7 Questions
What is a true benefit of using MapReduce compared to RDBMS?
MapReduce is more scalable than RDBMS and therefore can handle larger datasets than RDBMS.
What is a key advantage of MapReduce over RDBMS according to the text?
MapReduce is fault-tolerant and can handle large-scale data processing efficiently.
What distinguishes MapReduce from RDBMS in terms of data processing?
MapReduce is designed for parallel processing of large datasets, unlike RDBMS.
Which of the following statements about the benefits of MapReduce is false?
MapReduce shuffles less data as a result of using a scaling-out architecture.
Which of the following is a true benefit of using local aggregation within MapReduce?
Less data will be shuffled from the mapper to the reducer.
Given 1 million employee records (containing each employee's name, phone number, date of birth and company join date), which of the following problems will benefit the least from being solved using MapReduce?
Select all employees who joined the company after 2018.
Which of the following statements about the way MapReduce works is false?
Data from the mapper are shuffled and grouped at the reducer according to the output value of the mapper.
Study Notes
Benefits of MapReduce
- MapReduce can process large datasets in parallel, making it more efficient than RDBMS for big data processing
- MapReduce allows for flexible schema, which enables it to handle unstructured or semi-structured data, unlike RDBMS
- MapReduce can scale horizontally, making it suitable for handling large datasets
Key Advantage of MapReduce
- MapReduce can process large datasets in a distributed manner, making it more efficient for big data processing than RDBMS
Data Processing
- MapReduce is designed for batch processing large datasets, whereas RDBMS is designed for transactional processing
False Statement
- MapReduce is suitable for real-time data processing (FALSE: MapReduce is designed for batch processing)
Local Aggregation
- Local aggregation in MapReduce reduces the amount of data transferred between nodes, making it faster and more efficient
Inefficient Use of MapReduce
- Processing a small, structured dataset (e.g., 1 million employee records) would not benefit much from using MapReduce, as RDBMS would be more suitable for such a task
How MapReduce Works
- MapReduce does not use a master node to coordinate the entire process (FALSE: a master node, called the JobTracker, coordinates the entire process)
Test your knowledge about the benefits of using MapReduce compared to RDBMS with this quiz. Choose the correct option and learn about how MapReduce differs from RDBMS in handling data.
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