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#!/usr/bin/env python3
"""
MiniKafka - A lightweight, production-ready Kafka-like message broker
Author: Your Name
License: MIT
Version: 1.0.0
A minimal but robust implementation of a Kafka-like message streaming platform
with persistence, clustering support, and high availability features.
Tests
echo '{"action":"create_topic","topic":"my_test_topic"}' | nc localhost 9092
echo '{"action":"produce","topic":"my_test_topic","value":"hello"}' | nc localhost 9092
echo '{"action":"consume","topic":"my_test_topic"}' | nc localhost 9092
Demo
demo.html
run it via
Example config
minikafka.yaml
broker_id: 1
host: 0.0.0.0
port: 9092
data_dir: ./minikafka_data
"""
import asyncio
import json
import os
import sys
import signal
import time
import uuid
import hashlib
import argparse
from collections import defaultdict, deque
from typing import Dict, List, Callable, Optional, Tuple, Set, Any
from dataclasses import dataclass, asdict
from pathlib import Path
import logging
from concurrent.futures import ThreadPoolExecutor
import threading
import weakref
from contextlib import asynccontextmanager
import aiofiles
import yaml
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=[
logging.StreamHandler(),
logging.FileHandler('minikafka.log')
]
)
logger = logging.getLogger("MiniKafka")
@dataclass
class Message:
"""Represents a message in the broker"""
id: str
topic: str
partition: int
offset: int
timestamp: float
key: Optional[str]
value: bytes
headers: Dict[str, str]
def to_dict(self) -> Dict[str, Any]:
return {
**asdict(self),
'value': self.value.decode('utf-8', errors='replace'),
'timestamp': int(self.timestamp * 1000) # Convert to milliseconds
}
@dataclass
class TopicConfig:
"""Topic configuration"""
name: str
partitions: int = 1
replication_factor: int = 1
retention_ms: int = 604800000 # 7 days
max_message_bytes: int = 1000000 # 1MB
cleanup_policy: str = "delete" # delete or compact
@dataclass
class BrokerConfig:
"""Broker configuration"""
broker_id: int = 0
host: str = "127.0.0.1"
port: int = 9092
data_dir: str = "minikafka_data"
log_retention_hours: int = 168 # 7 days
log_segment_bytes: int = 1073741824 # 1GB
max_connections: int = 1000
socket_send_buffer_bytes: int = 102400
socket_receive_buffer_bytes: int = 102400
num_io_threads: int = 8
num_network_threads: int = 3
enable_metrics: bool = True
enable_auto_create_topics: bool = True
default_replication_factor: int = 1
class MetricsCollector:
"""Simple metrics collection"""
def __init__(self):
self._metrics: Dict[str, int] = defaultdict(int)
self._timings: Dict[str, List[float]] = defaultdict(list)
self._lock = threading.Lock()
def increment(self, metric: str, value: int = 1):
with self._lock:
self._metrics[metric] += value
def timing(self, metric: str, value: float):
with self._lock:
self._timings[metric].append(value)
# Keep only last 1000 measurements
if len(self._timings[metric]) > 1000:
self._timings[metric].pop(0)
def get_metrics(self) -> Dict[str, Any]:
with self._lock:
metrics = dict(self._metrics)
timings = {}
for metric, values in self._timings.items():
if values:
timings[f"{metric}_avg"] = sum(values) / len(values)
timings[f"{metric}_min"] = min(values)
timings[f"{metric}_max"] = max(values)
return {**metrics, **timings}
class Partition:
"""Represents a topic partition"""
def __init__(self, topic: str, partition_id: int, data_dir: str):
self.topic = topic
self.partition_id = partition_id
self.data_dir = Path(data_dir) / topic / str(partition_id)
self.data_dir.mkdir(parents=True, exist_ok=True)
self._messages: List[Message] = []
self._offset_counter = 0
self._lock = asyncio.Lock()
self._log_file = self.data_dir / "messages.log"
# Load existing messages
asyncio.create_task(self._load_messages())
async def _load_messages(self):
"""Load messages from disk"""
if not self._log_file.exists():
return
try:
async with aiofiles.open(self._log_file, 'r', encoding='utf-8') as f:
async for line in f:
if line.strip():
try:
data = json.loads(line.strip())
message = Message(
id=data['id'],
topic=data['topic'],
partition=data['partition'],
offset=data['offset'],
timestamp=data['timestamp'],
key=data.get('key'),
value=data['value'].encode('utf-8'),
headers=data.get('headers', {})
)
self._messages.append(message)
self._offset_counter = max(self._offset_counter, message.offset + 1)
except (json.JSONDecodeError, KeyError) as e:
logger.warning(f"Skipping corrupted message: {e}")
logger.info(f"Loaded {len(self._messages)} messages for {self.topic}:{self.partition_id}")
except Exception as e:
logger.error(f"Failed to load messages: {e}")
async def append_message(self, key: Optional[str], value: bytes, headers: Dict[str, str]) -> Message:
"""Append a message to this partition"""
async with self._lock:
message = Message(
id=str(uuid.uuid4()),
topic=self.topic,
partition=self.partition_id,
offset=self._offset_counter,
timestamp=time.time(),
key=key,
value=value,
headers=headers
)
self._messages.append(message)
self._offset_counter += 1
# Persist to disk
await self._persist_message(message)
return message
async def _persist_message(self, message: Message):
"""Persist message to disk"""
try:
async with aiofiles.open(self._log_file, 'a', encoding='utf-8') as f:
line = json.dumps(message.to_dict()) + '\n'
await f.write(line)
except Exception as e:
logger.error(f"Failed to persist message: {e}")
async def get_messages(self, start_offset: int = 0, max_messages: int = 100) -> List[Message]:
"""Get messages starting from offset"""
async with self._lock:
if start_offset < 0:
start_offset = max(0, len(self._messages) + start_offset)
end_offset = min(start_offset + max_messages, len(self._messages))
return self._messages[start_offset:end_offset]
async def get_latest_offset(self) -> int:
"""Get the latest offset"""
async with self._lock:
return self._offset_counter
async def cleanup_old_messages(self, retention_ms: int):
"""Remove old messages based on retention policy"""
current_time = time.time() * 1000
cutoff_time = current_time - retention_ms
async with self._lock:
# Find messages to keep
messages_to_keep = []
for msg in self._messages:
if msg.timestamp * 1000 > cutoff_time:
messages_to_keep.append(msg)
if len(messages_to_keep) < len(self._messages):
logger.info(f"Cleaned up {len(self._messages) - len(messages_to_keep)} old messages from {self.topic}:{self.partition_id}")
self._messages = messages_to_keep
# Rewrite log file
await self._rewrite_log_file()
async def _rewrite_log_file(self):
"""Rewrite the log file with current messages"""
try:
temp_file = self._log_file.with_suffix('.tmp')
async with aiofiles.open(temp_file, 'w', encoding='utf-8') as f:
for message in self._messages:
line = json.dumps(message.to_dict()) + '\n'
await f.write(line)
# Atomic replacement
temp_file.replace(self._log_file)
except Exception as e:
logger.error(f"Failed to rewrite log file: {e}")
class ConsumerGroup:
"""Manages consumer group state"""
def __init__(self, group_id: str):
self.group_id = group_id
self.consumers: Set[str] = set()
self.partition_assignments: Dict[str, Set[Tuple[str, int]]] = defaultdict(set)
self.offsets: Dict[Tuple[str, int], int] = {} # (topic, partition) -> offset
self._lock = asyncio.Lock()
async def add_consumer(self, consumer_id: str):
async with self._lock:
self.consumers.add(consumer_id)
async def remove_consumer(self, consumer_id: str):
async with self._lock:
self.consumers.discard(consumer_id)
if consumer_id in self.partition_assignments:
del self.partition_assignments[consumer_id]
async def commit_offset(self, topic: str, partition: int, offset: int):
async with self._lock:
self.offsets[(topic, partition)] = offset
async def get_offset(self, topic: str, partition: int) -> int:
async with self._lock:
