MapReduce
A software framework for processing large datasets in parallel across clusters, enabling reliable and fault-tolerant data processing.
Score
30
User Rating
3.0
Free/Trial Support
Supported
Starting Price
--
Last Updated
Jun 11, 2026
Overview
What is MapReduce?
Hadoop MapReduce is a framework for writing applications that process vast amounts of data in parallel on large clusters of commodity hardware, handling tasks like scheduling, monitoring, and fault tolerance.
What is MapReduce used for?
Top Features
- Parallel data processing
- Fault tolerance
- Scalability to thousands of nodes
- Support for multiple languages
- Integration with HDFS
How to use MapReduce?
Install Hadoop, write MapReduce jobs in Java or other languages via Hadoop Streaming, configure input/output paths, and submit jobs to the JobTracker for execution on a cluster.
Alternative Tools
No alternative tools found
Pros & Cons
Pros
- Handles multi-terabyte datasets
- High reliability
- Flexible with various data types
- Open-source and free
Cons
- Complex setup and configuration
- Steep learning curve
- Requires cluster management
Use Cases
- Log analysis
- Data mining
- Large-scale text processing
- Scientific computations
MapReduce Pricing
Free Plan
No detailed pricing information available
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