# Preventing Overheating When Using Pathway Library in
##
Experiencing laptop shutdowns during Pathway library execution in VS Code due to overheating caused by uncontrolled resource consumption during data processing pipelines.
## Root
- Pathway's default execution settings aggressively utilize all available CPU
- Memory-intensive operations exceed local machine
- Lack of resource constraints leads to thermal
- Continuous computation without backpressure overwhelms
## Why This Happens in Real
- Local dev environments lack production-grade
- Resource-hungry frameworks prioritize throughput over safety by
- Complex data transformations amplify processing demands
- Absence of throttling mechanisms during
## Real-World
| Severity | Consequence |
|----------|---------------------------------|
| Critical | Hardware damage & data loss |
| High | Reduced device lifespan |
| Medium | Disrupted development workflow |
| Low | Repeated task failures |
## Example orimport pathway as
Overheating trigger
table = pw.debug.table_from_markdown(“””
|
1 | generate_large_json() # Memory-intensive
2 | generate_large_json()
3 | generate_large_json()
“””)
Chain transforms creates cumulative
result = (
.select(data=apply_complex_transformation(pw.this.data))
.groupby(pw.this.data)
.reduce(aggregate_field=pw.reducers.count())
)
## How Senior Engineers Fix
1. **Resource Constraints**pw.run(max_workers=2, monitoring_level=pw.MonitoringLevel.NONE)
2. **Batch Processing**table = pw.io.csv.read(
“./large_file.csv”,
mode=”streaming”,
autocommit_duration_ms=5000 # Throttle
)
3. **Monitoring Integration**with pw.monitoring.Monitor() as monitor:
pw.run(monitor=monitor)
4. **Selective Optimization**
- Use `pw.this` instead of `pw.apply()` for column
- Disable debug features in production
## Why Juniors Miss
- Focus on functional correctness over resource
- Assumption frameworks auto-manage hardware
- Lack exposure to thermal management
- Underestimation of transformation operation
- Debugging workflow prioritizes logs over system