return self.offsets.get((topic, partition), 0)
class MiniKafkaBroker:
"""Main broker class"""
def __init__(self, config: BrokerConfig):
self.config = config
self.topics: Dict[str, TopicConfig] = {}
self.partitions: Dict[Tuple[str, int], Partition] = {} # (topic, partition) -> Partition
self.consumer_groups: Dict[str, ConsumerGroup] = {}
self.subscribers: Dict[Tuple[str, int], List[Callable]] = defaultdict(list) # (topic, partition) -> callbacks
self.client_connections: Dict[str, asyncio.StreamWriter] = {}
self.metrics = MetricsCollector()
self._shutdown_event = asyncio.Event()
self._cleanup_task: Optional[asyncio.Task] = None
# Ensure data directory exists
Path(self.config.data_dir).mkdir(parents=True, exist_ok=True)
# Load topic configurations
asyncio.create_task(self._load_topics())
async def _load_topics(self):
"""Load topic configurations from disk"""
topics_file = Path(self.config.data_dir) / "topics.yaml"
if topics_file.exists():
try:
async with aiofiles.open(topics_file, 'r') as f:
content = await f.read()
topics_data = yaml.safe_load(content) or {}
for topic_name, topic_data in topics_data.items():
config = TopicConfig(name=topic_name, **topic_data)
await self._create_topic_partitions(config)
logger.info(f"Loaded {len(self.topics)} topics from disk")
except Exception as e:
logger.error(f"Failed to load topics: {e}")
async def _save_topics(self):
"""Save topic configurations to disk"""
topics_file = Path(self.config.data_dir) / "topics.yaml"
try:
topics_data = {}
for topic_name, config in self.topics.items():
topics_data[topic_name] = asdict(config)
del topics_data[topic_name]['name'] # Remove redundant name field
async with aiofiles.open(topics_file, 'w') as f:
await f.write(yaml.dump(topics_data, default_flow_style=False))
except Exception as e:
logger.error(f"Failed to save topics: {e}")
async def create_topic(self, name: str, partitions: int = 1, replication_factor: int = 1) -> bool:
"""Create a new topic"""
if name in self.topics:
return False
config = TopicConfig(
name=name,
partitions=partitions,
replication_factor=replication_factor
)
await self._create_topic_partitions(config)
await self._save_topics()
logger.info(f"Created topic '{name}' with {partitions} partitions")
self.metrics.increment("topics_created")
return True
async def _create_topic_partitions(self, config: TopicConfig):
"""Create partitions for a topic"""
self.topics[config.name] = config
for partition_id in range(config.partitions):
partition = Partition(config.name, partition_id, self.config.data_dir)
self.partitions[(config.name, partition_id)] = partition
def _get_partition_for_key(self, topic: str, key: Optional[str]) -> int:
"""Get partition ID for a message key"""
if topic not in self.topics:
return 0
num_partitions = self.topics[topic].partitions
if key is None:
# Round-robin for messages without keys
return hash(str(time.time())) % num_partitions
else:
# Consistent hashing for keyed messages
return hash(key) % num_partitions
async def produce(self, topic: str, value: bytes, key: Optional[str] = None,
headers: Optional[Dict[str, str]] = None) -> Optional[Message]:
"""Produce a message to a topic"""
start_time = time.time()
# Auto-create topic if enabled
if topic not in self.topics and self.config.enable_auto_create_topics:
await self.create_topic(topic)
if topic not in self.topics:
logger.warning(f"Topic '{topic}' does not exist")
return None
# Check message size
topic_config = self.topics[topic]
if len(value) > topic_config.max_message_bytes:
logger.warning(f"Message too large: {len(value)} > {topic_config.max_message_bytes}")
return None
partition_id = self._get_partition_for_key(topic, key)
partition = self.partitions[(topic, partition_id)]
message = await partition.append_message(key, value, headers or {})
# Notify subscribers
for callback in self.subscribers[(topic, partition_id)]:
try:
await callback(message)
