Overview
MapReduce is a powerful programming model designed for processing large data sets across distributed systems. It breaks down tasks into smaller, manageable pieces that can be processed in parallel, making it highly efficient for big data applications. The model consists of two main functions: Map, w...
Key Terms
Example: In a word count program, the map function outputs each word as a key with a count of 1.
Example: In a word count program, the reduce function sums the counts for each word.
Example: In a dictionary, 'apple' is a key and 'fruit' is its value.
Example: Using multiple servers to process data simultaneously.
Example: A Hadoop cluster used for big data processing.
Example: The job tracker assigns tasks to different nodes in a cluster.
Related Topics
Hadoop
A framework that allows for distributed storage and processing of large data sets using MapReduce.
intermediateSpark
An open-source data processing engine that can perform in-memory computations, often faster than MapReduce.
advancedBig Data
A term that describes large volumes of data that can be analyzed for insights.
intermediateKey Concepts
Map functionReduce functionDistributed computingData processing