Scrapy-Cluster结合Spiderkeeper管理分布式爬虫

摘要：分布式爬虫，分发网址是基于地址。注意要使用管理同一个集群，爬虫项目名称须一致，同时集群中配置相同任务浏览器访问启动爬虫时即可看见两个集群配置，启动同名爬虫开始分布式爬虫启动分布式爬虫后状态

基于Scrapy-cluster库的kafka-monitor可以实现分布式爬虫

Scrapyd+Spiderkeeper实现爬虫的可视化管理

# cat /etc/redhat-release 
CentOS Linux release 7.4.1708 (Core) 
# python -V
Python 2.7.5
# java -version
openjdk version "1.8.0_181"
OpenJDK Runtime Environment (build 1.8.0_181-b13)
OpenJDK 64-Bit Server VM (build 25.181-b13, mixed mode)

下载并配置

# wget http://mirror.bit.edu.cn/apache/zookeeper/zookeeper-3.4.13/zookeeper-3.4.13.tar.gz
# tar -zxvf zookeeper-3.4.13.tar.gz
# cd zookeeper-3.4.13/conf
# cp zoo_sample.cfg zoo.cfg
# cd ..
# PATH=/opt/zookeeper-3.4.13/bin:$PATH
# echo "export PATH=/opt/zookeeper-3.4.13/bin:$PATH" > /etc/profile.d/zoo.sh

单节点启动

# zkServer.sh status
ZooKeeper JMX enabled by default
Using config: /opt/zookeeper-3.4.13/bin/../conf/zoo.cfg
Error contacting service. It is probably not running.

# zkServer.sh start

下载

# wget http://mirrors.hust.edu.cn/apache/kafka/2.0.0/kafka_2.12-2.0.0.tgz
# tar -zxvf kafka_2.12-2.0.0.tgz
# cd kafka_2.12-2.0.0/

配置

# vim config/server.properties

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0                     # kafka的机器编号，
host.name = 168.*.*.119         # 绑定ip
port=9092                        # 默认端口9092，
# Switch to enable topic deletion or not, default value is false
delete.topic.enable=true
############################# Zookeeper #############################
zookeeper.connect=localhost:2181

启动

nohup bin/kafka-server-start.sh config/server.properties & 

停止命令bin/kafka-server-stop.sh config/server.properties

安装配置

# yum -y install redis
# vim /etc/redis.conf
bind 168.*.*.119

启动

# systemctl start redis.service

# git clone https://github.com/istresearch/scrapy-cluster.git
# cd scrapy-cluster
# pip install -r requirements.txt

离线运行单元测试,以确保一切似乎正常

# ./run_offline_tests.sh

修改配置

# vim kafka-monitor/settings.py
# vim redis-monitor/settings.py
# vim crawlers/crawling/settings.py

修改以下

# Redis host configuration
REDIS_HOST = "168.*.*.119"
REDIS_PORT = 6379
REDIS_DB = 0

KAFKA_HOSTS = "168.*.*.119:9092"
KAFKA_TOPIC_PREFIX = "demo"
KAFKA_CONN_TIMEOUT = 5
KAFKA_APPID_TOPICS = False
KAFKA_PRODUCER_BATCH_LINGER_MS = 25  # 25 ms before flush
KAFKA_PRODUCER_BUFFER_BYTES = 4 * 1024 * 1024  # 4MB before blocking

# Zookeeper Settings
ZOOKEEPER_ASSIGN_PATH = "/scrapy-cluster/crawler/"
ZOOKEEPER_ID = "all"
ZOOKEEPER_HOSTS = "168.*.*.119:2181"

启动监听

# nohup python kafka_monitor.py run >> /root/scrapy-cluster/kafka-monitor/kafka_monitor.log 2>&1 &
# nohup python redis_monitor.py >> /root/scrapy-cluster/redis-monitor/redis_monitor.log 2>&1 &

安装

# pip install scrapyd

配置

# sudo mkdir /etc/scrapyd
# sudo vi /etc/scrapyd/scrapyd.conf

[scrapyd]
eggs_dir    = eggs
logs_dir    = logs
items_dir   =
jobs_to_keep = 5
dbs_dir     = dbs
max_proc    = 0
max_proc_per_cpu = 10
finished_to_keep = 100
poll_interval = 5.0
bind_address = 0.0.0.0
http_port   = 6800
debug       = off
runner      = scrapyd.runner
application = scrapyd.app.application
launcher    = scrapyd.launcher.Launcher
webroot     = scrapyd.website.Root

[services]
schedule.json     = scrapyd.webservice.Schedule
cancel.json       = scrapyd.webservice.Cancel
addversion.json   = scrapyd.webservice.AddVersion
listprojects.json = scrapyd.webservice.ListProjects
listversions.json = scrapyd.webservice.ListVersions
listspiders.json  = scrapyd.webservice.ListSpiders
delproject.json   = scrapyd.webservice.DeleteProject
delversion.json   = scrapyd.webservice.DeleteVersion
listjobs.json     = scrapyd.webservice.ListJobs
daemonstatus.json = scrapyd.webservice.DaemonStatus

