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Web Intelligence and Big Data
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Web Intelligence and Big Data
by Dr. Gautam Shroff
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Quiz 4
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The
hard deadline
for this quiz is
Tue 19 Jan 2038 4:14 AM CET
.
In accordance with the Coursera Honor Code, I (Anonymous Student) certify that the answers here are my own work.
Thank you!
Question 1
Which of the following are true about No-SQL databases:Question text
No-SQL databases do not allow one to define indexes on specific attributes
No-SQL databases usually do not support joins
No-SQL databases are always superior in performance to SQL databases
No-SQL databases usually do not support strictly isolated concurrent transactions
Question 2
Which challenges of the map-reduce paradigm are sought to be overcome using the pregel model:
successive map-reduce iterations cannot keep track of results of previous iteratiosn without writing to disk
successive map-reduce iterations often need to read large volumes of data repeatedly fault-tolerence in recursive algorithms
map-reduce requires all data to fit in the total memory of all processors
pregel allows us to process very large volumes of data, beyond the memory capacity of all processors put together
Question 3
Which of the following do you agree with?
deep-analytics using machine-learning techniques is more appropriate when the number of features of one's data is small.
query-based analytics is appropriate when the number of features of one's data is small.
deep-analytics using machine-learning techniques is more appropriate when the number of features of one's data is large.
query-based analytics is appropriate when the number of features of one's data is very large.
Question 4
Which of the following do you agree with:
HBase is an example of a No-SQL database
Pregel and map-reduce are different parallel programming paradigms
Mongo-DB is a reasonable choice to be used for an e-commerce website
HBase is a reasonable choice to be used for a social-networking site
Question 5
In which situation might computing aggregation queries involving joins using map-reduce be difficult as compared to a Dremel-like platform:
When the joins involve too many tables
When the volume of data extremely large; so large that replicating it during computations is not feasible.
When the aggregation queries involve complex, non-commutative functions
When a real-time response is desired, as opposed to a batch computation
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