Design systems for processing large-scale data across multiple machines.
Tasks:
Implementation Strategy:
Design a system to find mode and median in a very large dataset using distributed computing.
Part 1: Mode Calculation
Input:
- Large dataset (size >> single machine memory)
- Array of available machines
- Each machine has limited memory
Requirements:
- Distribute workload efficiently
- Handle machine failures
- Minimize network communication
- Ensure accurate results
Approach:
1. Data Partitioning
2. Local Mode Calculation
3. Result Aggregation
4. Final Mode Selection
Part 2: Median Calculation (Follow-up)
Additional Challenges:
- Sorting distributed data
- Memory constraints
- Network bandwidth optimization
- Maintaining accuracy
Considerations:
- Approximate vs exact solutions
- Sampling techniques
- Parallel processing strategies
- Data skew handling
System Design Requirements: