python elasticsearch从创建索引到写入数据的全过程

python elasticsearch从创建索引到写入数据

创建索引

from elasticsearch import Elasticsearch
es = Elasticsearch('192.168.1.1:9200')
mappings = {
      "mappings": {
 "type_doc_test": {#type_doc_test为doc_type
   "properties": {
     "id": {
"type": "long",
"index": "false"
     },
     "serial": {
"type": "keyword", # keyword不会进行分词,text会分词
"index": "false" # 不建索引
     },
     #tags可以存json格式，访问tags.content
     "tags": {
"type": "object",
"properties": {
  "content": {"type": "keyword", "index": True},
  "dominant_color_name": {"type": "keyword", "index": True},
  "skill": {"type": "keyword", "index": True},
}
     },
     "hasTag": {
"type": "long",
"index": True
     },
     "status": {
"type": "long",
"index": True
     },
     "createTime": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
     },
     "updateTime": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
     }
   }
 }
      }
    }
res = es.indices.create(index = 'index_test',body =mappings)

通过以上代码即可创建es索引

写入一条数据

写入数据需要根据创建的es索引类型对应的数据结构写入：

from elasticsearch import Elasticsearch
es = Elasticsearch('192.168.1.1:9200')
action ={
"id": "1111122222",
"serial":"版本",
#以下tags.content是错误的写法
#"tags.content" :"标签2",
#"tags.dominant_color_name": "域名的颜色黄色",
#正确的写法如下：
"tags":{"content":"标签3","dominant_color_name": "域名的颜色黄色"},
#按照字典的格式写入，如果用上面的那种写法，会直接写成一个tags.content字段。
#而不是在tags中content添加数据，这点需要注意
"tags.skill":"分类信息",
"hasTag":"123",
"status":"11",
"createTime" :"2018-2-2",
"updateTime":"2018-2-3",
 }
es.index(index="index_test",doc_type="doc_type_test",body = action)

即可写入一条数据

错误的写入

正确的写入

写入多条数据

from elasticsearch import Elasticsearch
from elasticsearch.helpers import bulk
es = Elasticsearch('192.168.1.1:9200')
ACTIONS = []
action1 ={
   "_index": "indes_test",
   "_type": "doc_type_test",
   "_id":"bSlegGUBmJ2C8ZCSC1R1",
   "_source":{
     "id": "1111122222",
     "serial":"版本",
     "tags.content" :"标签2",
     "tags.dominant_color_name": "域名的颜色黄色",
     "tags.skill":"分类信息",
     "hasTag":"123",
     "status":"11",
     "createTime" :"2018-2-2",
     "updateTime":"2018-2-3",
   }
 }
action2 ={
   "_index": "indes_test",
   "_type": "doc_type_test",
   "_id":"bSlegGUBmJ2C8ZCSC1R2",
   "_source":{
     "id": "1111122222",
     "serial":"版本",
     "tags.content" :"标签2",
     "tags.dominant_color_name": "域名的颜色黄色",
     "tags.skill":"分类信息",
     "hasTag":"123",
     "status":"11",
     "createTime" :"2018-2-2",
     "updateTime":"2018-2-3",
   }
 }
ACTIONS.append(action1)
ACTIONS.append(action2)
res,_ =bulk(es, ACTIONS, index="indes_test", raise_on_error=True)
print(res)

这个方式是手动指定了id，如果把”_id”这个参数去掉即可自动生成id数据.
如下：

action2 ={
   "_index": "indes_test",
   "_type": "doc_type_test",
   "_source":{
     "id": "1111122222",
     "serial":"版本",
     "tags.content" :"标签2",
     "tags.dominant_color_name": "域名的颜色黄色",
     "tags.skill":"分类信息",
     "hasTag":"123",
     "status":"11",
     "createTime" :"2018-2-2",
     "updateTime":"2018-2-3",
   }
 }

删除一条数据

from elasticsearch import Elasticsearch
es = Elasticsearch('192.168.1.1:9200')
res = es.delete(index="index_test",doc_type="doc_type_test", id ="bSlegGUBmJ2C8ZCSC1R1")
print(res)

直接替换id的即可删除所需的id

查询一条数据

from elasticsearch import Elasticsearch
es = Elasticsearch('192.168.1.1:9200')
res = es.get(index="index_test",doc_type="doc_type_test", id ="bSlegGUBmJ2C8ZCSC1R2")
print(res)

直接替换id的即可查询所需的id

查询所有数据

from elasticsearch import Elasticsearch

es = Elasticsearch('192.168.1.1:9200')

res = es.search(index="index_test",doc_type="doc_type_test")
print(res)
print(res['hits']['hits'])

通过['hits']参数，可以解析出查询数据的详细内容

根据关键词查找

from elasticsearch import Elasticsearch
es = Elasticsearch('192.168.1.1:9200')
doc = {
      "query": {
 "match": {
   "_id": "aSlZgGUBmJ2C8ZCSPVRO"
 }
      }
    }
res = es.search(index="index_test",doc_type="doc_type_test",body=doc)
print（res）

总结

所述是小编给大家介绍的python elasticsearch从创建索引到写入数据的全过程，希望对大家有所帮助，如果大家有任何疑问欢迎给我留言，小编会及时回复大家的！

python elasticsearch从创建索引到写入数据的全过程

Python相关栏目本月热门文章