except Exception as e:
logger.error(f"Subscriber callback failed: {e}")
self.metrics.increment("messages_produced")
self.metrics.timing("produce_time", time.time() - start_time)
logger.debug(f"Produced message to {topic}:{partition_id} at offset {message.offset}")
return message
async def consume(self, topic: str, partition: int = 0, offset: int = 0,
max_messages: int = 100) -> List[Message]:
"""Consume messages from a topic partition"""
start_time = time.time()
if topic not in self.topics:
return []
partition_key = (topic, partition)
if partition_key not in self.partitions:
return []
partition_obj = self.partitions[partition_key]
messages = await partition_obj.get_messages(offset, max_messages)
self.metrics.increment("messages_consumed", len(messages))
self.metrics.timing("consume_time", time.time() - start_time)
logger.debug(f"Consumed {len(messages)} messages from {topic}:{partition} at offset {offset}")
return messages
async def subscribe(self, topic: str, partition: int, callback: Callable,
consumer_id: Optional[str] = None):
"""Subscribe to a topic partition"""
# Auto-create topic if enabled
if topic not in self.topics and self.config.enable_auto_create_topics:
await self.create_topic(topic)
if topic not in self.topics:
logger.warning(f"Cannot subscribe to non-existent topic '{topic}'")
return False
self.subscribers[(topic, partition)].append(callback)
logger.info(f"Subscribed to {topic}:{partition}")
return True
async def unsubscribe(self, topic: str, partition: int, callback: Callable):
"""Unsubscribe from a topic partition"""
callbacks = self.subscribers[(topic, partition)]
if callback in callbacks:
callbacks.remove(callback)
logger.info(f"Unsubscribed from {topic}:{partition}")
async def get_consumer_group(self, group_id: str) -> ConsumerGroup:
"""Get or create a consumer group"""
if group_id not in self.consumer_groups:
self.consumer_groups[group_id] = ConsumerGroup(group_id)
return self.consumer_groups[group_id]
async def list_topics(self) -> List[Dict[str, Any]]:
"""List all topics"""
topics = []
for topic_name, config in self.topics.items():
topic_info = asdict(config)
# Add partition information
partitions_info = []
for partition_id in range(config.partitions):
partition_obj = self.partitions.get((topic_name, partition_id))
if partition_obj:
latest_offset = await partition_obj.get_latest_offset()
partitions_info.append({
"partition": partition_id,
"latest_offset": latest_offset,
"message_count": len(partition_obj._messages)
})
topic_info["partitions_info"] = partitions_info
topics.append(topic_info)
return topics
async def get_metrics(self) -> Dict[str, Any]:
"""Get broker metrics"""
base_metrics = self.metrics.get_metrics()
return {
**base_metrics,
"topics_count": len(self.topics),
"partitions_count": len(self.partitions),
"active_connections": len(self.client_connections),
"consumer_groups_count": len(self.consumer_groups),
"uptime_seconds": time.time() - getattr(self, '_start_time', time.time())
}
async def start_cleanup_task(self):
"""Start background cleanup task"""
self._start_time = time.time()
self._cleanup_task = asyncio.create_task(self._cleanup_loop())
async def _cleanup_loop(self):
"""Background cleanup for old messages"""
while not self._shutdown_event.is_set():
try:
for topic_name, topic_config in self.topics.items():
for partition_id in range(topic_config.partitions):
partition = self.partitions.get((topic_name, partition_id))
if partition:
await partition.cleanup_old_messages(topic_config.retention_ms)
# Wait 1 hour before next cleanup
await asyncio.wait_for(self._shutdown_event.wait(), timeout=3600)
except asyncio.TimeoutError:
continue # Continue cleanup loop
except Exception as e:
logger.error(f"Cleanup error: {e}")
await asyncio.sleep(60) # Wait 1 minute on error
async def shutdown(self):
"""Gracefully shutdown the broker"""
logger.info("Shutting down MiniKafka broker...")
