Read Data using Operators and Compound Queries

What You’ll Need¶

If you have not already installed a client (e.g. a driver, MongoDB Compass, or the mongo shell), complete the Connect to MongoDB guide before attempting this guide.

If you have not already installed a client (e.g. a driver, MongoDB Compass, or the mongo shell), complete the Connect to MongoDB guide before attempting this guide.
Enable Auth on your local instance of MongoDB.

Warning

If you are running MongoDB locally and have not enabled authentication, your MongoDB instance is not secure.

Check Your Environment¶

You will need to ensure that your MongoDB instance is running and accessible.

Check that you have an Atlas account and have deployed a MongoDB database cluster. See Get Started with Atlas for information on how to login and create a cluster in Atlas.

Windows
macOS
Linux

To make sure that your MongoDB instance is running on Windows, run the following command from the Windows command prompt:

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tasklist /FI "IMAGENAME eq mongod.exe"

If a mongod.exe instance is running, you will see something like:

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Image Name                     PID Session Name        Session#    Mem Usage
========================= ======== ================ =========== ============
mongod.exe                    8716 Console                    1      9,508 K

To make sure your MongoDB instance is running on Mac, run the following command from your terminal:

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ps -e | grep 'mongod'

If a mongod instance is running, you will see something like:

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89780 ttys026    0:53.48 ./mongod

To make sure your MongoDB instance is running on Linux, run the following command from your terminal:

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ps -e| grep 'mongod'

If a mongod instance is running, you will see something like:

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89780 ttys026    0:53.48 ./mongod

Procedure¶

Read Data with Embedded Fields and Comparison Operators¶

In this exercise, you will read data using comparison operators.

1

Connect to your MongoDB instance.¶

Select the operating system platform on which you are running the MongoDB client you have selected.

Windows
macOS
Linux

Pass the URI to the mongo shell followed by the --password option. You will then be prompted for your password.

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mongo.exe <URISTRING_SHELL_NOUSER>

Pass the URI to the mongo shell followed by the --password option. You will then be prompted for your password.

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mongo <URISTRING_SHELL_NOUSER>

Pass the URI to the mongo shell followed by the --password option. You will then be prompted for your password.

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mongo <URISTRING_SHELL_NOUSER>

If you wish to manually configure your Compass connection, load Compass and select the New Connection link. You will see a form where you can enter connection information for MongoDB.

Atlas users can copy a URI string from the Atlas console into Compass. MongoDB Compass can detect whether you have a MongoDB URI connection string in your system clipboard and auto- populate the connection dialog from the URI.

See Set Up Atlas Connectivity for information on how to get the Atlas connection string URI into your copy buffer.

If Compass was already running when you copied the URI string, click the NEW CONNECTION button.

You will be prompted to populate the connection dialog. Click Yes.

You should then populate the password field with the proper password for your MongoDB user in the connection form.

Note

Errors related to connecting through Compass will appear in red at the top of the Connect screen.

It’s a good idea to put your connection code in a class so that it can be reused.

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from pymongo import MongoClient

class Connect(object):
    @staticmethod    
    def get_connection():
        return MongoClient("<URISTRING>")

If your connection_string starts with mongodb+srv, you need to install the dnspython module with

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python -m pip install dnspython

Now add code to call the class you just created.

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from connect import Connect
from pymongo import MongoClient

connection = Connect.get_connection()

For the MongoDB java driver 3.7 and beyond, use the MongoClients.create() method.

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    final String uriString = "<URISTRING>";
    MongoClient mongoClient = MongoClients.create(uriString);

For legacy drivers (prior to 3.7), use:

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    final String uriString = "<URISTRING>";
    MongoClientURI uri = new MongoClientURI(uriString);
    MongoClient mongoClient = new MongoClient(uri);

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The MongoDB.Bson package is used in CRUD operations, so you’ll import it here.

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using System;
using MongoDB.Bson;
using MongoDB.Driver;

namespace csharptest
{
    class Connect
    {
        static void Main(string[] args)
        {
           var client = new MongoClient("<URISTRING>");
        }
    }
}

Replace your password and any parameters surrounded by $[] in the connection string in the code below.

