QuickStart

Code

vim src/main/java/com/admatic/QuickTour.java

package com.admatic;

import com.mongodb.Block;
import com.mongodb.client.*;
import com.mongodb.client.model.*;
import com.mongodb.client.result.DeleteResult;
import com.mongodb.client.result.UpdateResult;
import org.bson.Document;

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

import static com.mongodb.client.model.Accumulators.sum;
import static com.mongodb.client.model.Aggregates.*;
import static com.mongodb.client.model.Filters.*;
import static com.mongodb.client.model.Projections.excludeId;
import static com.mongodb.client.model.Sorts.descending;
import static com.mongodb.client.model.Updates.inc;
import static com.mongodb.client.model.Updates.set;
import static java.util.Arrays.asList;
import static java.util.Collections.singletonList;

public class QuickTour {

    /**
     * Run this main method to see the output of this quick example.
     *
     * @param args takes an optional single argument for the connection string
     */
    public static void main(final String[] args) {
        Logger mongoLogger = Logger.getLogger("org.mongodb.driver");
        mongoLogger.setLevel(Level.SEVERE);

        MongoClient mongoClient;

        if (args.length == 0) {
            // connect to the local database server
            mongoClient = MongoClients.create();
        } else {
            mongoClient = MongoClients.create(args[0]);
        }

        // get handle to "admatic-db" database
        MongoDatabase database = mongoClient.getDatabase("admatic-db");


        // get a handle to the "admatic-collection" collection
        MongoCollection<Document> collection = database.getCollection("admatic-collection");

        // drop all the data in it
        collection.drop();

        // make a document and insert it
        Document doc = new Document("name", "MongoDB")
                .append("type", "database")
                .append("count", 1)
                .append("info", new Document("x", 203).append("y", 102));

        collection.insertOne(doc);

        // get it (since it's the only one in there since we dropped the rest earlier on)
        Document myDoc = collection.find().first();
        System.out.println(myDoc.toJson());

        // now, lets add lots of little documents to the collection so we can explore queries and cursors
        List<Document> documents = new ArrayList<Document>();
        for (int i = 0; i < 100; i++) {
            documents.add(new Document("i", i));
        }
        collection.insertMany(documents);
        System.out.println("total # of documents after inserting 100 small ones (should be 101) " + collection.countDocuments());

        // find first
        myDoc = collection.find().first();
        System.out.println(myDoc.toJson());

        // lets get all the documents in the collection and print them out
        MongoCursor<Document> cursor = collection.find().iterator();
        try {
            while (cursor.hasNext()) {
                System.out.println(cursor.next().toJson());
            }
        } finally {
            cursor.close();
        }

        for (Document cur : collection.find()) {
            System.out.println(cur.toJson());
        }

        // now use a query to get 1 document out
        myDoc = collection.find(eq("i", 71)).first();
        System.out.println(myDoc.toJson());

        // now use a range query to get a larger subset
        cursor = collection.find(gt("i", 50)).iterator();

        try {
            while (cursor.hasNext()) {
                System.out.println(cursor.next().toJson());
            }
        } finally {
            cursor.close();
        }

        // range query with multiple constraints
        cursor = collection.find(and(gt("i", 50), lte("i", 100))).iterator();

        try {
            while (cursor.hasNext()) {
                System.out.println(cursor.next().toJson());
            }
        } finally {
            cursor.close();
        }

        // Query Filters
        myDoc = collection.find(eq("i", 71)).first();
        System.out.println(myDoc.toJson());

        // now use a range query to get a larger subset
        Block<Document> printBlock = new Block<Document>() {
            @Override
            public void apply(final Document document) {
                System.out.println(document.toJson());
            }
        };
        collection.find(gt("i", 50)).forEach(printBlock);

        // filter where; 50 < i <= 100
        collection.find(and(gt("i", 50), lte("i", 100))).forEach(printBlock);

        // Sorting
        myDoc = collection.find(exists("i")).sort(descending("i")).first();
        System.out.println(myDoc.toJson());

        // Projection
        myDoc = collection.find().projection(excludeId()).first();
        System.out.println(myDoc.toJson());