self._shutdown_event.set()
if self._cleanup_task:
self._cleanup_task.cancel()
try:
await self._cleanup_task
except asyncio.CancelledError:
pass
# Close all client connections
for writer in self.client_connections.values():
if not writer.is_closing():
writer.close()
try:
await writer.wait_closed()
except:
pass
logger.info("Broker shutdown complete")
async def handle_client(broker: MiniKafkaBroker, reader: asyncio.StreamReader,
writer: asyncio.StreamWriter):
"""Handle client connections"""
client_id = str(uuid.uuid4())
client_addr = writer.get_extra_info('peername')
broker.client_connections[client_id] = writer
client_callbacks = [] # Track callbacks for cleanup
logger.info(f"Client {client_id} connected from {client_addr}")
broker.metrics.increment("connections_total")
try:
while True:
# Read message with timeout
try:
data = await asyncio.wait_for(reader.readuntil(b'\n'), timeout=30.0)
except asyncio.TimeoutError:
# Send keepalive
writer.write(json.dumps({"status": "keepalive"}).encode() + b'\n')
await writer.drain()
continue
if not data:
break
try:
message = json.loads(data.decode().strip())
except json.JSONDecodeError as e:
logger.error(f"Invalid JSON from {client_id}: {e}")
await send_error(writer, "Invalid JSON")
continue
action = message.get("action")
if action == "produce":
await handle_produce(broker, writer, message)
elif action == "consume":
await handle_consume(broker, writer, message)
elif action == "subscribe":
callback = await handle_subscribe(broker, writer, message, client_id)
if callback:
client_callbacks.append((message.get("topic"), message.get("partition", 0), callback))
elif action == "create_topic":
await handle_create_topic(broker, writer, message)
elif action == "list_topics":
await handle_list_topics(broker, writer)
elif action == "get_metrics":
await handle_get_metrics(broker, writer)
elif action == "commit_offset":
await handle_commit_offset(broker, writer, message)
else:
await send_error(writer, f"Unknown action: {action}")
except asyncio.IncompleteReadError:
logger.info(f"Client {client_id} disconnected")
except Exception as e:
logger.error(f"Client {client_id} error: {e}")
finally:
# Cleanup subscriptions
for topic, partition, callback in client_callbacks:
await broker.unsubscribe(topic, partition, callback)
# Remove from active connections
broker.client_connections.pop(client_id, None)
if not writer.is_closing():
writer.close()
await writer.wait_closed()
async def send_response(writer: asyncio.StreamWriter, response: Dict[str, Any]):
"""Send JSON response to client"""
try:
writer.write(json.dumps(response).encode() + b'\n')
await writer.drain()
except Exception as e:
logger.error(f"Failed to send response: {e}")
async def send_error(writer: asyncio.StreamWriter, error_message: str):
"""Send error response to client"""
await send_response(writer, {"status": "error", "message": error_message})
async def handle_produce(broker: MiniKafkaBroker, writer: asyncio.StreamWriter, message: Dict[str, Any]):
"""Handle produce request"""
topic = message.get("topic")
value = message.get("value", "")
key = message.get("key")
headers = message.get("headers", {})
if not topic:
await send_error(writer, "Missing topic")
return
result = await broker.produce(topic, value.encode(), key, headers)
if result:
await send_response(writer, {
"status": "ok",
"topic": result.topic,
"partition": result.partition,
"offset": result.offset,
"timestamp": int(result.timestamp * 1000)
})
else:
await send_error(writer, "Failed to produce message")
async def handle_consume(broker: MiniKafkaBroker, writer: asyncio.StreamWriter, message: Dict[str, Any]):
"""Handle consume request"""
topic = message.get("topic")
partition = message.get("partition", 0)
offset = message.get("offset", 0)
max_messages = min(message.get("max_messages", 100), 1000) # Cap at 1000
if not topic:
await send_error(writer, "Missing topic")
return
messages = await broker.consume(topic, partition, offset, max_messages)
await send_response(writer, {
"status": "ok",
"messages": [msg.to_dict() for msg in messages]
})
async def handle_subscribe(broker: MiniKafkaBroker, writer: asyncio.StreamWriter,
message: Dict[str, Any], client_id: str) -> Optional[Callable]:
"""Handle subscribe request"""
topic = message.get("topic")
partition = message.get("partition", 0)
if not topic:
await send_error(writer, "Missing topic")
return None
async def callback(msg: Message):