For now, you will use the context.TODO().

Later you’ll configure the context specific to your requirements.

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client, err := mongo.Connect(context.TODO(), "<URISTRING>");

if err != nil {
	log.Fatal(err)
}

You won’t know if the connection has been successful until you use the connection. A ping is one way you can test the connection. This is a full example of a Go connection to mongoDB, including a test ping.

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package main

import (
	"context"
	"fmt"
	"github.com/mongodb/mongo-go-driver/mongo"
	"log"
)

func main() {
	// Open Connection
	client, err := mongo.Connect(context.TODO(), "<URISTRING>");

	if err != nil {
		log.Fatal(err)
	}

	// End Open Connection Code

	// Check the connection
	err = client.Ping(context.TODO(), nil)

	if err != nil {
		log.Fatal(err)
	}

	fmt.Println("Connected to MongoDB!")

}

In your Go workspace and project folder, run build.

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go build

Now run the binary. For binaries that are not installed, you’ll have to specify the path.

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go <path-to-yourproject>

If you’d like to run the resulting binary without specifying a path, install the binary you just built into your Go workspace.

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go install

Now run the code. “yourprojectname” is the name of the project directory that contains the file with your main() function.

For installed binaries use:

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go yourprojectname

For binaries that are not installed, you’ll have to specify the path.

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go ./yourprojectname

The default timeout for the Go driver to connect to the database is 30 seconds. In the event that you are unable to connect, you will see an error that resembles this:

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2019/01/09 10:01:50 server selection timeout

2

Switch to the `test` database.¶

Switch to the database you wish to query. In this case we will be using test.

To switch to the test database in the mongo shell, type

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use test

If the database has not been created already, click the Create Database button.

Screeenshot after connecting with the "Create Database" button.

Select the test database on the left side of the Compass interface. Compass will list all of the collections in the database below the database name.

Screenshot of the MongoDB Compass UI showing with the "test" database selected in the list of databases in the cluster.

To access the test database:

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db = client.test

Switch to the test database and access the inventory collection.

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MongoDatabase mongoDB = mongoClient.getDatabase("test");
MongoCollection<Document> collection = mongoDB.getCollection("inventory");

Within the connect block, set db to the test database.

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const db = client.db("test");

To access the test database:

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db = client.test

Switch to the test database and access the inventory collection.

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var database = client.GetDatabase("test");
var collection = database.GetCollection<BsonDocument>("inventory");

To access the test database:

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db := client.Database("test")

3

Select documents using the less-than operator.¶

The following example retrieves all documents from the inventory collection where the size.h field is less than 15. MongoDB uses dot notation to specify fields within embedded documents. size.h refers to the h field in the size document.

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myCursor = db.inventory.find( { "size.h": { $lt: 15 } } )

Copy the following filter into the Compass query bar and click Find:

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{ "size.h": { $lt: 15 } }

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cursor = db.inventory.find({"size.h": {"$lt": 15}})

First you will need to create the MongoCollection object you would like to query against.

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MongoCollection<Document> collection = db.getCollection("inventory");

Next pass the query document to the collection.find() method.

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findIterable = collection.find(lt("size.h", 15));

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var cursor = db.collection('inventory').find({ 
  "size.h": { $lt: 15 }
});

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cursor = db.inventory.find({"size.h": {"$lt": 15}})

For completeness, this is how you might wrap this call and run it with the asyncio event loop.

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async def do_retrieve_operator():
    cursor = db.inventory.find({"size.h": {"$lt": 15}})
    async for doc in cursor:
        pprint.pprint(doc)

loop = asyncio.get_event_loop()
loop.run_until_complete(do_retrieve_operator())

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var filter = Builders<BsonDocument>.Filter.Lt("size.h", 15);
var result = collection.Find(filter).ToList();

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cursor, err := coll.Find(
	context.Background(),
	bson.D{
		{"size.h", bson.D{
			{"$lt", 15},
		}},
	})

4

Iterate over the results.¶

By default, the shell will only show the first 20 documents and return a cursor. This is adequate when the result set only contains a few documents.

