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IA⚙️ Parallel File Processing in Java — When to Use What
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🧵 1️⃣ Thread Pool (Executor-Based)
✅ Use When:
• Many independent files
• Moderate concurrency required
• Java 8–17 environment
• Need controlled, predictable resource usage
• Mixed I/O + CPU workload
🎯 Best For:
General-purpose production systems.
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⚡ 2️⃣ Virtual Threads (Java 21+)
✅ Use When:
• Workload is mostly I/O-bound
• High number of concurrent files
• File + DB/network operations
• Want simple scaling without tuning
🎯 Best For:
Modern systems with high concurrency needs.
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🧮 3️⃣ Fork-Join / CPU-Optimized Pool
✅ Use When:
• Parsing is CPU-heavy
• Heavy regex, JSON transformation
• Large computation per file
• Minimal blocking I/O
🎯 Best For:
Compute-intensive log analysis.
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📦 4️⃣ File-Level Parallelism
✅ Use When:
• Many independent files
• File sizes vary
• Simple architecture preferred
🎯 Default starting strategy.
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🪓 5️⃣ Chunk-Level Parallelism
✅ Use When:
• Few but very large files (1–2GB)
• Per-file processing is slow
• Need maximum CPU utilization
⚠ Avoid When:
• Files are small
• Implementation complexity not justified
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🧱 6️⃣ Producer–Consumer Architecture
✅ Use When:
• Processing speed ≠ ingestion speed
• Need backpressure control
• Database writes require batching
• Enterprise-scale ingestion system
🎯 Best For:
Stable, controlled high-throughput systems.
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🌍 7️⃣ Distributed Processing
✅ Use When:
• Single machine CPU/disk saturated
• TB-scale daily logs
• Horizontal scaling required
• High availability needed
🎯 Best For:
Large enterprise or cloud-scale pipelines.
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