Detect Machine Downtime Events in Streaming IIoT Data with Apache Flink and delta-rs

"""
Production implementation for detecting machine downtime events in streaming IIoT data using Apache Flink and delta-rs.
Provides secure, scalable operations for real-time data processing.
"""

from typing import Dict, Any, List, Tuple
import os
import logging
import time
import json
import requests
from delta import DeltaTable
from apache_flink import StreamExecutionEnvironment
from apache_flink.datastream import DataStream

# Logger setup for the application
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class for environment variables.
    """
    database_url: str = os.getenv('DATABASE_URL')
    delta_table_path: str = os.getenv('DELTA_TABLE_PATH')

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate request data for machine events.
    
    Args:
        data: Input data to validate.
    Returns:
        True if valid.
    Raises:
        ValueError: If validation fails.
    """
    if 'machine_id' not in data:
        raise ValueError('Missing machine_id')
    if 'timestamp' not in data:
        raise ValueError('Missing timestamp')
    return True

async def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input data fields.
    
    Args:
        data: Input data to sanitize.
    Returns:
        Sanitized data.
    """
    # Sanitize fields by removing leading/trailing whitespace
    return {k: v.strip() if isinstance(v, str) else v for k, v in data.items()}

async def normalize_data(data: Dict[str, Any]) -> Dict[str, Any]:
    """Normalize the input data for processing.
    
    Args:
        data: Input data to normalize.
    Returns:
        Normalized data.
    """
    return {
        'machine_id': data['machine_id'],
        'timestamp': data['timestamp'],
        'status': data.get('status', 'unknown')
    }

async def transform_records(data_list: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform multiple records for downstream processing.
    
    Args:
        data_list: List of records to transform.
    Returns:
        Transformed list of records.
    """
    return [await normalize_data(data) for data in data_list]

async def process_batch(data_stream: DataStream) -> None:
    """Process a batch of data from the stream.
    
    Args:
        data_stream: The DataStream to process.
    """
    event_list = []
    async for event in data_stream:
        await validate_input(event)
        sanitized_event = await sanitize_fields(event)
        event_list.append(sanitized_event)
    transformed_events = await transform_records(event_list)
    await save_to_db(transformed_events)

async def save_to_db(events: List[Dict[str, Any]]) -> None:
    """Save processed events to the database using Delta Lake.
    
    Args:
        events: List of events to save.
    """
    delta_table = DeltaTable.for_path(Config.delta_table_path)
    for event in events:
        delta_table.insert(event)
    logger.info('Saved %d events to the database.', len(events))

async def call_api(url: str, payload: Dict[str, Any]) -> None:
    """Call an external API with the given payload.
    
    Args:
        url: API endpoint.
        payload: Data to send in the request.
    """
    response = requests.post(url, json=payload)
    if response.status_code != 200:
        logger.error('API call failed: %s', response.text)

async def handle_errors(error: Exception) -> None:
    """Handle errors and log them appropriately.
    
    Args:
        error: The exception to handle.
    """
    logger.error('Error occurred: %s', str(error))

class MachineDowntimeDetector:
    """Main class for orchestrating the downtime detection process.
    """
    def __init__(self, env: StreamExecutionEnvironment):
        self.env = env
        self.data_stream = self.env.socket_text_stream('localhost', 9999)

    async def run(self) -> None:
        try:
            await process_batch(self.data_stream)
        except Exception as e:
            await handle_errors(e)

if __name__ == '__main__':
    env = StreamExecutionEnvironment.get_execution_environment()
    detector = MachineDowntimeDetector(env)
    env.execute(detector.run())