MongoDB M101N Final Exam Question 10

Question 10:

We perform the following query on the enron dataset:

var exp = db.messages.explain('executionStats')

exp.find( { 'headers.Date' : { '$gt' : new Date(2001,3,1) } }, { 'headers.From' : 1, '_id' : 0 } ).sort( { 'headers.From' : 1 } )

and get the following explain output.  

MongoDB M101N Final Exam Question 9

Question 9:

Imagine an electronic medical record database designed to hold the medical records of every individual in the United States. Because each person has more than 16MB of medical history and records, it's not feasible to have a single document for every patient. Instead, there is a patient collection that contains basic information on each person and maps the person to a patient_id, and a record collection that contains one document for each test or procedure. One patient may have dozens or even hundreds of documents in the record collection.
We need to decide on a shard key to shard the record collection. What's the best shard key for the record collection, provided that we are willing to run inefficient scatter-gather operations to do infrequent research and run studies on various diseases and cohorts? That is, think mostly about the operational aspects of such a system. And by operational, we mean, think about what the most common operations that this systems needs to perform day in and day out.

MongoDB M101N Final Exam Question 8

Question 8:

Supposed we executed the following C# code. How many animals will be inserted into the "animals" collection?

using MongoDB.Bson;
using MongoDB.Driver;
using System.Threading.Tasks;

namespace M101DotNet
{
    class InsertTest
    {
        static void Main(string[] args)
        {
            MainAsync(args).GetAwaiter().GetResult();
        }

        static async Task MainAsync(string[] args)
        {
            var client = new MongoClient();
            var db = client.GetDatabase("test");

            var animals = db.GetCollection<BsonDocument>("animals");

            var animal = new BsonDocument
                            {
                            {"animal", "monkey"}
                            };

            await animals.InsertOneAsync(animal);
            animal.Remove("animal");
            animal.Add("animal", "cat");
            animal["_id"] = ObjectId.GenerateNewId();
            await animals.InsertOneAsync(animal);
            animal.Remove("animal");
            animal.Add("animal", "lion");
            animal["_id"] = ObjectId.GenerateNewId();
            await animals.InsertOneAsync(animal);
        }
    }
}

MongoDB M101N Final Exam Question 7

Question 7:

You have been tasked to cleanup a photo-sharing database. The database consists of two collections, albums, and images. Every image is supposed to be in an album, but there are orphan images that appear in no album. Here are some example documents (not from the collections you will be downloading). 

> db.albums.findOne()
{
    "_id" : 67
    "images" : [
        4745,
        7651,
        15247,
        17517,
        17853,
        20529,
        22640,
        27299,
        27997,
        32930,
        35591,
        48969,
        52901,
        57320,
        96342,
        99705
    ]
}

> db.images.findOne()
{ "_id" : 99705, "height" : 480, "width" : 640, "tags" : [ "dogs", "kittens", "work" ] }

MongoDB M101N Final Exam Question 6

Question 6:

Suppose you have a collection of students of the following form:

{
 "_id" : ObjectId("50c598f582094fb5f92efb96"),
 "first_name" : "John",
 "last_name" : "Doe",
 "date_of_admission" : ISODate("2010-02-21T05:00:00Z"),
 "residence_hall" : "Fairweather",
 "has_car" : true,
 "student_id" : "2348023902",
 "current_classes" : [
  "His343",
  "Math234",
  "Phy123",
  "Art232"
 ]
}

Now suppose that basic inserts into the collection, which only include the last name, first name and student_id, are too slow (we can't do enough of them per second from our program). What could potentially improve the speed of inserts. Check all that apply.

MongoDB M101N Final Exam Question 5

Question 5:

Suppose your have a collection fubar with the following indexes created:

[
    {
        "v" : 1,
        "key" : {
            "_id" : 1
        },
        "ns" : "test.fubar",
        "name" : "_id_"
    },
    {
        "v" : 1,
        "key" : {
            "a" : 1,
            "b" : 1
        },
        "ns" : "test.fubar",
        "name" : "a_1_b_1"
    },
    {
        "v" : 1,
        "key" : {
            "a" : 1,
            "c" : 1
        },
        "ns" : "test.fubar",
        "name" : "a_1_c_1"
    },
    {
        "v" : 1,
        "key" : {
            "c" : 1
        },
        "ns" : "test.fubar",
        "name" : "c_1"
    },
    {
        "v" : 1,
        "key" : {
            "a" : 1,
            "b" : 1,
            "c" : -1
        },
        "ns" : "test.fubar",
        "name" : "a_1_b_1_c_-1"
    }
]

MongoDB M101N Final Exam Question 4

Question 4:

For this problem, you will be implementing the functionality needed to "like" a comment in the blog.
First, download and unpack the blog solution handout from here
Next, find the "XXX" in HomeController.cs. This is where you will need to code in the ability to "like" a comment.
When you are done, the following functionality will be in place:

• When you are logged in, and you view a post in its own page (/Home/Post/<post_id>), each post will have a number of "Likes".
• When you click on the "Likes" button, it gets incremented by one.
• You can like a comment as many times as you wish; each click will increment it by one.
• You can even like your own comments.

In your "blog.posts" documents, the "Comments" subdocuments will each contain a "Likes" field. Its value will be a number, and that number will be the number of "Likes" for that comment. Here is an example:

MongoDB M101N Final Exam Question 3

Question 3:

In this problem, the database will begin in an initial state, you will manipulate it, and we will verify that the database is in the correct final state when you click 'submit'. If you need to start over at any point, you can click 'reset' to re-initialize the database, but this will not change your answer if you have already clicked 'submit'. If you wish to change your answer, get the database into the correct state, and then click 'submit'. If you leave the question and come back, the database will re-initialize. If you have clicked the 'submit' button at least once, you will see the word "Submitted" below the shell.
 
In this problem you will update a document in the messages collection to illustrate your mastery of updating documents from the shell. In fact, we've created a collection with a very similar schema to the Enron dataset, but filled instead with randomly generated data.

MongoDB M101N Final Exam Question 2

Question 2:

Please use the Enron dataset you imported for the previous problem. For this question you will use the aggregation framework to figure out pairs of people that tend to communicate a lot. To do this, you will need to unwind the To list for each message.

This problem is a little tricky because a recipient may appear more than once in the To list for a message. You will need to fix that in a stage of the aggregation before doing your grouping and counting of (sender, recipient) pairs.

MongoDB M101N Final Exam Question 1

Question 1:

Please download the Enron email dataset enron.zip, unzip it and then restore it using mongorestore. It should restore to a collection called "messages" in a database called "enron". Note that this is an abbreviated version of the full corpus. There should be 120,477 documents after restore.

Inspect a few of the documents to get a basic understanding of the structure. Enron was an American corporation that engaged in a widespread accounting fraud and subsequently failed.