首页 > 脚本专栏 > python > python的elasticsearch_dsl转换es

python中的elasticsearch_dsl查询语句转换成es查询语句详解

2023-07-25 09:48:41 作者：IT之一小佬

这篇文章主要介绍了python中的elasticsearch_dsl查询语句转换成es查询语句详解,ElasticSearch在实际生产里通常和LogStash，Kibana，FileBeat一起构成Elastic Stack来使用，它是这些组件里面最核心的一个,需要的朋友可以参考下

elasticsearch_dsl查询语句转换成es语句

使用代码运行效果来演示转换结果。

示例代码1：

from elasticsearch_dsl import connections, Search, Q
es = connections.create_connection(hosts=["192.168.104.49:9200"], timeout=20)
# print(es)
res = Search(using=es, index="test_index").query().query()  # 当调用.query()方法多次时，内部会使用&操作符
print(res.to_dict())

运行结果：

示例代码2：

from elasticsearch_dsl import connections, Search, Q
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = ~Q("match", title="python")
res = Search(using=es, index="test_index").query(q)
print(res.to_dict())

运行结果：

示例代码3：

from elasticsearch_dsl import connections, Search, Q
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q('match', name='张') & Q("match", name="北")
res = Search(using=es, index="test_index").query(q)
print(res.to_dict())

运行结果：

示例代码4：

from elasticsearch_dsl import connections, Search, Q
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q("bool", must=[Q("match", address="山")], should=[Q("match", gender="男"), Q("match", emplyer="AAA")], minimum_should_match=1)
res = Search(using=es, index="test_index").query(q)
print(res.to_dict())

运行结果：

示例代码5：【分页】

from elasticsearch_dsl import connections, Search, Q
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q("bool", must=[Q("match", address="山")], should=[Q("match", gender="男"), Q("match", emplyer="AAA")], minimum_should_match=1)
res = Search(using=es, index="test_index").query(q)[2: 5]
print(res.to_dict())

运行结果：

示例代码6：【聚合】

from elasticsearch_dsl import connections, Search, Q, A
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q("match", sex='男')
a = A("terms", field="gender")
res = Search(using=es, index="test_index").query(q)
res.aggs.bucket("gender_terms", a)
print(res.to_dict())

运行结果：

示例代码7：【聚合】

from elasticsearch_dsl import connections, Search, Q, A
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q("match", sex='男')
res = Search(using=es, index="test_index").query(q)
res.aggs.bucket("per_gender", "terms", field="gender")
res.aggs["per_gender"].metric("sum_age", "sum", field="age")
res.aggs["per_gender"].bucket("terms_balance", "terms", field="balance")
res.aggs["per_gender"].bucket("terms_balance2", "terms", field="balance2")
print(res.to_dict())

运行结果：

示例代码8：【聚合内置排序】

from elasticsearch_dsl import connections, Search, Q, A
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q("match", sex='男')
res = Search(using=es, index="test_index").query(q)
res.aggs.bucket("agg_age", "terms", field="age", order={"_count": "desc"})
print(res.to_dict())

运行结果：

示例代码9：

from elasticsearch_dsl import connections, Search, Q, A
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q("match", sex='男')
res = Search(using=es, index="test_index").query(q)
res.aggs.bucket("agg_age", "terms", field="age", order={"_count": "asc"}).metric("avg_age", "avg", field="age")
print(res.to_dict())

运行结果：

示例代码10：【_source字段】

from elasticsearch_dsl import connections, Search, Q, A
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
q = Q("match", sex='男')
res = Search(using=es, index="test_index").query(q).source(['account_number', 'address'])
print(res.to_dict())

运行结果：

示例代码11：

from elasticsearch_dsl import connections, Search, Q
# 连接es
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
s = Search(using=es, index="account_info")
# 方式一：
# 省份为北京
q1 = Q("match", province="北京")
# 25或30岁的男性信息
q2 = Q("bool", must=[Q("terms", age=[25, 30]), Q("term", gender="男")])
# and
q = q1 & q2
res = s.query(q)
print(res.to_dict())
# for data in res:
#     print(data.to_dict())
print("共查到%d条数据" % res.count())
print("*" * 100)
# 方式二
# 省份为北京
q1 = Q("match", province="北京")
# 25或30岁的信息
# q2 = Q("bool", must=[Q("terms", age=[25, 30]), Q("term", gender="男")])
q2 = Q("term", age=25) | Q("term", age=30)
# 男性
q3 = Q("term", gender="男")
res = s.query(q1).query(q2).query(q3)  # 多次query就是& ==> and 操作
print(res.to_dict())
# for data in res:
#     print(data.to_dict())
print("共查到%d条数据" % res.count())

运行结果：

示例代码12：

from elasticsearch_dsl import connections, Search, Q, A
# 连接es
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
s = Search(using=es, index="account_info")
s.query()
q = A("terms", field="age", size=100).metric("age_per_balance", "avg", field="balance")
s.aggs.bucket("res", q)
print(s.to_dict())

运行结果：

示例代码13：【多次嵌套聚合】

from elasticsearch_dsl import connections, Search, Q, A
# 连接es
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
s = Search(using=es, index="account_info")
a1 = A("range", field="age", ranges={"from": 25, "to": 28})
a2 = A("terms", field="gender")
a3 = A("avg", field="balance")
s.aggs.bucket("res", a1).bucket("gender_group", a2).metric("balance_avg", a3)
print(s.to_dict())

运行结果：

示例代码14：【使用pycharm打断点查看查询语句】

from elasticsearch_dsl import connections, Search, Q, A
# 连接es
es = connections.create_connection(hosts=["192.168.124.49:9200"], timeout=20)
# print(es)
s = Search(using=es, index="account_info")
a1 = A("range", field="age", ranges={"from": 25, "to": 28})
a2 = A("terms", field="gender")
a3 = A("avg", field="balance")
s.aggs.bucket("res", a1).bucket("gender_group", a2).metric("balance_avg", a3)
# print(s.to_dict())
# 执行并拿到返回值
response = s.execute()
# res是bucket指定的名字
for data in response.aggregations.res:
    print(data.to_dict())

运行结果：