If your result set is larger, to see all of the results of your query, iterate the cursor.

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while (myCursor.hasNext()) {
    print(tojson(myCursor.next()));
}

Note

You can also manually iterate through the results by typing it when prompted by the shell.

You will see a list of all of the documents that match your criteria in the query window.

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from pprint import pprint

for inventory in cursor:
     pprint(inventory)

You can implement a java.util.function.Consumer to print the results of the iteration

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Consumer<Document> printConsumer = new Consumer<>() {
    public void accept(final Document doc) {
        System.out.println(doc.toJson());
    }
};

Then iterate the cursor for documents, passing the printConsumer as a parameter.

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findIterable.forEach(printConsumer);

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function iterateFunc(doc) {
   console.log(JSON.stringify(doc, null, 4));
}

function errorFunc(error) {
   console.log(error);
}

cursor.forEach(iterateFunc, errorFunc);

In the code snippet above you may have noticed the code that iterates the results and prints them to the command line:

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async for doc in cursor:
    print(doc)

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foreach (var doc in result) {
   Console.WriteLine(doc.ToJson());
}

Iterate the results and print them to the command line:

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for cursor.Next(context.TODO()) {
    elem := &bson.D{}
    if err := cursor.Decode(elem); err != nil {
            log.Fatal(err)
    }
    // ideally, you would do something with elem....
    // but for now just print it to the console
    fmt.Println(elem)
}

5

Check your results.¶

If you have loaded data into your test database, you will see one or more JSON documents returned. Note that the records have a height (“size.h”) of less than 15.

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{ "_id" : ObjectId("5ae14d2e124da839884ff939"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : ObjectId("5ae14d2e124da839884ff93a"), "item" : "notebook", "qty" : 50, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "A" }
{ "_id" : ObjectId("5ae14d2e124da839884ff93b"), "item" : "paper", "qty" : 100, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "D" }
{ "_id" : ObjectId("5ae14d2e124da839884ff93d"), "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

../../_images/compass-find-nested-query-op.png

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{u'_id': ObjectId('5ada625baea65088bf0aa131'),
 u'item': u'journal',
 u'qty': 25,
 u'size': {u'h': 14, u'uom': u'cm', u'w': 21},
 u'status': u'A'}
{u'_id': ObjectId('5ada625baea65088bf0aa132'),
 u'item': u'notebook',
 u'qty': 50,
 u'size': {u'h': 8.5, u'uom': u'in', u'w': 11},
 u'status': u'A'}
{u'_id': ObjectId('5ada625baea65088bf0aa133'),
 u'item': u'paper',
 u'qty': 100,
 u'size': {u'h': 8.5, u'uom': u'in', u'w': 11},
 u'status': u'D'}
{u'_id': ObjectId('5ada625baea65088bf0aa135'),
 u'item': u'postcard',
 u'qty': 45,
 u'size': {u'h': 10, u'uom': u'cm', u'w': 15.25},
 u'status': u'A'}

Create a method to print the results of the iteration

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{ "_id" : { "$oid" : "5ada88359b267e9b5bd393b9" }, "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : { "$oid" : "5ada88359b267e9b5bd393ba" }, "item" : "notebook", "qty" : 50, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "A" }
{ "_id" : { "$oid" : "5ada88359b267e9b5bd393bb" }, "item" : "paper", "qty" : 100, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "D" }
{ "_id" : { "$oid" : "5ada88359b267e9b5bd393bd" }, "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

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{ _id: 5ade424c84c9ca2d56d31697,
  item: 'journal',
  qty: 25,
  size: { h: 14, w: 21, uom: 'cm' },
  status: 'A' }
{ _id: 5ade424c84c9ca2d56d31698,
  item: 'notebook',
  qty: 50,
  size: { h: 8.5, w: 11, uom: 'in' },
  status: 'A' }
{ _id: 5ade424c84c9ca2d56d31699,
  item: 'paper',
  qty: 100,
  size: { h: 8.5, w: 11, uom: 'in' },
  status: 'D' }
{ _id: 5ade424c84c9ca2d56d3169b,
  item: 'postcard',
  qty: 45,
  size: { h: 10, w: 15.25, uom: 'cm' },
  status: 'A' }

