56:12.489+0000    [#######################.] admatic-db.restaurants       11.2MB/11.3MB (99.4%)
2019-02-25T17:56:12.573+0000    [########################] admatic-db.restaurants       11.3MB/11.3MB (100.0%)
2019-02-25T17:56:12.574+0000    imported 25359 documents

Code

mkdir -p src/main/java/com/admatic/primer

vim src/main/java/com/admatic/primer/AggregatePrimer.java

package com.admatic.primer;

import com.mongodb.Block;
import com.mongodb.client.AggregateIterable;
import com.mongodb.client.MongoClient;
import com.mongodb.client.MongoClients;
import com.mongodb.client.MongoDatabase;
import org.bson.Document;

import java.util.logging.Level;
import java.util.logging.Logger;

import static java.util.Arrays.asList;

public class AggregatePrimer {

    private static void groupDocumentsByAFieldAndCalculateCount(MongoDatabase db) {
        AggregateIterable<Document> iterable = db.getCollection("restaurants").aggregate(asList(
                new Document("$group", new Document("_id", "$borough").append("count", new Document("$sum", 1)))));

        iterable.forEach(new Block<Document>() {
            @Override
            public void apply(final Document document) {
                System.out.println(document.toJson());
            }
        });
    }

    private static void filterAndGroupDocuments(MongoDatabase db) {
        AggregateIterable<Document> iterable = db.getCollection("restaurants").aggregate(asList(
                new Document("$match", new Document("borough", "Queens").append("cuisine", "Brazilian")),
                new Document("$group", new Document("_id", "$address.zipcode").append("count", new Document("$sum", 1)))));

        iterable.forEach(new Block<Document>() {
            @Override
            public void apply(final Document document) {
                System.out.println(document.toJson());
            }
        });
    }

    public static void main(final String[] args) {
        Logger mongoLogger = Logger.getLogger("org.mongodb.driver");
        mongoLogger.setLevel(Level.SEVERE);

        MongoClient mongoClient;

        if (args.length == 0) {
            mongoClient = MongoClients.create();
        } else {
            mongoClient = MongoClients.create(args[0]);
        }

        MongoDatabase database = mongoClient.getDatabase("admatic-db");

        switch (args[1]) {
            case "0":
                System.out.println("groupDocumentsByAFieldAndCalculateCount");
                groupDocumentsByAFieldAndCalculateCount(database);
                break;
            case "1":
                System.out.println("filterAndGroupDocuments");
                filterAndGroupDocuments(database);
                break;

            default:
                System.out.println("Enter an option between 0 and 1");
        }

        mongoClient.close();
    }
}

Compile

mvn compile

Run

Group Documents By A Field And Calculate Count

db.getCollection("restaurants").aggregate(asList(
                new Document("$group", new Document("_id", "$borough").append("count", new Document("$sum", 1))))

mvn exec:java -Dexec.mainClass=com.admatic.primer.AggregatePrimer \
    -Dexec.args="mongodb+srv://admatic:admatic123@admatic-cluster-7qyyr.mongodb.net/test 0"

groupDocumentsByAFieldAndCalculateCount
{"_id": "Missing", "count": 51}
{"_id": "Manhattan", "count": 10259}
{"_id": "Staten Island", "count": 969}
{"_id": "Bronx", "count": 2338}
{"_id": "Queens", "count": 5656}
{"_id": "Brooklyn", "count": 6086}

Filter And Group Documents

db.getCollection("restaurants").aggregate(asList(
                new Document("$match", new Document("borough", "Queens").append("cuisine", "Brazilian")),
                new Document("$group", new Document("_id", "$address.zipcode").append("count", new Document("$sum", 1))))

mvn exec:java -Dexec.mainClass=com.admatic.primer.AggregatePrimer \
    -Dexec.args="mongodb+srv://admatic:admatic123@admatic-cluster-7qyyr.mongodb.net/test 1"

filterAndGroupDocuments
{"_id": "11377", "count": 1}
{"_id": "11103", "count": 1}
{"_id": "11106", "count": 3}
{"_id": "11368", "count": 1}
{"_id": "11101", "count": 2}