Scrapy-Cluster结合Spiderkeeper管理分布式爬虫

Scrapy-cluster 建设

• 基于Scrapy-cluster库的kafka-monitor能够实现分布式爬虫
• Scrapyd+Spiderkeeper实现爬虫的可视化管理

环境

IP	Role
168.*.*.118	Scrapy-cluster,scrapyd,spiderkeeper
168.*.*.119	Scrapy-cluster,scrapyd,kafka,redis,zookeeper

# 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)

Zookeeper 单机配置

• 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

kafka 单机配置

• 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 &

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

redis 单机配置

• 安装配置

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

• 启动

# systemctl start redis.service

scrapy-cluster 单机配置

# 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,以确保一切彷佛正常

# ./run_offline_tests.sh

• 修改配置

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

• 修改如下

# 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 &

scrapyd 爬虫管理工具配置

• 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 &

建议作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 <module>
from twisted.application.internet import TimerService, TCPServer
File "/usr/local/lib64/python3.6/site-packages/twisted/application/internet.py", line 54, in <module>
from automat import MethodicalMachine
File "/usr/local/lib/python3.6/site-packages/automat/__init__.py", line 2, in <module>
from ._methodical import MethodicalMachine
File "/usr/local/lib/python3.6/site-packages/automat/_methodical.py", line 210, in <module>
    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

Spiderkeeper 爬虫管理界面配置

• 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

使用Spiderkeeper 管理爬虫

使用scrapyd-deploy部署爬虫项目

• 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"}

spiderkeeper 配置爬虫项目

• 登陆Spiderkeeper建立项目

使用scrapy.cfg中配置的项目名

建立后再Spiders->Dashboard中看到全部spider

Scrapy-cluster 分布式爬虫

Scrapy Cluster须要在不一样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一样域名的攻击速度。这由爬虫的类型与IP地址肯定，但他们都做用于不一样的域名队列。

Scrapy-cluster分布式爬虫，分发网址是基于IP地址。在不一样的机器上启动集群，不一样服务器上的每一个爬虫去除队列中的全部连接。

部署集群中第二个scrapy-cluster

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

Current public ip 问题

因为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，致使scrapy-cluster调度器没法根据IP分发连接

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]

运行分布式爬虫

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投递多个连接，使用DEBUG便可观察到连接分配状况

使用SpiderKeeper管理分布式爬虫

配置scrapyd管理集群第二个scrapy-cluster

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。

使用Spiderkeeper链接多个scrapy-cluster

• 从新启动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 启动爬虫时便可看见两个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