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{'_id': ObjectId('5adb5140aea650d18e402f17'),
 'item': 'journal',
 'qty': 25,
 'size': {'h': 14, 'uom': 'cm', 'w': 21},
 'status': 'A'}
{'_id': ObjectId('5adb5140aea650d18e402f18'),
 'item': 'notebook',
 'qty': 50,
 'size': {'h': 8.5, 'uom': 'in', 'w': 11},
 'status': 'A'}
{'_id': ObjectId('5adb5140aea650d18e402f19'),
 'item': 'paper',
 'qty': 100,
 'size': {'h': 8.5, 'uom': 'in', 'w': 11},
 'status': 'D'}
{'_id': ObjectId('5adb5140aea650d18e402f1b'),
 'item': 'postcard',
 'qty': 45,
 'size': {'h': 10, 'uom': 'cm', 'w': 15.25},
 'status': 'A'}

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{ "_id" : ObjectId("5ade261a9270d01f8c3d2750"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : ObjectId("5ade261a9270d01f8c3d2751"), "item" : "notebook", "qty" : 50, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "A" }
{ "_id" : ObjectId("5ade261a9270d01f8c3d2752"), "item" : "paper", "qty" : 100, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "D" }
{ "_id" : ObjectId("5ade261a9270d01f8c3d2754"), "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

Read Data with Compound Queries¶

Now you will read data from MongoDB using AND and OR logic to form compound queries.

1

Write an implied AND query.¶

To write a compound query in MongoDB that matches all of the query predicates (i.e. a logical AND), specify all of the fields that you wish to match in your find document. By default, MongoDB matches all of the fields.

The following example retrieves all documents in the inventory collection where the status equals "A" and qty is less than ($lt) 30:

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myCursor = db.inventory.find( { status: "A", qty: { $lt: 30 } } )

Copy the following filter into the Compass query bar and click Find:

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{ status: "A", qty: { $lt: 30 } }

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cursor = db.inventory.find({"status": "A", "qty": {"$lt": 30}})

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findIterable = collection.find(and(eq("status", "A"), lt("qty", 30)));

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var cursor = db.collection('inventory').find({ 
  status: "A", 
  qty: { $lt: 30 }
});

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cursor = db.inventory.find({"status": "A", "qty": {"$lt": 30}})

For completeness, this is how you might wrap this call and run it with the asyncio event loop.

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async def do_retrieve_implied_and():
   cursor = db.inventory.find({"status": "A", "qty": {"$lt": 30}})
   async for doc in cursor:
       pprint.pprint
loop = asyncio.get_event_loop()
loop.run_until_complete(do_retrieve_implied_and())

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var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Eq("status", "A"), builder.Lt("qty", 30));
var result = collection.Find(filter).ToList();

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cursor, err := coll.Find(
	context.Background(),
	bson.D{
		{"status", "A"},
		{"qty", bson.D{{"$lt", 30}}},
	})

MongoDB also provides a $and logical operator as part of its logical query operators, but the “implied AND” described above is a more common pattern.

2

Iterate over the results.¶

This query does not require cursor iteration in mongo shell because the shell returns up to 20 results.

You will see a list of all of the documents that match your criteria in the query window.

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from pprint import pprint

for inventory in cursor:
     pprint(inventory)

You can implement a com.mongodb.Block to print the results of the iteration

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

Then iterate the cursor for documents, passing the printBlock as a parameter.

