Comic Crusaders are one of the largest comic books retailer having presence in United States (US) and United Kingdom (UK) who wish to have online presence in the current market. For each book they wish to store the customer’s feedback. Only those customers can provide the feedback who register their name with Comic Crusaders. MongoDB database is being used to store the details like comics, publishers and reviews & ratings. (Anon., 2015).
Like other RDBMS, MongoDB is non-relational. Tables of RDBMS are represented as collection and rows are represented as fields in MongoDB.
Database with the following structure has been created:
Database name: “comiccrusaders”
Collection Name: “comics”
Colletion comics have the following fields:
Each comic is recognized by this field and it is compulsory. It cannot be null.
Title of the comic.
Series of the title e.g. Disney kingdoms. (if any). It can contain a null value.
It just stores the publication year of the comic and cannot be null.
Physical description of the comic book. It is an optional field.
Category or keywords of comic book. It is an optional field. Searching of a comic depends upon this field.
Comic books are presently available in English only. It cannot be null.
Detail of comic book’s publisher is stored e.g. publisher id, publisher name, place of publication and country.
Reviews& Ratings provided by the registered customers. e.g. reviewed by, date, rating and comments. Rating should be out of 10.
"_id" field is created by MongoDB by default to store ObjectId for every single comic.
Indexes in comiccrusaders
In current situation or scenario one index has been created by DB i.e. unique index on comicid for identification of each comic. It is created in ascending order by default. Comic records are easily maintained with all its relevant data. Due to assignment of comicid to each comic it is easy for retailer to fetch its data. (Anon., 2008)
By default, MongoDB creates unique index on _id field for allocation (memory) for each comic in the “comics” collection. (Anon., 2016)
Relationships in comiccrusaders
In comics, embedded relationship has been created. In this associated publisher’s details and reviews & ratings are embedded to the particular comic. In comics reviews are present for some comics and some of the comic(s) reviews are not present. If review is present then it will be displayed else only braces are displayed. In some cases multiple reviews are being stored for the comic but with different reviewID. In this type of relationship the data present is not in the normalized form. (Anon., 2011)
Alternative Modeling (Relationships)
In MongoDB relationships are handled or created by two different ways:
In comiccrusaders embedded relationship has been implemented but referenced approach implementation would be better approach. If we implement referenced approach it would be easy for Comic Crusaders to maintain the data in bulk. Data present in the referenced approach is basically in normalized form. In this ratings & reviews and publisher’s details should be stored in another collection. (França, 2015). We can have 3 collection:
- Comics – comicID, title, series title, date of publication, pubid, physical description, topics and language.
- Reviews – comicID, reviewed by, ratings and comments
- Publishers – pubID, publisher name, place of publication and country.
Isolate data that can be suggested from various spots into its own specific aggregation. If many records will suggest comparable data, it is more capable and less mix-up slanted to revive a single record and keep references to it in various spots. The use of reference approach requires an extra request for a read operation and therefore impact execution. In the referenced model the data is a relationship is the institutionalized shape. It can manage the considerable number of data. For information that should be rehashed crosswise over completed many documents, it can be useful to have them in their own specific unmistakable record. This can decrease messes up and help in keeping the information tried and true (while remembering that different record strengthens are not nuclear). (Nayak, 2016)
In addition, in the event that figure you're presented reports may beat the recording gage confine obliged by MongoDB, by then you'll have to store two or three information in free narratives.
The drawback of this approach is that brain boggling request is to be made for fulfilling the results. If any control like eradication is to be done by then looking at unobtrusive components from various collections ought to be deleted. (Anon., n.d.)
Recommendations to Comic Crusaders
In the wake of breaking down the necessity I might want to recommend or suggest various implementations to the retailer Comic Crusaders:
- They should store the purposes of enthusiasm of their productive customers like customer name, address, mobile number and email.
- They should demonstrate the examinations and reviews of the each comic book open.
- They should in like manner consolidate funnies on another tongue.
- Before circulating the reviews on the site they should coordinate the overviews given by the customers. In case of any objectionable reviews they should obsolete it and inform customers not to post such comments or reviews.
- They should ensure that the funnies or comics are available to them.
- Customers should give the evaluations and reviews to each comic they have examined.
- Each comic should be stand-out.
- Each merchant should be unique.
- Implementation of the site should bid or essential.
- Year of conveyance should be secured.
- They should in like manner start giving the news and updates on their site including latest releases.
- They should also introduce the new features in the site like customers can place an order online with payment made online or cash on delivery.
- They should help the customers to track the delivery of their ordered comic.
- Keywords for each comic should be secured so it is available through the web crawler.
- Customers should have the ability to look through the funnies on the preface of the wholesalers for giving assessments and overviews.(Anon., 2017)
Anon., 2008. Indexes. [Online]
Available at: https://docs.mongodb.com/manual/indexes/
Anon., 2011. Model One-to-One Relationships with Embedded Documents. [Online]
Available at: https://docs.mongodb.com/manual/tutorial/model-embedded-one-to-one-relationships-between-documents/
Anon., 2015. Schema Basics. [Online]
Available at: https://learnmongodbthehardway.com/schema/schemabasics/
Anon., 2016. Indexing and Aggregation in MongoDB Tutorial. [Online]
Available at: https://www.simplilearn.com/indexing-and-aggregation-mongodb-tutorial-video
Anon., 2017. Embedded Documents. [Online]
Available at: https://mongoosejs.com/docs/2.7.x/docs/embedded-documents.html
Anon., n.d. Multiple Collections Versus Embedded Documents. [Online]
Available at: https://openmymind.net/Multiple-Collections-Versus-Embedded-Documents/
França, W. d. R., 2015. MongoDB Data Modeling. s.l.:s.n.
Nayak, A., 2016. MongoDB Cookbook. s.l.:s.n.
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