Python插入Elasticsearch操作方法解析_Python

这篇文章主要介绍了Python插入Elasticsearch操作方法解析,文中通过示例代码介绍的非常详细，对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下

在用scrapy做爬虫的时候，需要将数据存入的es中。网上找了两种方法，照葫芦画瓢也能出来，暂记下来：

首先安装了es，版本是5.6.1的较早版本

用pip安装与es版本相对的es相关包

pip install elasticsearch-dsl==5.1.0

方法一：

以下是pipelines.py模块的完整代码

				?

									# -*- coding: utf-8 -*-

									# Define your item pipelines here

									#

									# Don't forget to add your pipeline to the ITEM_PIPELINES setting

									# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html

									import chardet

									class SinafinancespiderPipeline(object):

									  def process_item(self, item, spider):

									    return item

									# 写入到es中,需要在settings中启用这个类 ExchangeratespiderESPipeline

									# 需要安装pip install elasticsearch-dsl==5.1.0 注意与es版本需要对应

									from elasticsearch_dsl import Date,Nested,Boolean,analyzer,Completion,Keyword,Text,Integer,DocType

									from elasticsearch_dsl.connections import connections

									connections.create_connection(hosts=['192.168.52.138'])

									from elasticsearch import Elasticsearch

									es = Elasticsearch()

									class AticleType(DocType):

									  page_from = Keyword()

									  # domain报错

									  domain=Keyword()

									  cra_url=Keyword()

									  spider = Keyword()

									  cra_time = Keyword()

									  page_release_time = Keyword()

									  page_title = Text(analyzer="ik_max_word")

									  page_content = Text(analyzer="ik_max_word")

									class Meta:

									    index = "scrapy"

									    doc_type = "sinafinance"

									    # 以下settings和mappings都没起作用，暂且记下

									    settings = {

									      "number_of_shards": 3,

									    }

									    mappings = {

									      '_id':{'path':'cra_url'}

									    }

									class ExchangeratespiderESPipeline(DocType):

									  from elasticsearch5 import Elasticsearch

									  ES = ['192.168.52.138:9200']

									  es = Elasticsearch(ES,sniff_on_start=True)

									  def process_item(self, item, spider):

									    spider.logger.info("-----enter into insert ES")

									    article = AticleType()

									    article.page_from=item['page_from']

									    article.domain=item['domain']

									    article.cra_url =item['cra_url']

									    article.spider =item['spider']

									    article.cra_time =item['cra_time']

									    article.page_release_time =item['page_release_time']

									    article.page_title =item['page_title']

									    article.page_content =item['page_content']

									    article.save()

									    return item

以上方法能将数据写入es，但是如果重复爬取的话，会重复插入数据，因为主键 ”_id” 是ES自己产生的，找不到自定义_id的入口。于是放弃。

方法二：实现自定义主键写入，覆盖插入

				?

									# -*- coding: utf-8 -*-

									# Define your item pipelines here

									#

									# Don't forget to add your pipeline to the ITEM_PIPELINES setting

									# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html

									from elasticsearch5 import Elasticsearch

									class SinafinancespiderPipeline(object):

									  def process_item(self, item, spider):

									    return item

									# 写入到es中,需要在settings中启用这个类 ExchangeratespiderESPipeline

									# 需要安装pip install elasticsearch-dsl==5.1.0 注意与es版本需要对应

									class SinafinancespiderESPipeline():

									  def __init__(self):

									    self.ES = ['192.168.52.138:9200']

									    # 创建es客户端

									    self.es = Elasticsearch(

									      self.ES,

									      # 启动前嗅探es集群服务器

									      sniff_on_start=True,

									      # es集群服务器结点连接异常时是否刷新es结点信息

									      sniff_on_connection_fail=True,

									      # 每60秒刷新节点信息

									      sniffer_timeout=60

									    )

									  def process_item(self, item, spider):

									    spider.logger.info("-----enter into insert ES")

									    doc = {

									      'page_from': item['page_from'],

									      'domain': item['domain'],

									      'spider': item['spider'],

									      'page_release_time': item['page_release_time'],

									      'page_title': item['page_title'],

									      'page_content': item['page_content'],

									      'cra_url': item['cra_url'],

									      'cra_time': item['cra_time']

									    }

									    self.es.index(index='scrapy', doc_type='sinafinance', body=doc, id=item['cra_url'])

									    return item

搜索数据的方法：

				?

									# 字典形式设置body

									query = {

									 'query': {

									  'bool': {

									   'must': [

									    {'match': {'_all': 'python web'}}

									   ],

									   'filter': [

									    {'term': {'status': 2}}

									   ]

									  }

									 }

									}

									ret = es.search(index='articles', doc_type='article', body=query)

									# 查询数据

									data = es.search(index='articles', doc_type='article', body=body)

									print(data)

									# 增加

									es.index(...)

									# 修改

									es.update(...)

									# 删除

									es.delete()

完成后

在settings.py模块中注册自定义的类

				?

									ITEM_PIPELINES = {

									  # 'sinafinancespider.pipelines.SinafinancespiderPipeline': 300,

									  'sinafinancespider.pipelines.SinafinancespiderESPipeline': 300,

									}