配置 OpenClaw

OpenClaw 与 Kafka 集成主要有以下几种方法：

作为 Kafka 生产者

直接写入 Kafka

from confluent_kafka import Producer
import json
class OpenClawKafkaProducer:
    def __init__(self, bootstrap_servers):
        self.producer = Producer({
            'bootstrap.servers': bootstrap_servers,
            'client.id': 'openclaw-producer'
        })
    def delivery_report(self, err, msg):
        if err is not None:
            print(f'消息发送失败: {err}')
        else:
            print(f'消息发送到 {msg.topic()} [{msg.partition()}]')
    def send_data(self, topic, data):
        # 将爬取的数据发送到 Kafka
        self.producer.produce(
            topic=topic,
            value=json.dumps(data).encode('utf-8'),
            callback=self.delivery_report
        )
        self.producer.flush()

使用 Kafka 连接器

Kafka Connect 配置

{
  "name": "openclaw-source-connector",
  "config": {
    "connector.class": "io.openclaw.OpenClawSourceConnector",
    "tasks.max": "3",
    "topics": "web_data",
    "url.patterns": "https://example.com/*",
    "poll.interval.ms": "10000"
  }
}

集成方案示例

OpenClaw → Kafka → 处理系统

from openclaw import OpenClaw
from kafka import KafkaProducer
import asyncio
class KafkaPipeline:
    def __init__(self, kafka_config):
        self.producer = KafkaProducer(
            bootstrap_servers=kafka_config['servers'],
            value_serializer=lambda v: json.dumps(v).encode('utf-8')
        )
    async def process_item(self, item, spider):
        # 发送到不同的主题
        if item['type'] == 'product':
            self.producer.send('products', item)
        elif item['type'] == 'article':
            self.producer.send('articles', item)
        return item
claw = OpenClaw({
    'pipelines': [KafkaPipeline],
    'middlewares': [...]
})

分布式爬虫 + Kafka 队列

# 生产者：调度器
class KafkaScheduler:
    def __init__(self):
        self.producer = KafkaProducer(...)
        self.consumer = KafkaConsumer('url_todo', ...)
    def enqueue_request(self, request):
        self.producer.send('url_todo', {
            'url': request.url,
            'meta': request.meta
        })
    def next_request(self):
        message = self.consumer.poll(timeout_ms=1000)
        # 返回给爬虫节点
        return message
# 消费者：爬虫节点
class CrawlerNode:
    def __init__(self):
        self.consumer = KafkaConsumer('url_todo', ...)
        self.producer = KafkaProducer(...)
    async def run(self):
        for message in self.consumer:
            data = await self.crawl(message.value['url'])
            self.producer.send('crawled_data', data)

配置文件示例

config.yaml

kafka:
  bootstrap_servers: "localhost:9092,localhost:9093"
  topics:
    urls: "crawl_urls"
    data: "crawled_data"
    errors: "crawl_errors"
  security:
    ssl_enabled: true
    sasl_mechanism: "PLAIN"
    username: "user"
    password: "pass"
openclaw:
  concurrent_requests: 16
  download_delay: 1
  pipelines:
    - "openclaw.pipelines.KafkaPipeline"
  spider_configs:
    - name: "product_spider"
      start_urls: []
      kafka_topic: "products"

Docker 部署

docker-compose.yml

version: '3'
services:
  zookeeper:
    image: confluentinc/cp-zookeeper:latest
    environment:
      ZOOKEEPER_CLIENT_PORT: 2181
  kafka:
    image: confluentinc/cp-kafka:latest
    depends_on:
      - zookeeper
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://kafka:9092
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
  openclaw:
    build: .
    depends_on:
      - kafka
    environment:
      KAFKA_BOOTSTRAP_SERVERS: kafka:9092
      KAFKA_TOPIC_PREFIX: "crawl_"
    volumes:
      - ./spiders:/app/spiders

监控和运维

监控指标

from prometheus_client import Counter, Histogram
class Metrics:
    kafka_messages_sent = Counter(
        'openclaw_kafka_messages_sent_total',
        'Total messages sent to Kafka'
    )
    kafka_send_duration = Histogram(
        'openclaw_kafka_send_duration_seconds',
        'Kafka send duration'
    )

错误处理和重试

from kafka import KafkaProducer
from kafka.errors import KafkaError
from tenacity import retry, stop_after_attempt, wait_exponential
class ResilientKafkaProducer:
    @retry(
        stop=stop_after_attempt(5),
        wait=wait_exponential(multiplier=1, min=4, max=10)
    )
    def send_with_retry(self, topic, data):
        future = self.producer.send(topic, data)
        try:
            future.get(timeout=10)
        except KafkaError as e:
            logger.error(f"Kafka发送失败: {e}")
            raise

最佳实践建议

1. 主题设计

   topics = {
       'raw_urls': 'crawl.urls.raw',
       'validated_urls': 'crawl.urls.validated',
       'html_content': 'crawl.content.html',
       'parsed_data': 'crawl.data.parsed',
       'errors': 'crawl.errors'
   }

2. 序列化格式

   • 使用 Avro 或 Protobuf 进行序列化
   • 包含 schema 版本信息

3. 分区策略

   # 根据域名分区，确保同一域名的请求在同一分区
   def partition_key(url):
       domain = urlparse(url).netloc
       return hash(domain) % num_partitions

4. 配置管理

   # 使用环境变量
   KAFKA_CONFIG = {
       'bootstrap.servers': os.getenv('KAFKA_BOOTSTRAP_SERVERS'),
       'security.protocol': os.getenv('KAFKA_SECURITY_PROTOCOL', 'PLAINTEXT'),
       'group.id': f"openclaw-{os.getenv('HOSTNAME', 'unknown')}"
   }

这种集成方式可以实现高吞吐量的数据采集和实时数据处理,特别适合大规模分布式爬虫系统。

标签： OpenClaw 配置