MAP REDUCE - HADOOP - SPARK - PYTHON: Need algorithms written to be used with my data-sets

Hello,

First and foremost, the requirements of this project are not very technical.

PROJECT DESCRIPTION: I need someone who can get the job done without asking too many questions, someone who is proficient in using Hadoop, MAP Reduce, Spark and can code in python.

If you have the skills as mentioned above, then please continue reading.

You must build me the following:

- Implement an algorithm to obtain the first (n) most frequent words in a large text file using Hadoop Map reduce. (n) = is the data-set, which you will be provided.

- Implement an algorithm to obtain the (AVERAGE) of all (n) (MOST FREQUENT WORDS) that appear in the text file using Hadoop Map reduce.

- Implement an algorithm to obtain the first (n) most frequent words in a large text file using Hadoop Spark.

- Ability to use (NMON) to compare the performances of the algorithms.

- Implement a simple (MIN-HASHING) algorithm, this must be written in Hadoop Spark. This algorithm will be used to compare 5 files, where their signatures will be used by (JACCARD SIMILARITY METRIC).

- Testing all algorithms with other provided data-sets.

You must absolutely be able to do what has been mentioned in the project description.

Please do not BID if you are not capable of doing this project.

Thank you!

Big Data Sales Hadoop Map Reduce Python Spark

Project ID: #11916153

About the project