This report is on the basis of the case study of the Movie Maniac Site. They provide the details of the movies for their clients, today they have to provide the unpretentious components of the flicks for their lovers and they also need to get the reviews of films and store the overview information inside their repository and a short time later they could display those opinions, for example, assessments and remarks for their films which fuses the movie title, director of the movie, lead performing specialists of the movie, release time of the picture, number of Oscars won by the movie and the country of the movie, today they have to store the opinions for the movie, a movie may have different overviews, reviews could be given by a client. (Abramova & Bernardino, 2013)
MongoDB is a No SQL database. It is an open-source, cross-stage, report situated database written in C++.
Here we are using MongoDB to store the information about the movies, as MongoDB stores, the information in the form of the document, in this scenario movie document is prepared for each movie; the structure of the document contains the information about the movies. (Banker, 2011)
A movie can have multiple reviews that would be given by the movie maniac users, for that user only need to submit his/her name along with the rating out of 10 and the comment about the movie
Thus reviews would be a list that contains multiple objects that have the name of the user, rating out of 10 and the comment about the movie. (Membrey & Plugge & Hawkins, 2011)
Structure of the movie document would look like this….
{
“movieId” : 1,
“title” : [
“2001”
],
“director” : [
“Stanley Kubrick”
],
“actors” : [
“Daniel Richter”,
“Gary Lockwood”,
“Keir Dullea”,
“William Sylvester”
],
“releaseDate” : [1968],
“oscars” : 1,
“country” : “USA”
“reviews” [
{
“name”: “Mike”,
“rating”: 6,
“comment”: “Fantastic movie.”
},
{
“name”: “Pike”,
“rating”: 9,
“comment”: “Just Awesome.”
}
]
}
// Output of the records will be like
{
“_id” : ObjectId(“5b900a7ad0ea0f2aecf4600d”),
“movieId” : 3,
“title” : [
“Blade Runner”
],
“director” : [
“Ridley Scott”
],
“actors” : [
“Harrison Ford”,
“Rutger Hauer”,
“Sean Young”
],
“releaseDate” : [
1982
],
“country” : “USA”
}
{
“_id” : ObjectId(“5b900b1ed0ea0f2aecf46035”),
“movieId” : 4,
“title” : [
“Alien”
],
“director” : [
“Ridley Scott”
],
“actors” : [
“Ian Holm”,
“John Hurt”,
“Sigourney Weaver”,
“Tom Skerritt”
],
“releaseDate” : [
1979
],
“oscars” : 1,
“country” : “USA”
}
Indexes are used in the database to access data or information in easy way; indexes are just like the book indexes, if you want to query some information indexes are used to start the searching from the appropriate record and not all records. In this database release date of the movie, a field is being set to index. It will help us to find the record very easily. If we want to display only the movies released before 1980 then index what will do is it will not search for all the records and check them whether it has been released before 1980 or not but it will sort the movies and start searching for some record and not all. (Stanescu & Brezovan & Burdescu, 2016)
There are many alternatives are available in the market to the MongoDB, some are written below.
We realize that MongoDB is a pattern less database. That implies we can have any sort of information in a different archive. This thing gives us adaptability and a flexibility to store information of various sorts.
We can store vast information by conveying it to a few servers associated with the application. On the off chance that a server can’t deal with such major information at that point there will be no disappointment condition. The term we can use here is “auto-sharding”.
MongoDB is a record situated database. It is anything but difficult to get to records by ordering. Consequently, it gives quick question reaction. The speed of MongoDB is 100 times speedier than the social database. (Wei-Ping & Ming-Xin & Huan, 2011)
As in current scenario there are One to one and one to many relationship which are handled by the embedded document –
Reviews will have ratings and the comments for the movie and it is handled by the embedded documents like this-
review : [
{
name : “person 1”,
rating : 3,
comment : ” Comment about a movie by person 1”
},
{
name : “person 2”,
rating : 4,
comment : ” Comment about a movie by person 2”
}
]
References
Abramova, V. and Bernardino, J., 2013, July. NoSQL databases: MongoDB vs cassandra. In Proceedings of the international C* conference on computer science and software engineering (pp. 14-22). ACM.
Banker, K., 2011. MongoDB in action. Manning Publications Co..
Chodorow, K., 2013. MongoDB: The Definitive Guide: Powerful and Scalable Data Storage. ” O’Reilly Media, Inc.”
Islam, R., 2011. PHP and MongoDB Web Development Beginner¿ s Guide. Packt PublishingLtd.
Lawrence, R., 2014, March. Integration and virtualization of relational SQL and NoSQL systems including MySQL and MongoDB. In Computational Science and Computational Intelligence (CSCI), 2014 International Conference on (Vol. 1, pp. 285-290). IEEE.
Leonard, A., 2013. Pro Hibernate and MongoDB. Apress.
Lv, Q. and Xie, W., 2014. A real-time log analyzer based on MongoDB. In Applied Mechanics and Materials (Vol. 571, pp. 497-501). Trans Tech Publications.
Membrey, P., Plugge, E. and Hawkins, D., 2011. The definitive guide to MongoDB: the noSQL database for cloud and desktop computing. Apress.
Okman, L., Gal-Oz, N., Gonen, Y., Gudes, E. and Abramov, J., 2011, November. Security issues in nosql databases. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2011 IEEE 10th International Conference on (pp. 541-547). IEEE.
Parker, Z., Poe, S. and Vrbsky, S.V., 2013, April. Comparing nosql mongodb to an sql db. In Proceedings of the 51st ACM Southeast Conference (p. 5). ACM.
Sattar, A., Lorenzen, T. and Nallamaddi, K., 2013. Incorporating NoSQL into a database course. acm Inroads, 4(2), pp.50-53.
Stanescu, L., Brezovan, M. and Burdescu, D.D., 2016, September. Automatic mapping of MySQL databases to NoSQL MongoDB. In Computer Science and Information Systems (FedCSIS), 2016 Federated Conference on (pp. 837-840). IEEE.
Wei-Ping, Z., Ming-Xin, L.I. and Huan, C., 2011, May. Using MongoDB to implement textbook management system instead of MySQL. In Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on (pp. 303-305). IEEE.
Essay Writing Service Features
Our Experience
No matter how complex your assignment is, we can find the right professional for your specific task. Contact Essay is an essay writing company that hires only the smartest minds to help you with your projects. Our expertise allows us to provide students with high-quality academic writing, editing & proofreading services.
Free Features
Free revision policy
$10Free bibliography & reference
$8Free title page
$8Free formatting
$8How Our Essay Writing Service Works
First, you will need to complete an order form. It's not difficult but, in case there is anything you find not to be clear, you may always call us so that we can guide you through it. On the order form, you will need to include some basic information concerning your order: subject, topic, number of pages, etc. We also encourage our clients to upload any relevant information or sources that will help.
Complete the order form
Once we have all the information and instructions that we need, we select the most suitable writer for your assignment. While everything seems to be clear, the writer, who has complete knowledge of the subject, may need clarification from you. It is at that point that you would receive a call or email from us.
Writer’s assignment
As soon as the writer has finished, it will be delivered both to the website and to your email address so that you will not miss it. If your deadline is close at hand, we will place a call to you to make sure that you receive the paper on time.
Completing the order and download