        // Aggregation
        collection.aggregate(asList(
                match(gt("i", 0)),
                project(Document.parse("{ITimes10: {$multiply: ['$i', 10]}}")))
        ).forEach(printBlock);

        myDoc = collection.aggregate(singletonList(group(null, sum("total", "$i")))).first();
        System.out.println(myDoc.toJson());

        // Update One
        collection.updateOne(eq("i", 10), set("i", 110));

        // Update Many
        UpdateResult updateResult = collection.updateMany(lt("i", 100), inc("i", 100));
        System.out.println(updateResult.getModifiedCount());

        // Delete One
        collection.deleteOne(eq("i", 110));

        // Delete Many
        DeleteResult deleteResult = collection.deleteMany(gte("i", 100));
        System.out.println(deleteResult.getDeletedCount());

        collection.drop();

        // ordered bulk writes
        List<WriteModel<Document>> writes = new ArrayList<WriteModel<Document>>();
        writes.add(new InsertOneModel<Document>(new Document("_id", 4)));
        writes.add(new InsertOneModel<Document>(new Document("_id", 5)));
        writes.add(new InsertOneModel<Document>(new Document("_id", 6)));
        writes.add(new UpdateOneModel<Document>(new Document("_id", 1), new Document("$set", new Document("x", 2))));
        writes.add(new DeleteOneModel<Document>(new Document("_id", 2)));
        writes.add(new ReplaceOneModel<Document>(new Document("_id", 3), new Document("_id", 3).append("x", 4)));

        collection.bulkWrite(writes);

        collection.drop();

        collection.bulkWrite(writes, new BulkWriteOptions().ordered(false));
        //collection.find().forEach(printBlock);

        // Clean up
        database.drop();

        // release resources
        mongoClient.close();
    }
}

Run

mvn compile

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

{"_id": {"$oid": "5c74f280d9f19b2d98feae08"}, "name": "MongoDB", "type": "database", "count": 1, "info": {"x": 203, "y": 102}}
total # of documents after inserting 100 small ones (should be 101) 101
{"_id": {"$oid": "5c74f280d9f19b2d98feae08"}, "name": "MongoDB", "type": "database", "count": 1, "info": {"x": 203, "y": 102}}
{"_id": {"$oid": "5c74f280d9f19b2d98feae08"}, "name": "MongoDB", "type": "database", "count": 1, "info": {"x": 203, "y": 102}}
{"_id": {"$oid": "5c74f280d9f19b2d98feae09"}, "i": 0}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0a"}, "i": 1}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0b"}, "i": 2}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0c"}, "i": 3}
...
...
...
{"_id": {"$oid": "5c74f280d9f19b2d98feae69"}, "i": 96}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6a"}, "i": 97}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6b"}, "i": 98}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6c"}, "i": 99}
{"_id": {"$oid": "5c74f280d9f19b2d98feae08"}, "name": "MongoDB", "type": "database", "count": 1, "info": {"x": 203, "y": 102}}
{"_id": {"$oid": "5c74f280d9f19b2d98feae09"}, "i": 0}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0a"}, "i": 1}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0b"}, "i": 2}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0c"}, "i": 3}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0d"}, "i": 4}
...
...
...
{"_id": {"$oid": "5c74f280d9f19b2d98feae69"}, "i": 96}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6a"}, "i": 97}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6b"}, "i": 98}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6c"}, "i": 99}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6c"}, "i": 99}
{"name": "MongoDB", "type": "database", "count": 1, "info": {"x": 203, "y": 102}}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0a"}, "ITimes10": 10}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0b"}, "ITimes10": 20}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0c"}, "ITimes10": 30}
{"_id": {"$oid": "5c74f280d9f19b2d98feae0d"}, "ITimes10": 40}
...
...
...
{"_id": {"$oid": "5c74f280d9f19b2d98feae69"}, "ITimes10": 960}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6a"}, "ITimes10": 970}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6b"}, "ITimes10": 980}
{"_id": {"$oid": "5c74f280d9f19b2d98feae6c"}, "ITimes10": 990}
{"_id": null, "total": 4950}
99
99