启动

# nohup scrapyd >> /root/scrapy-cluster/scrapyd.log 2>&1 &

建议做Nginx反向代理

启动异常

File "/usr/local/lib/python3.6/site-packages/scrapyd-1.2.0-py3.6.egg/scrapyd/app.py", line 2, in 
from twisted.application.internet import TimerService, TCPServer
File "/usr/local/lib64/python3.6/site-packages/twisted/application/internet.py", line 54, in 
from automat import MethodicalMachine
File "/usr/local/lib/python3.6/site-packages/automat/__init__.py", line 2, in 
from ._methodical import MethodicalMachine
File "/usr/local/lib/python3.6/site-packages/automat/_methodical.py", line 210, in 
    class MethodicalInput(object):
File "/usr/local/lib/python3.6/site-packages/automat/_methodical.py", line 220, in MethodicalInput
    @argSpec.default
builtins.TypeError: "_Nothing" object is not callable


Failed to load application: "_Nothing" object is not callable

解决：Automat降级

pip install Automat==0.6.0

安装

pip install SpiderKeeper

启动

mkdir /root/spiderkeeper/
nohup spiderkeeper --server=http://168.*.*.118:6800 --username=admin --password=admin --database-url=sqlite:////root/spiderkeeper/SpiderKeeper.db >> /root/scrapy-cluster/spiderkeeper.log 2>&1 &

浏览器访问http://168.*.*.118:5000

修改scrapy.cfg配置

vim /root/scrapy-cluster/crawler/scrapy.cfg

[settings]
default = crawling.settings

[deploy]
url = http://168.*.*.118:6800/
project = crawling

添加新的spider

cd /root/scrapy-cluster/crawler/crawling/spider

使用scrapyd-deploy部署项目

# cd /root/scrapy-cluster/crawler
# scrapyd-deploy 
Packing version 1536225989
Deploying to project "crawling" in http://168.*.*.118:6800/addversion.json
Server response (200):
{"status": "ok", "project": "crawling", "version": "1536225989", "spiders": 3, "node_name": "ambari"}

登录Spiderkeeper创建项目

使用scrapy.cfg中配置的项目名

创建后再Spiders->Dashboard中看到所有spider

Scrapy Cluster需要在不同的爬虫服务器之间进行协调，以确保最大的内容吞吐量，同时控制集群服务器爬取网站的速度。

Scrapy Cluster提供了两种主要策略来控制爬虫对不同域名的攻击速度。这由爬虫的类型与IP地址确定，但他们都作用于不同的域名队列。

Scrapy-cluster分布式爬虫，分发网址是基于IP地址。在不同的机器上启动集群，不同服务器上的每个爬虫去除队列中的所有链接。

配置一台新的服务器参照scrapy-cluster 单机配置,同时使用第一台服务器配置kafka-monitor/settings.py redis-monitor/settings.py crawling/settings.py

由于两台服务器同时部署在相同内网，spider运行后即获取相同Current public ip，导致scrapy-cluster调度器无法根据IP分发链接

2018-09-07 16:08:29,684 [sc-crawler] DEBUG: Current public ip: b"110.*.*.1"

参考代码/root/scrapy-cluster/crawler/crawling/distributed_scheduler.py第282行：

try:
    obj = urllib.request.urlopen(settings.get("PUBLIC_IP_URL",
                                  "http://ip.42.pl/raw"))
    results = self.ip_regex.findall(obj.read())
    if len(results) > 0:
        # results[0] 获取IP地址即为110.90.122.1
        self.my_ip = results[0]
    else:
        raise IOError("Could not get valid IP Address")
    obj.close()
    self.logger.debug("Current public ip: {ip}".format(ip=self.my_ip))
except IOError:
    self.logger.error("Could not reach out to get public ip")
    pass

建议修改代码，获取本机IP

self.my_ip = [(s.connect(("8.8.8.8", 53)), s.getsockname()[0], s.close()) 
                for s in [socket.socket(socket.AF_INET, socket.SOCK_DGRAM)]][0][1]

在两个scrapy-cluster中运行相同Spider

execute(["scrapy", "runspider", "crawling/spiders/link_spider.py"])

使用python kafka_monitor.py feed投递多个链接，使用DEBUG即可观察到链接分配情况

在第二台scrapy-cluster服务器上安装配置scrapyd，参考scrapyd 爬虫管理工具配置并修改配置

[settings]
default = crawling.settings

[deploy]
url = http://168.*.*.119:6800/
project = crawling

启动scrapyd后使用scrapyd-deploy工具部署两个scrapy-cluster上的爬虫项目。

重新启动spiderkeeper，对接两个scrapy-cluster的管理工具scrapyd。

nohup spiderkeeper --server=http://168.*.*.118:6800 --server=http://168.*.*.119:6800 --username=admin --password=admin --database-url=sqlite:////root/spiderkeeper/SpiderKeeper.db >> /root/scrapy-cluster/spiderkeeper.log 2>&1 &

注意：要使用spiderkeeper管理同一个集群，爬虫项目名称须一致，同时集群中scrapy-cluster配置相同spider任务

浏览器访问http://168.*.*.118:5000 启动爬虫时即可看见两个scrapy-cluster集群配置，启动同名爬虫开始scrapy-cluster分布式爬虫

启动分布式爬虫后状态