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https://github.com/swag-code/performance-analysis-of-apriori-algorithm-using-mongodb


https://github.com/swag-code/performance-analysis-of-apriori-algorithm-using-mongodb

anaconda-navigator apriori-algorithm big-data comparison excel jupyter-notebook mlxtend mongodb mysql nosql pandas-library performance-analysis python-script rdbms

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# Performance-Analysis-of-Apriori-Algorithm-Using-MongoDB

In present days there are lots of problems with Excel files and RDBMS(MySQL)

to handle a large amount of data, problems like importing the data, Data accessing

time etc. are very common now. To minimize this problem NoSQL Database MongoDB has come into play. Also,

MongoDB is very popular nowadays so I choose this in my project. It also helps

new MongoDB learners & it is very easy to operate since it is schemaless, join free,

document-oriented database and can handle a large amount of structured or

unstructured data.

I have also implemented the Apriori algorithm using excel,

RDBMS(MySQL) and found that the execution gets slow. So I used MongoDB as

database. At the end, I compared their execution time and found that MongoDB

is 79% faster than excel files and 73% faster than RDBMS(MySQL).

By this project I can prove that in Bigdata environment, MongoDB will

be a great choice and these days there are a lot of demand on the market for NoSQL

applications. So I think this application will be very helpful for people who are

interested in MongoDB to use structured and unstructured data.