MapReduce is best described as which of the following?

MapReduce is best described as which of the following?

• A. A Database Query Language
• B. A Data Visualization Tool
• C. A Computation Framework for Dealing with Big Data
• D. A Data Governance Policy

Answer: (C)

MapReduce is a framework for processing very large data sets by distributing the work across many machines. It uses two main stages: map, which processes input and emits key-value pairs, and reduce, which aggregates the results for each key. This design lets computations run in parallel and handle machine failures, making it practical for massive data volumes typical in big data environments. It’s best described as a computation framework for dealing with big data because it focuses on how to compute results from large-scale data, not on querying data, visualizing it, or enforcing data policies. It’s not a database query language, since it requires writing procedures in code rather than issuing declarative queries. It’s not a data visualization tool, as its purpose isn’t to present data visually. And it’s not a data governance policy, which would define rules about data access and quality. For example, counting word frequencies in a huge text collection uses map to emit (word, 1) pairs and reduce to sum counts per word.

MapReduce is a framework for processing very large data sets by distributing the work across many machines. It uses two main stages: map, which processes input and emits key-value pairs, and reduce, which aggregates the results for each key. This design lets computations run in parallel and handle machine failures, making it practical for massive data volumes typical in big data environments. It’s best described as a computation framework for dealing with big data because it focuses on how to compute results from large-scale data, not on querying data, visualizing it, or enforcing data policies. It’s not a database query language, since it requires writing procedures in code rather than issuing declarative queries. It’s not a data visualization tool, as its purpose isn’t to present data visually. And it’s not a data governance policy, which would define rules about data access and quality. For example, counting word frequencies in a huge text collection uses map to emit (word, 1) pairs and reduce to sum counts per word.