The purpose of this page is if you are following along on your own or want to copy/paste the answers:
- Deploy the cluster and follow the guide for AtlasSetup.md
- Once complete, click the
...button, then "Load Sample Dataset" and confirm the load. This may take several minutes.
- We will use the
sample_mflix.moviescollection. Press the "Collections" button on the cluster, then that database, then that collection to get to the Document Explorer - We will paste the command below into the box. If using the shell, we should surround the query with
db.movies.find()
| Question | Answer |
|---|---|
| From 1987 | {year:1987} |
| “Comedy” as one of their genres | {genres: "Comedy"} |
| “Comedy as only genre | {genres:["Comedy"]} |
| “Comedy” or “Drama” | {genres:{$in:["Comedy", "Drama"]}} |
| “Comedy” and “Drama” | { genres: { $all: ["Comedy", "Drama"] } } |
| IMDB Rating>8.0 and PG Rating | {"imdb.rating" : {$gt: 8.0}, rated:"PG"} |
| Title starting with “Dr. Strangelove” | {title: {$regex: '^Dr. Strangelove'}} |
For the index section, we will want to identify an optimal indexes (following the ESR rule) for queries like:
db.movies.find(
{
"actors":"Bill Murray",
"year":{$gte: 2000}
}
).sort(
{"title":1}
)
Here we will want to find all comedies, create an individual document for each country, then group by country to get a count.
| Stage | Answer |
|---|---|
| How can you use $match to find all comedies? | $match {genres: "Comedy"} |
| How can you use $unwind to create an individual document for each country? | $unwind {path: "$countries"} |
| How can you use $group to count all the comedies grouped by country? | $group { _id: "$countries", count: {$sum:1}} |
Here we want to restrict output with a calculated field for each movie:
| Stage | Answer |
|---|---|
| Retrieve just the title and how many years old | $project { _id:0, title:1, yearsOld: { $subtract: [2020,"$year"]}} |