Difference between revisions of "Mobeen-big-data"

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(1. Identifying and downloading the target data set)
(1. Identifying and downloading the target data set)
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*The downloaded data is on cluster at:  /cluster/home/mmludin08/Big-Data-M
 
*The downloaded data is on cluster at:  /cluster/home/mmludin08/Big-Data-M
  
- ad;lja;lf
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The Big-Data-M contains the follwing directories and files:
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*  '''Directories: Backupfiles  Clean_Data  Q_results    Scripts'''
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*  '''Files:      bigdata.sql  movies.csv  ratings.csv  tags.csv'''
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- The Backupfiles directory contains the data set that was downloaded from Movielens.
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- The Clean_Data directory has all the data files that were formated by using the perl/python scripts.
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- The Q_results directory has
  
 
==== 2. Data cleaning and per-processing ====
 
==== 2. Data cleaning and per-processing ====

Revision as of 08:49, 14 December 2011

MovieLens Data Sets Project

Project data set

  • This data set contains 10000054 ratings and 95580 tags applied to 10681 movies by 71567 users of the online movie recommender service MovieLens.
  • Link to data set: http://www.grouplens.org/node/12

Project Tasks

1. Identifying and downloading the target data set

  • The downloaded data is on cluster at: /cluster/home/mmludin08/Big-Data-M

The Big-Data-M contains the follwing directories and files:

  • Directories: Backupfiles Clean_Data Q_results Scripts
  • Files: bigdata.sql movies.csv ratings.csv tags.csv
- The Backupfiles directory contains the data set that was downloaded from Movielens. 
- The Clean_Data directory has all the data files that were formated by using the perl/python scripts.
- The Q_results directory has

2. Data cleaning and per-processing

  • The original data was in the .dat format. one perl script and a python script was written to change the formate and clean the data.

3. Load the data into your Postgres instance

  • After the cleaning the data was uploaded to cluster and laptop machine.

4. Develop queries to explore your ideas in the data

  • SQL statements with results are on cluster: /cluster/home/mmludin08/Big-Data-M

5. Develop and document the model function you are exploring in the data

  • For this project my aim was to discover the movie genres time line. In more words, I wanted to find out at what period of time people watch what type of movies. I also tried to look for the pattern

6. Develop a visualization to show the model/patterns in the data

Tech Details
  • Node: as7
  • Path to storage space: /scratch/big-data/mobeen
Results
  • The visualization(s)
  • The story