Python Elasticsearch DSL 的使用

一、Elasticsearch的基本概念

• Index：Elasticsearch用来存储数据的逻辑区域，它类似于关系型数据库中的database 概念。一个index可以在一个或者多个shard上面，同时一个shard也可能会有多个replicas。
• Document：Elasticsearch里面存储的实体数据，类似于关系数据中一个table里面的一行数据。 document由多个field组成，不同的document里面同名的field一定具有相同的类型。document里面field可以重复出现，也就是一个field会有多个值，即multivalued。
• Document type：为了查询需要，一个index可能会有多种document，也就是document type. 它类似于关系型数据库中的 table 概念。但需要注意，不同document里面同名的field一定要是相同类型的。
• Mapping：它类似于关系型数据库中的 schema 定义概念。存储field的相关映射信息，不同document type会有不同的mapping。

二、Python Elasticsearch DSL使用简介

1、安装

<code>$ pip install elasticsearch-dsl/<code>

2、创建索引和文档

<code>from datetime import datetime
from elasticsearch_dsl import DocType, Date, Integer, Keyword, Text
from elasticsearch_dsl.connections import connections
# Define a default Elasticsearch client
connections.create_connection(hosts=['localhost'])
class Article(DocType): 

    title = Text(analyzer='snowball', fields={'raw': Keyword()})
    body = Text(analyzer='snowball')
    tags = Keyword()
    published_from = Date()
    lines = Integer()
    class Meta:
        index = 'blog'
    def save(self, ** kwargs):
        self.lines = len(self.body.split())
        return super(Article, self).save(** kwargs)
    def is_published(self):
        return datetime.now() >= self.published_from
# create the mappings in elasticsearch
Article.init()/<code>

创建了一个索引为blog，文档为article的Elasticsearch数据库和表。必须执行Article.init()方法。 这样Elasticsearch才会根据你的DocType产生对应的Mapping。否则Elasticsearch就会在你第一次创建Index和Type的时候根据你的内容建立对应的Mapping。

现在我们可以通过Elasticsearch Restful API来检查

<code>http GET http://127.0.0.1:9200/blog/_mapping/
{"blog":
\t{"mappings":
\t\t{"article":
\t\t\t{"properties":{
\t\t\t\t"body":{"type":"text","analyzer":"snowball"},
\t\t\t\t"lines":{"type":"integer"},
\t\t\t\t"published_from":{"type":"date"},
\t\t\t\t"tags":{"type":"keyword"},
\t\t\t\t"title":{"type":"text","fields":{"raw":{"type":"keyword"}},"analyzer":"snowball"}
\t\t\t}
\t\t}}
\t}
}/<code>

三、使用Elasticsearch进行CRUD操作

1、Create an article

<code># create and save and article
article = Article(meta={'id': 1}, title='Hello elasticsearch!', tags=['elasticsearch']) 

article.body = ''' looong text '''
article.published_from = datetime.now()
article.save()/<code>

=>Restful API

<code>http POST http://127.0.0.1:9200/blog/article/1 title="hello elasticsearch" tags:='["elasticsearch"]'
HTTP/1.1 201 Created
Content-Length: 73
Content-Type: application/json; charset=UTF-8
{
    "_id": "1", 
    "_index": "blog", 
    "_type": "article", 
    "_version": 1, 
    "created": true
}/<code>

2、Get a article

<code>article = Article.get(id=1)
# 如果获取一个不存在的文章则返回None
a = Article.get(id='no-in-es')
a is None
# 还可以获取多个文章
articles = Article.mget([1, 2, 3])/<code>

=>Restful API

<code>http GET http://127.0.0.1:9200/blog/article/1
HTTP/1.1 200 OK
Content-Length: 141
Content-Type: application/json; charset=UTF-8
{
    "_id": "1", 
    "_index": "blog", 
    "_source": {
        "tags": [
            "elasticsearch"
        ], 
        "title": "hello elasticsearch"
    }, 
    "_type": "article", 
    "_version": 1, 
    "found": true
}/<code> 

3、Update a article

<code>article = Article.get(id=1)
article.tags = ['elasticsearch', 'hello']
article.save()
# 或者
article.update(body='Today is good day!', published_by='me')/<code>

=>Restful API

<code>http PUT http://127.0.0.1:9200/blog/article/1 title="hello elasticsearch" tags:='["elasticsearch", "hello"]'
HTTP/1.1 200 OK
Content-Length: 74
Content-Type: application/json; charset=UTF-8
{
    "_id": "1", 
    "_index": "blog", 
    "_type": "article", 
    "_version": 2, 
    "created": false
}/<code>

4、Delete a article

<code>article = Article.get(id=1)
article.delete()/<code>

=> Restful API

<code>http DELETE http://127.0.0.1:9200/blog/article/1
HTTP/1.1 200 OK
Content-Length: 71
Content-Type: application/json; charset=UTF-8
{
    "_id": "1", 
    "_index": "blog", 
    "_type": "article", 
    "_version": 4, 
    "found": true
}
http HEAD  http://127.0.0.1:9200/blog/article/1
HTTP/1.1 404 Not Found
Content-Length: 0
Content-Type: text/plain; charset=UTF-8/<code>

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關鍵字: 使用 ElasticSearch Python