- 2070 Bhadra · 6 marks
MapReduce vs Hadoop
Short answer
MapReduce is a programming model for parallel processing; Hadoop is an open-source framework providing distributed storage (HDFS), resource management (YARN), and runs MapReduce jobs. Hadoop includes an implementation of MapReduce.
Differentiate between Mapreduce and Hadoop Systems.
MapReduce is a programming model for processing large datasets in parallel across a cluster. Hadoop is an open-source framework that provides distributed storage (HDFS) and resource management, and runs MapReduce jobs.
| Basis | MapReduce | Hadoop |
|---|---|---|
| Definition | Programming model/algorithm with map and reduce functions | Software framework for distributed storage and processing |
| Developed by | Google (paper in 2004) | Apache Software Foundation (Doug Cutting, inspired by Google papers) |
| Scope | Only the processing layer | Whole ecosystem: storage, processing, resource management |
| Main parts | Map, shuffle and sort, reduce | HDFS, YARN, MapReduce, Common utilities; plus Hive, Pig, HBase, Spark |
| Storage | None; uses an underlying file system (GFS or HDFS) | Has its own file system, HDFS |
| Language | Model is language independent | Mainly Java |
| Availability | Concept; Google's original is proprietary | Open source and free |
| Fault tolerance | Re-executes failed tasks | Replicates data blocks (default 3) and re-runs tasks |
| Relation | A component of Hadoop | Includes an implementation of MapReduce |
| Example | Word count job | A cluster where the word count job runs on data stored in HDFS |
✓ Answer checked by Claude Opus 5.5 (high effort)
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