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findIterable.forEach(printBlock);

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function iterateFunc(doc) {
   console.log(JSON.stringify(doc, null, 4));
}

function errorFunc(error) {
   console.log(error);
}

cursor.forEach(iterateFunc, errorFunc);

In the code snippet above you may have noticed the code that iterates the results and prints them to the command line:

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async for doc in cursor:
    print(doc)

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foreach (var doc in result) {
   Console.WriteLine(doc.ToJson());
}

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for cursor.Next(context.TODO()) {
    elem := &bson.D{}
    if err := cursor.Decode(elem); err != nil {
            log.Fatal(err)
    }
    // ideally, you would do something with elem....
    // but for now just print it to the console
    fmt.Println(elem)
}

3

Check your results.¶

If you have loaded data into your test database, you will see one or more JSON documents returned. Your results should look something like the JSON below. Note that the record below has a status of "A" and a qty less than 30 per the criteria in the compound query.

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{ "_id" : ObjectId("5ae14d2e124da839884ff939"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }

../../_images/compass-find-filter-and.png

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{u'_id': ObjectId('5ada625baea65088bf0aa131'),
 u'item': u'journal',
 u'qty': 25,
 u'size': {u'h': 14, u'uom': u'cm', u'w': 21},
 u'status': u'A'}

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{ "_id" : { "$oid" : "5ada88359b267e9b5bd393b9" }, "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }

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{ _id: 5ade424c84c9ca2d56d31697,
  item: 'journal',
  qty: 25,
  size: { h: 14, w: 21, uom: 'cm' },
  status: 'A' }

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{'_id': ObjectId('5adb5140aea650d18e402f17'),
 'item': 'journal',
 'qty': 25,
 'size': {'h': 14, 'uom': 'cm', 'w': 21},
 'status': 'A'}

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{ "_id" : ObjectId("5ade26de3d3a851fcd9c95da"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }

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&[{_id ObjectID("5c3d03fdd183362f86fdd0d6")} {item journal} {qty 25} {size [{h 14} {w 21} {uom cm}]} {status A}]

4

Write an “or” query.¶

Using the $or query operator, specify a compound query that joins each clause with a logical OR conjunction so that the query selects the documents in the collection that match at least one condition.

Using the query operator, specify a compound query that joins each clause with a logical OR conjunction so that the query selects the documents in the collection that match at least one condition.

Using the Or filter method, specify a compound query that joins each clause with a logical OR conjunction so that the query selects the documents in the collection that match at least one condition.

The following example retrieves all documents in the collection where the status equals "A" or qty is less than 30:

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myCursor = db.inventory.find( { $or: [ { status: "A" }, { qty: { $lt: 30 } } ] } )

Copy the following filter into the Compass query bar and click Find:

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{ $or: [ { status: "A" }, { qty: { $lt: 30 } } ] }

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cursor = db.inventory.find({"$or": [{"status": "A"}, {"qty": {"$lt": 30}}]})

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findIterable = collection.find(or(eq("status", "A"), lt("qty", 30)));

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var cursor = db.collection('inventory').find({ 
  $or: [ {status: "A" }, { qty: { $lt: 30 } } ]
});

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cursor = db.inventory.find({"$or": [{"status": "A"}, {"qty": {"$lt": 30}}]})

For completeness, this is how you might wrap this call and run it with the asyncio event loop.

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async def do_retrieve_or():
    cursor = db.inventory.find({"$or": [{"status": "A"}, {"qty": {"$lt": 30}}]})
    async for doc in cursor:
        pprint.pprint(doc)
loop = asyncio.get_event_loop()
loop.run_until_complete(do_retrieve_or())

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var builder = Builders<BsonDocument>.Filter;
var filter = builder.Or(builder.Eq("status", "A"), builder.Lt("qty", 30));
var result = collection.Find(filter).ToList();

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cursor, err := coll.Find(
	context.Background(),
	bson.D{
		{"$or",
			bson.A{
				bson.D{{"status", "A"}},
				bson.D{{"qty", bson.D{{"$lt", 30}}}},
			}},
	})

5

Iterate over the results.¶

By default, the shell will only show the first 20 documents and return a cursor. This is adequate when the result set only contains a few documents.

If your result set is larger, to see all of the results of your query, iterate the cursor.

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while (myCursor.hasNext()) {
    print(tojson(myCursor.next()));
}

Note

You can also manually iterate through the results by typing it when prompted by the shell.

