MongoDB Database: Query, Indexing, and Performance

This guide provides a comprehensive overview of MongoDB database query, indexing, and performance. It covers topics such as creating indexes, executing queries, and improving performance. The guide also includes a bibliography of relevant research studies on MongoDB.

Running head: MONGODB DATABASE
MongoDB Database
Name of the Student
Name of the University

1MONGODB DATABASE
Table of Contents
Part A: Query.............................................................................................................................2
Index 1:...................................................................................................................................2
Index 2:...................................................................................................................................2
Index 3:...................................................................................................................................2
Query 1:..................................................................................................................................2
Query 2:..................................................................................................................................2
Query 3:..................................................................................................................................2
Query 4:..................................................................................................................................2
Query 5:..................................................................................................................................2
Query 6:..................................................................................................................................2
Query 7:..................................................................................................................................3
Query 8:..................................................................................................................................3
Query 9:..................................................................................................................................3
Query 10:................................................................................................................................3
Query 11:................................................................................................................................3
Bibliography:..............................................................................................................................5

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Part A: Query
Index 1:
db.getCollection('Movie').createIndex( { MovieID: 1 } );
Index 2:
db.getCollection('Movie').createIndex( { MovieID: 1 }, { collation: { Country: "Japan" } } );
Index 3:
db.getCollection('Movie').createIndex( { MovieName: 1 }, { collation: { Country:
"Japan" } } );
Query 1:
db.getCollection('Movie').find({}, {MovieID: '1', '_id':0})
Query 2:
db.getCollection('Movie').find({Country: 'Japan'})
Query 3:
db.getCollection('Movie').find({}, {MovieName: 1, Director: 1, '_id':0})
Query 4:
db.getCollection('Movie').find({}, {MovieName: '2001', Director: 'Japan', '_id':0})
Query 5:
db.getCollection('Movie').distinct("Director")
Query 6:
db.getCollection('Movie').count({}, {MovieID: 1, '_id':0})

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Query 7:
db.Movie.find({OscarsWon: { $exists: false }})
Query 8:
db.getCollection('Movie').find({ReleaseDate: {$lte: '1968'}})
Query 9:
db.Movie.aggregate([{$lookup:{from:"Movie", localField: "MovieID",
foreignField: "MovieID", as: "MovieRating"}}, {$replaceRoot: { newRoot:
{ $mergeObjects: [ { $arrayElemAt: [ "$MovieRating", 0 ] }, "$$ROOT" ] } } }, {$group:
{_id: {Movie: "$MovieID", MovieName: "$MovieName"}, averageRating: {$avg:
"$Rating"}}}]);
Query 10:
db.Movie.aggregate([{ $lookup:{from:"Rating", localField: "MovieID", foreignField:
"MovieID", as: "MovieRating"}}, {$replaceRoot: { newRoot: { $mergeObjects:
[ { $arrayElemAt: [ "$MovieRating ", 0 ] }, "$$ROOT" ] } } }, {$project : {"MovieName":
1, MovieRating: {"Rating": 1, "Comments": 1}}}]);
Query 11:
db.Movie.update(
{ MovieName: "ET" },
{
MovieID: "6",
MovieName: "E.T.",
Director: "Steven Spielberg",

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ReleaseDate: "1982",
OscarsWon: "4",
Country: "USA"
},
{ upsert: true }
)
Query 12: db.getCollection
('Movie').update
({MovieID: "12"},
{$set:{ notes: "Terminator and Terminator 2 are rated together"}})
db.getCollection
('Movie').update
({MovieID: "18"},
{$set:{ notes: "The trilogy consists of the three movies "}})

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Bibliography:
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ontology from MongoDB database. In International Conference on Intelligent Systems
Design and Applications (pp. 612-621). Springer, Cham.
Abbes, H. and Gargouri, F., 2016. Big data integration: A MongoDB database and modular
ontologies based approach. Procedia Computer Science, 96, pp.446-455.
Abbes, H., Boukettaya, S. and Gargouri, F., 2015, November. Learning ontology from big
data through MongoDB database. In Computer Systems and Applications (AICCSA), 2015
IEEE/ACS 12th International Conference of (pp. 1-7). IEEE.
Aboutorabi, S.H., Rezapour, M., Moradi, M. and Ghadiri, N., 2015, August. Performance
evaluation of SQL and MongoDB databases for big e-commerce data. In Computer Science
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Chauhan, D. and Bansal, K.L., 2017. Using the Advantages of NoSQL: A case study on
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quality in open data: A case study. In de Innovacion y Tendencias en Ingenieria (CONIITI),
2017 Congreso Internacional (pp. 1-5). IEEE.

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Gousios, G., Vasilescu, B., Serebrenik, A. and Zaidman, A., 2014, May. Lean GHTorrent:
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