Instructions

Learn how to use the MapReduce Distributed Sort Simulator

Interactive Controls

  • Configure Parameters: Set number of mappers (2-6), reducers (≤ mappers+1), and partition strategy.
  • Load Data: Initialize simulation with your input data (comma-separated numbers).
  • Step Through: Use "Next Step" to progress through each MapReduce phase individually.
  • Auto Run: Automatic progression through all phases with visual feedback.
  • Pause/Reset: Control simulation flow and restart with different parameters.

Simulation Metrics

  • Data Distribution: Visual representation of how data is distributed across mappers.
  • Processing Progress: Real-time tracking of sort operations and data movement.
  • Performance Statistics: Monitor successful sorts, elements processed, and communication rounds.

MapReduce Phases

  • Map Phase: Input data distributed across mapper nodes for parallel processing.
  • Shuffle Phase: Data reorganized and grouped by partition keys (Hash/Range).
  • Reduce Phase: Each reducer independently sorts its assigned data partition.
  • Final Merge: Sorted partitions combined into final sorted output.

Learning Objectives

  • Understand distributed sorting principles and MapReduce framework benefits.
  • Compare Hash vs Range partitioning strategies for data distribution.
  • Observe parallel processing impact on sorting large datasets efficiently.
  • Analyze the relationship between mappers, reducers, and overall performance.

Configuration & Controls

Step: 0
Maximum: Mappers + 1 (currently 4)

MapReduce Visualization

Input Data

Map Phase - Data Distribution

Shuffle & Sort Phase

Shuffle and sort in progress...

Reduce Phase - Final Sorting

Final Sorted Output

Logs and Statistics

Logs

[System] Distributed Sort MapReduce initialized
[Info] Configure parameters and click 'Load Data' to begin

Experiment Statistics

0
Successful Sorts
Completed experiments
0
Elements Processed
Total data items sorted
0
Avg Comm. Rounds
Average per experiment
0
Total Experiments
All runs completed