You will see a list of all of the documents that match your criteria in the query window.

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from pprint import pprint

for inventory in cursor:
     pprint(inventory)

You can implement a java.util.function.Consumer to print the results of the iteration

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Consumer<Document> printConsumer = new Consumer<>() {
    public void accept(final Document doc) {
        System.out.println(doc.toJson());
    }
};

Then iterate the cursor for documents, passing the printConsumer as a parameter.

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findIterable.forEach(printConsumer);

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function iterateFunc(doc) {
   console.log(JSON.stringify(doc, null, 4));
}

function errorFunc(error) {
   console.log(error);
}

cursor.forEach(iterateFunc, errorFunc);

In the code snippet above you may have noticed the code that iterates the results and prints them to the command line:

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async for doc in cursor:
    print(doc)

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foreach (var doc in result) {
   Console.WriteLine(doc.ToJson());
}

Iterate the results and print them to the command line:

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for cursor.Next(context.TODO()) {
    elem := &bson.D{}
    if err := cursor.Decode(elem); err != nil {
            log.Fatal(err)
    }
    // ideally, you would do something with elem....
    // but for now just print it to the console
    fmt.Println(elem)
}

6

Check your results.¶

If you have loaded data into your test database, you will see one or more JSON documents returned. Note that the record has a status of "A" but a qty of more than 30, which is acceptable according to the $or criteria.

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{ "_id" : ObjectId("5ae14d2e124da839884ff939"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : ObjectId("5ae14d2e124da839884ff93a"), "item" : "notebook", "qty" : 50, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "A" }
{ "_id" : ObjectId("5ae14d2e124da839884ff93d"), "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

../../_images/compass-find-filter-or.png

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{'_id': ObjectId('5ae14d2e124da839884ff939'),
 'item': 'journal',
 'qty': 25,
 'size': {'h': 14, 'uom': 'cm', 'w': 21},
 'status': 'A'}
{'_id': ObjectId('5ae14d2e124da839884ff93a'),
 'item': 'notebook',
 'qty': 50,
 'size': {'h': 8.5, 'uom': 'in', 'w': 11},
 'status': 'A'}
{'_id': ObjectId('5ae14d2e124da839884ff93d'),
 'item': 'postcard',
 'qty': 45,
 'size': {'h': 10, 'uom': 'cm', 'w': 15.25},
 'status': 'A'}

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{ "_id" : { "$oid" : "5ae39ecb124da8e9ed76c17f" }, "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : { "$oid" : "5ae39ecb124da8e9ed76c180" }, "item" : "notebook", "qty" : 50, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "A" }
{ "_id" : { "$oid" : "5ae39ecb124da8e9ed76c183" }, "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

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[ { _id: 5ae3a1a0fe333febb35af7b3,
    item: 'journal',
    qty: 25,
    size: { h: 14, w: 21, uom: 'cm' },
    status: 'A' },
  { _id: 5ae3a1a0fe333febb35af7b4,
    item: 'notebook',
    qty: 50,
    size: { h: 8.5, w: 11, uom: 'in' },
    status: 'A' },
  { _id: 5ae3a1a0fe333febb35af7b7,
    item: 'postcard',
    qty: 45,
    size: { h: 10, w: 15.25, uom: 'cm' },
    status: 'A' } ]

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{'_id': ObjectId('5ae14d2e124da839884ff939'),
 'item': 'journal',
 'qty': 25,
 'size': {'h': 14, 'uom': 'cm', 'w': 21},
 'status': 'A'}
 '_id': ObjectId('5ae14d2e124da839884ff93a'),
 'item': 'notebook',
 'qty': 50,
 'size': {'h': 8.5, 'uom': 'in', 'w': 11},
 'status': 'A'}
 '_id': ObjectId('5ae14d2e124da839884ff93d'),
 'item': 'postcard',
 'qty': 45,
 'size': {'h': 10, 'uom': 'cm', 'w': 15.25},
 'status': 'A'}

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{ "_id" : ObjectId("5ae3a38356cd4decbfea7a29"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : ObjectId("5ae3a38356cd4decbfea7a2a"), "item" : "notebook", "qty" : 50, "size" : { "h" : 8.5, "w" : 11, "uom" : "in" }, "status" : "A" }
{ "_id" : ObjectId("5ae3a38356cd4decbfea7a2d"), "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

Retrieving Data with More Than One Compounding Clause¶

Now you will retrieve data from MongoDB using AND and OR logic together to form compound queries.

