Difference between revisions of "Mobeen-big-data"
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*Link to data set: http://www.grouplens.org/node/12 | *Link to data set: http://www.grouplens.org/node/12 | ||
| − | == Project Tasks == | + | === Project Tasks === |
| − | === 1. Identifying and downloading the target data set === | + | ==== 1. Identifying and downloading the target data set ==== |
*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 | ||
| − | === 2. Data cleaning and per-processing === | + | ==== 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. | * 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 === | + | ==== 3. Load the data into your Postgres instance ==== |
* After the cleaning the data was uploaded to cluster and laptop machine. | * After the cleaning the data was uploaded to cluster and laptop machine. | ||
| − | === 4. Develop queries to explore your ideas in the data === | + | ==== 4. Develop queries to explore your ideas in the data ==== |
* SQL statements with results are on cluster: /cluster/home/mmludin08/Big-Data-M | * 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 === | + | ==== 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 | *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 === | + | ==== 6. Develop a visualization to show the model/patterns in the data ==== |
===== Tech Details ===== | ===== Tech Details ===== | ||
Revision as of 07:38, 14 December 2011
Contents
- 1 Project title: MovieLens Data Sets
- 1.1 Project data set
- 1.2 Project Tasks
- 1.2.1 1. Identifying and downloading the target data set
- 1.2.2 2. Data cleaning and per-processing
- 1.2.3 3. Load the data into your Postgres instance
- 1.2.4 4. Develop queries to explore your ideas in the data
- 1.2.5 5. Develop and document the model function you are exploring in the data
- 1.2.6 6. Develop a visualization to show the model/patterns in the data
Project title: MovieLens Data Sets
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
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