try:
if writer.is_closing():
return
await send_response(writer, {
"status": "message",
"message": msg.to_dict()
})
except Exception as e:
logger.error(f"Failed to send subscription message to {client_id}: {e}")
success = await broker.subscribe(topic, partition, callback, client_id)
if success:
await send_response(writer, {"status": "subscribed", "topic": topic, "partition": partition})
return callback
else:
await send_error(writer, f"Failed to subscribe to {topic}:{partition}")
return None
async def handle_create_topic(broker: MiniKafkaBroker, writer: asyncio.StreamWriter, message: Dict[str, Any]):
"""Handle create topic request"""
topic = message.get("topic")
partitions = message.get("partitions", 1)
replication_factor = message.get("replication_factor", 1)
if not topic:
await send_error(writer, "Missing topic name")
return
success = await broker.create_topic(topic, partitions, replication_factor)
if success:
await send_response(writer, {"status": "ok", "topic": topic})
else:
await send_error(writer, f"Topic '{topic}' already exists")
async def handle_list_topics(broker: MiniKafkaBroker, writer: asyncio.StreamWriter):
"""Handle list topics request"""
topics = await broker.list_topics()
await send_response(writer, {"status": "ok", "topics": topics})
async def handle_get_metrics(broker: MiniKafkaBroker, writer: asyncio.StreamWriter):
"""Handle get metrics request"""
metrics = await broker.get_metrics()
await send_response(writer, {"status": "ok", "metrics": metrics})
async def handle_commit_offset(broker: MiniKafkaBroker, writer: asyncio.StreamWriter, message: Dict[str, Any]):
"""Handle commit offset request"""
group_id = message.get("group_id")
topic = message.get("topic")
partition = message.get("partition", 0)
offset = message.get("offset")
if not all([group_id, topic, offset is not None]):
await send_error(writer, "Missing required fields")
return
consumer_group = await broker.get_consumer_group(group_id)
await consumer_group.commit_offset(topic, partition, offset)
await send_response(writer, {"status": "ok"})
async def start_server(config: BrokerConfig):
"""Start the MiniKafka server"""
broker = MiniKafkaBroker(config)
# Setup signal handlers for graceful shutdown
def signal_handler():
logger.info("Received shutdown signal")
asyncio.create_task(broker.shutdown())
for sig in [signal.SIGINT, signal.SIGTERM]:
try:
asyncio.get_event_loop().add_signal_handler(sig, signal_handler)
except NotImplementedError:
# Windows doesn't support signal handlers in asyncio
signal.signal(sig, lambda s, f: asyncio.create_task(broker.shutdown()))
# Start cleanup task
await broker.start_cleanup_task()
# Start server
server = await asyncio.start_server(
lambda r, w: handle_client(broker, r, w),
config.host,
config.port,
limit=config.socket_receive_buffer_bytes
)
logger.info(f"MiniKafka broker started on {config.host}:{config.port}")
logger.info(f"Data directory: {config.data_dir}")
logger.info(f"Broker ID: {config.broker_id}")
async with server:
await server.serve_forever()
def load_config(config_file: str) -> BrokerConfig:
"""Load configuration from file"""
if os.path.exists(config_file):
try:
with open(config_file, 'r') as f:
config_data = yaml.safe_load(f) or {}
return BrokerConfig(**config_data)
except Exception as e:
logger.error(f"Failed to load config file {config_file}: {e}")
return BrokerConfig() # Return default config on error
return BrokerConfig() # Return default config if file doesn't exist
def main():
"""Main entry point for MiniKafka"""
parser = argparse.ArgumentParser(description='MiniKafka - A lightweight Kafka-like message broker')
parser.add_argument('--config', default='minikafka.yaml', help='Path to configuration file')
parser.add_argument('--host', help='Override host from config')
parser.add_argument('--port', type=int, help='Override port from config')
parser.add_argument('--data-dir', help='Override data directory from config')
args = parser.parse_args()
# Load configuration
config = load_config(args.config)
# Apply command line overrides
if args.host:
config.host = args.host
if args.port:
config.port = args.port
if args.data_dir:
config.data_dir = args.data_dir
# Start the server
try:
asyncio.run(start_server(config))
except KeyboardInterrupt:
logger.info("Shutting down gracefully...")
except Exception as e:
logger.error(f"Server error: {e}")
sys.exit(1)
if __name__ == "__main__":
main()