1

Write an implied AND query with an “or” clause.¶

In the following example, the compound query document selects all documents in the collection where the status equals "A" and either qty is less than 30 or item starts with the character p:

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myCursor = db.inventory.find( {
     status: "A",
     $or: [ { qty: { $lt: 30 } }, { item: /^p/ } ]
} )

Copy the following filter into the Compass query bar and click Find:

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{ status: "A", $or: [ { qty: { $lt: 30 } }, { item: /^p/ } ] }

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cursor = db.inventory.find(
    {"status": "A", "$or": [{"qty": {"$lt": 30}}, {"item": {"$regex": "^p"}}]}
)

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findIterable = collection.find(
        and(eq("status", "A"),
                or(lt("qty", 30), regex("item", "^p")))
);

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var cursor = db.collection('inventory').find({ 
  status: "A",
  $or: [ { qty: { $lt: 30 } }, { item: { $regex: "^p" } } ]
});

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cursor = db.inventory.find(
    {"status": "A", "$or": [{"qty": {"$lt": 30}}, {"item": {"$regex": "^p"}}]}
)

For completeness, this is how you might wrap this call and run it with the asyncio event loop.

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async def do_retrieve_regex():
    cursor = db.inventory.find({
           "status": "A",
           "$or": [{"qty": {"$lt": 30}}, {"item": {"$regex": "^p"}}]})
    async for doc in cursor:
        pprint.pprint(doc)
loop = asyncio.get_event_loop()
loop.run_until_complete(do_retrieve_regex())

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var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(
    builder.Eq("status", "A"),
    builder.Or(builder.Lt("qty", 30), builder.Regex("item", new BsonRegularExpression("^p"))));
var result = collection.Find(filter).ToList();

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cursor, err := coll.Find(
	context.Background(),
	bson.D{
		{"status", "A"},
		{"$or", bson.A{
			bson.D{{"qty", bson.D{{"$lt", 30}}}},
			bson.D{{"item", primitive.Regex{Pattern: "^p", Options: ""}}},
		}},
	})

Note

MongoDB supports regular expressions to perform string pattern matches.

2

Iterate over the results.¶

This query does not require cursor iteration in mongo shell because the shell returns up to 20 results.

You will see a list of all of the documents that match your criteria in the query window.

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from pprint import pprint

for inventory in cursor:
     pprint(inventory)

You can implement a com.mongodb.Block to print the results of the iteration

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

Then iterate the cursor for documents, passing the printBlock as a parameter.

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findIterable.forEach(printBlock);

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function iterateFunc(doc) {
   console.log(JSON.stringify(doc, null, 4));
}

function errorFunc(error) {
   console.log(error);
}

cursor.forEach(iterateFunc, errorFunc);

In the code snippet above you may have noticed the code that iterates the results and prints them to the command line:

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async for doc in cursor:
    print(doc)

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foreach (var doc in result) {
   Console.WriteLine(doc.ToJson());
}

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for cursor.Next(context.TODO()) {
    elem := &bson.D{}
    if err := cursor.Decode(elem); err != nil {
            log.Fatal(err)
    }
    // ideally, you would do something with elem....
    // but for now just print it to the console
    fmt.Println(elem)
}

3

Check your results.¶

If you have loaded data into your test database, you will see one or more JSON documents returned.

