Stream Factory Sensor Events to Delta Lake with Apache Kafka and delta-rs

                      
                     
"""
Production implementation for streaming factory sensor events to Delta Lake using Apache Kafka and delta-rs.
This architecture enables real-time data processing and analytics.
"""
import os
import logging
import json
import asyncio
from typing import Dict, Any, List
from aiokafka import AIOKafkaConsumer, AIOKafkaProducer
from delta import DeltaTable

# Setup logger for monitoring events
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class to manage environment variables.
    """
    kafka_bootstrap_servers: str = os.getenv('KAFKA_BOOTSTRAP_SERVERS', 'localhost:9092')
    delta_table_path: str = os.getenv('DELTA_TABLE_PATH', '/mnt/delta/sensor_events')
    kafka_topic: str = os.getenv('KAFKA_TOPIC', 'sensor_events')

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate sensor data input.
    
    Args:
        data: Input data from sensor
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'sensor_id' not in data or 'value' not in data:
        raise ValueError('Input data must include sensor_id and value')
    return True

async def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input data fields.
    
    Args:
        data: Raw input data
    Returns:
        Sanitized data
    """
    # Example sanitization (e.g., strip whitespace)
    data['sensor_id'] = data['sensor_id'].strip()
    return data

async def transform_records(data: Dict[str, Any]) -> Dict[str, Any]:
    """Transform raw sensor data into a suitable format for Delta Lake.
    
    Args:
        data: Raw sensor data
    Returns:
        Transformed data ready for insertion
    """
    # Transform data as needed (e.g., convert types)
    data['timestamp'] = data.get('timestamp', 'now')
    return data

async def process_batch(records: List[Dict[str, Any]]) -> None:
    """Process a batch of records and save them to Delta Lake.
    
    Args:
        records: List of transformed sensor records
    """
    delta_table = DeltaTable.for_path(Config.delta_table_path)
    # Simulating batch processing
    for record in records:
        logger.info(f'Saving record: {record}')
        await delta_table.append(record)

async def fetch_data(consumer: AIOKafkaConsumer) -> None:
    """Fetch data from Kafka topic and process it.
    
    Args:
        consumer: Kafka consumer instance
    """
    async for message in consumer:
        data = json.loads(message.value)
        try:
            await validate_input(data)
            data = await sanitize_fields(data)
            data = await transform_records(data)
            await process_batch([data])
        except ValueError as e:
            logger.error(f'Validation error: {e}')
        except Exception as e:
            logger.error(f'Processing error: {e}')

async def save_to_db(data: Dict[str, Any]) -> None:
    """Simulate saving data to a database.
    
    Args:
        data: Data to save
    """
    # Implementation for saving to a DB (skipped for brevity)
    logger.info(f'Data saved: {data}')

async def handle_errors(e: Exception) -> None:
    """Handle errors gracefully.
    
    Args:
        e: Exception to handle
    """
    logger.error(f'An error occurred: {e}')

class SensorEventStream:
    """Main orchestrator for streaming sensor events from Kafka to Delta Lake.
    """
    def __init__(self):
        self.consumer = AIOKafkaConsumer(
            Config.kafka_topic,
            bootstrap_servers=Config.kafka_bootstrap_servers,
            group_id='sensor_group'
        )
        self.producer = AIOKafkaProducer(bootstrap_servers=Config.kafka_bootstrap_servers)

    async def start(self) -> None:
        """Start the consumer and producer.
        """
        await self.consumer.start()
        await self.producer.start()
        try:
            await fetch_data(self.consumer)
        finally:
            await self.consumer.stop()
            await self.producer.stop()

if __name__ == '__main__':
    # Entry point for running the application
    loop = asyncio.get_event_loop()
    stream = SensorEventStream()
    try:
        loop.run_until_complete(stream.start())
    except KeyboardInterrupt:
        logger.info('Shutting down...')
    finally:
        loop.close()