COMP336: Big Data - Computer Science Assignment Help

Assignment Task:

Task 1: (15%)
• Dataset: 10000 Tweets; dataset on iLearn “tweets.zip”
• MapReduce: Calculate the count of number of occurrences of each word in the text of Tweets.
• Create a short documentation in which you briefly describe your implementation:
o What to write in the mapper(s) ? Flowchart and Pseudocode !
o What to write in the reducer(s) ? Flowchart and Pseudocode !

Task 2: (15%)
• Dataset: 10000 Tweets; dataset on iLearn “tweets.zip”
• MapReduce: Calculate the count of number of tweets for a list of different cities in Australia.
• Create a short documentation in which you briefly describe your implementation:
o What to write in the mapper(s) ? Flowchart and Pseudocode !
o What to write in the reducer(s) ? Flowchart and Pseudocode !

Task 3: (35%)
• Dataset: 10000 Tweets; dataset on iLearn “tweets.zip”
• MapReduce: Implement the Merge Sort1 algorithm using Map-Reduce.
• MapReduce: Implement the Bucket Sort2 algorithm using Map-Reduce.
• Create a short documentation in which you briefly describe your implementation:
o How many MapReduce Jobs? Why?
o What to write in the mapper(s) ? Flowchart and Pseudocode !
o What to write in the reducer(s) ? Flowchart and Pseudocode !

Task 4: (35%)
• Dataset: 10000 Tweets; dataset on iLearn “tweets.zip”
• MapReduce: Implement the TF-IDF algorithm using Map-Reduce for the term “health” in the text of
the Tweets.
• Create a short documentation in which you briefly describe your implementation:
o How many MapReduce Jobs? Why?
o What to write in the mapper(s) ? Flowchart and Pseudocode !
o What to write in the reducer(s) ? Flowchart and Pseudocode !

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