Map-Reduce is a programming model used for processing and generating large data sets with a parallel, distributed algorithm on a cluster. It simplifies data processing by dividing the task into two distinct phases: 'Map', which processes and filters data, and 'Reduce', which aggregates the results.

Map-Reduce

Programming Model

Processing large data sets

Generating large data sets

Parallel algorithm

Distributed algorithm

A cluster is a group of similar data points or objects that are grouped together based on specific characteristics or metrics, often used in data analysis to identify patterns or structures within a dataset. Clustering helps in simplifying complex data sets by organizing them into meaningful subgroups, making it easier to analyze and interpret data trends and relationships.

Cluster

Data processing involves the collection, transformation, and organization of data to extract meaningful insights and facilitate decision-making. It encompasses a range of activities, from data cleaning and integration to analysis and visualization, ensuring data is accurate, accessible, and actionable.

Concepts

Relevant Degrees

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