# Data Pipeline

> ⚠️ This documentation is AI-generated and may contain errors.

Data processing pipeline showing how to process multiple batches in parallel.

## Script

See `/examples/data_pipeline.rsh` in the repository.

```rush
#!/usr/bin/env rush

DATASET = "user_analytics"
INPUT_DIR = "$HOME/data/raw"
OUTPUT_DIR = "$HOME/data/processed"
BATCH_SIZE = "1000"

echo "Data Processing Pipeline: $DATASET"

# Pre-processing stages
for stage in validate clean normalize {
    STAGE_UPPER = "$stage"
    echo "  Stage: $STAGE_UPPER"
}

# Process batches in parallel
BATCH_1_IN = "$INPUT_DIR/batch_001.csv"
BATCH_1_OUT = "$OUTPUT_DIR/batch_001.json"
# ... (define other batches)

parallel {
    run {
        echo "[batch_001] Processing $BATCH_1_IN -> $BATCH_1_OUT"
        echo "[batch_001] Transformed 1000 records"
    }
    
    run {
        echo "[batch_002] Processing $BATCH_2_IN -> $BATCH_2_OUT"
        echo "[batch_002] Transformed 1000 records"
    }
    # ... (more batches)
}

echo "All batches processed successfully"
```

## Key Concepts

- **Parallel data processing**: Process multiple batches simultaneously
- **Path construction**: Building input/output file paths
- **Pipeline stages**: Sequential setup, parallel processing, sequential summary