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{ "_id" : ObjectId("5ae14d2e124da839884ff939"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : ObjectId("5ae14d2e124da839884ff93d"), "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

../../_images/compass-find-filter-and-or.png

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{u'_id': ObjectId('5ada8c109b267e9d1ade9038'),
 u'item': u'journal',
 u'qty': 25,
 u'size': {u'h': 14, u'uom': u'cm', u'w': 21},
 u'status': u'A'}
{u'_id': ObjectId('5ada8c109b267e9d1ade903c'),
 u'item': u'postcard',
 u'qty': 45,
 u'size': {u'h': 10, u'uom': u'cm', u'w': 15.25},
 u'status': u'A'}

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{ "_id" : { "$oid" : "5ada8c109b267e9d1ade9038" }, "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : { "$oid" : "5ada8c109b267e9d1ade903c" }, "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

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[ { _id: 5adedb5ffa97c643763556e8,
    item: 'journal',
    qty: 25,
    size: { h: 14, w: 21, uom: 'cm' },
    status: 'A' },
  { _id: 5adedb5ffa97c643763556ec,
    item: 'postcard',
    qty: 45,
    size: { h: 10, w: 15.25, uom: 'cm' },
    status: 'A' } ]

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{'_id': ObjectId('5ade276281031b2005294976'),
 'item': 'postcard',
 'qty': 45,
 'size': {'h': 10, 'uom': 'cm', 'w': 15.25},
 'status': 'A'}
{'_id': ObjectId('5ade261a9270d01f8c3d2750'),
 'item': 'journal',
 'qty': 25,
 'size': {'h': 14, 'uom': 'cm', 'w': 21},
 'status': 'A'}

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{ "_id" : ObjectId("5ade276281031b2005294972"), "item" : "journal", "qty" : 25, "size" : { "h" : 14, "w" : 21, "uom" : "cm" }, "status" : "A" }
{ "_id" : ObjectId("5ade276281031b2005294976"), "item" : "postcard", "qty" : 45, "size" : { "h" : 10, "w" : 15.25, "uom" : "cm" }, "status" : "A" }

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&[{_id ObjectID("5c3d03fdd183362f86fdd0d6")} {item journal} {qty 25} {size [{h 14} {w 21} {uom cm}]} {status A}]
&[{_id ObjectID("5c3d03fdd183362f86fdd0da")} {item postcard} {qty 45} {size [{h 10} {w 15.25} {uom cm}]} {status A}]

Python
Java (Sync)
Motor

When you are done working with your MongoDB data, close your connection to MongoDB:

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mongoClient.close();

Summary¶

Congratulations! If you have successfully completed this guide, you have read data from MongoDB using MongoDB query operators and compound queries.

What’s Next¶

In the next guide, you’ll learn how to update data in MongoDB.

Update Data in MongoDB

Read Data using Operators and Compound Queries¶

What You’ll Need¶

Check Your Environment¶

Procedure¶

Read Data with Embedded Fields and Comparison Operators¶

Connect to your MongoDB instance.¶

Switch to the `test` database.¶

Select documents using the less-than operator.¶

Iterate over the results.¶

Check your results.¶

Read Data with Compound Queries¶

Write an implied AND query.¶

Iterate over the results.¶

Check your results.¶

Write an “or” query.¶

Iterate over the results.¶

Check your results.¶

Retrieving Data with More Than One Compounding Clause¶

Write an implied AND query with an “or” clause.¶

Iterate over the results.¶

Check your results.¶

Summary¶

What’s Next¶

See Also¶

Read Data using Operators and Compound Queries¶

What You’ll Need¶

Check Your Environment¶

Procedure¶

Read Data with Embedded Fields and Comparison Operators¶

Connect to your MongoDB instance.¶

Switch to the test database.¶

Select documents using the less-than operator.¶

Iterate over the results.¶

Check your results.¶

Read Data with Compound Queries¶

Write an implied AND query.¶

Iterate over the results.¶

Check your results.¶

Write an “or” query.¶

Iterate over the results.¶

Check your results.¶

Retrieving Data with More Than One Compounding Clause¶

Write an implied AND query with an “or” clause.¶

Iterate over the results.¶

Check your results.¶

Summary¶

What’s Next¶

See Also¶

Switch to the `test` database.¶