ElasticSearch与python交互
测试环境 ElasticSearch7.7.0 python 3.8
1. 基本查询数据
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"match_all": {
}
}
}
res = es.search(index='movies', doc_type='movie', body=query)
print(res)
#查询索引为movies type为movie的所有数据
term 和terms的用法
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"term": {
"title": "Kill"
}
}
}
res = es.search(index='movies', doc_type='movie', body=query)
print(res)
#查询查询索引为movies type为movie的 且title等于kill的所有数据
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"terms": {
"title":
[
"Kill", "Lawrence of Arabia"
]
}
}
}
res = es.search(index='movies', doc_type='movie', body=query)
print(res)
#查询查询索引为movies type为movie的 且title等于kill或title等于Lawrence of Arabia的所有数据
match与multi_match
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"match": {
"title": "kill"
}
}
}
res = es.search(index='movies', doc_type='movie', body=query)
print(res)
#查询查询索引为movies type为movie的 且title包含kill的所有数据
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"multi_match": {
"query": "kill",
"fields": ["title", "genres"]
}
}
}
res = es.search(index='movies', doc_type='movie', body=query)
print(res)
#查询查询索引为movies type为movie的 条件是在title和genres中查询包含kill的所有数据
ids
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"ids": {
"type": "movie",
"values": [
"1", "2"
]
}
}
}
res = es.search(index='movies', body=query)
print(res)
#查询查询索引为movies type为movie的 id为1或者2的说有的值
复合查询
bool有3类查询关系，must(都满足),should(其中一个满足),must_not(都不满足)
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"bool": {
"must": [{
"match": {
"city": "Brogan"
}
},
{
"match": {
"state": "IL"
}
}
]
}
}
}
res = es.search(index='bank', doc_type="typeName", body=query)
print(res)
#查询索引bank type是typeName city包含Brogan且state包含IL的所有数据，
#如果把match换成term就是精准查找
切片查询 from size
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"match_all": {},
},
"from": 2,
"size": 4
}
res = es.search(index='bank', doc_type="typeName", body=query)
print(res)
#from 从什么地方开始，size查询几条记录 类似于sql中的skip 和limit的用法
范围查询 range
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"range": {
"age": {
"gte": 20,
"lte": 25
}
},
}
}
res = es.search(index='bank', doc_type="typeName", body=query)
print(res)
# 查询年龄在20-25之间的所有数据
根据前缀查询
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"prefix": {
"title": "T"
}
}
}
res = es.search(index='movies', doc_type="movie", body=query)
print(res)
查询title 前缀是T开头的说有数据
排序
from elasticsearch import Elasticsearch
es = Elasticsearch()
query = {
"query": {
"match_all": {}
},
"sort": {
"age": { # 根据age字段升序排序
"order": "asc" # asc升序，desc降序
}
}
}
res = es.search(index='bank', doc_type="typeName", body=query)
print(res)
按照年龄升序排列
响应过滤 和mongo的查询之后显示部分字段类似
# 只获取自己想要的字段
from elasticsearch import Elasticsearch
es = Elasticsearch()
query=["hits.hits._id"]
es.search(index="bank",doc_type="typeName",filter_path=query)
# 获取所有数据
query=["hits.hits._*"]
es.search(index="bank",doc_type="typeName",filter_path=query)
查询匹配数量
es.count(index="bank",doc_type="typeName")