索引 / 查询 JSON 文档

将 JSON 文档添加到索引中

import redis
from redis.commands.json.path import Path
import redis.commands.search.aggregation as aggregations
import redis.commands.search.reducers as reducers
from redis.commands.search.field import TextField, NumericField, TagField
from redis.commands.search.indexDefinition import IndexDefinition, IndexType
from redis.commands.search.query import NumericFilter, Query


r = redis.Redis(host='localhost', port=6379)
user1 = {
    "user":{
        "name": "Paul John",
        "email": "paul.john@example.com",
        "age": 42,
        "city": "London"
    }
}
user2 = {
    "user":{
        "name": "Eden Zamir",
        "email": "eden.zamir@example.com",
        "age": 29,
        "city": "Tel Aviv"
    }
}
user3 = {
    "user":{
        "name": "Paul Zamir",
        "email": "paul.zamir@example.com",
        "age": 35,
        "city": "Tel Aviv"
    }
}

user4 = {
    "user":{
        "name": "Sarah Zamir",
        "email": "sarah.zamir@example.com",
        "age": 30,
        "city": "Paris"
    }
}
r.json().set("user:1", Path.root_path(), user1)
r.json().set("user:2", Path.root_path(), user2)
r.json().set("user:3", Path.root_path(), user3)
r.json().set("user:4", Path.root_path(), user4)

schema = (TextField("$.user.name", as_name="name"),TagField("$.user.city", as_name="city"), NumericField("$.user.age", as_name="age"))
r.ft().create_index(schema, definition=IndexDefinition(prefix=["user:"], index_type=IndexType.JSON))

b'OK'

搜索(Searching)

简单搜索(Simple search)

r.ft().search("Paul")

Result{2 total, docs: [Document {'id': 'user:1', 'payload': None, 'json': '{"user":{"name":"Paul John","email":"paul.john@example.com","age":42,"city":"London"}}'}, Document {'id': 'user:3', 'payload': None, 'json': '{"user":{"name":"Paul Zamir","email":"paul.zamir@example.com","age":35,"city":"Tel Aviv"}}'}]}

过滤搜索结果(Filtering search results)

q1 = Query("Paul").add_filter(NumericFilter("age", 30, 40))
r.ft().search(q1)

Result{1 total, docs: [Document {'id': 'user:3', 'payload': None, 'json': '{"user":{"name":"Paul Zamir","email":"paul.zamir@example.com","age":35,"city":"Tel Aviv"}}'}]}

分页和排序搜索结果(Paginating and Ordering search Results)

# Search for all users, returning 2 users at a time and sorting by age in descending order
offset = 0
num = 2
q = Query("*").paging(offset, num).sort_by("age", asc=False) # pass asc=True to sort in ascending order
r.ft().search(q)

Result{4 total, docs: [Document {'id': 'user:1', 'payload': None, 'age': '42', 'json': '{"user":{"name":"Paul John","email":"paul.john@example.com","age":42,"city":"London"}}'}, Document {'id': 'user:3', 'payload': None, 'age': '35', 'json': '{"user":{"name":"Paul Zamir","email":"paul.zamir@example.com","age":35,"city":"Tel Aviv"}}'}]}

计算项目的总数

q = Query("*").paging(0, 0)
r.ft().search(q).total

4

使用 JSON Path 表达式进行映射

r.ft().search(Query("Paul").return_field("$.user.city", as_field="city")).docs

[Document {'id': 'user:1', 'payload': None, 'city': 'London'},
 Document {'id': 'user:3', 'payload': None, 'city': 'Tel Aviv'}]

聚合(Aggregation)

req = aggregations.AggregateRequest("Paul").sort_by("@age")
r.ft().aggregate(req).rows

[[b'age', b'35'], [b'age', b'42']]

计算项目的总数

# `group_by` 期望一个字符串或字符串列表，以便在对每个组应用聚合函数之前对结果进行分组。
# 在此处传递一个空列表的效果相当于 `GROUPBY 0`，它将聚合函数应用于整个结果集。
req = aggregations.AggregateRequest("*").group_by([], reducers.count().alias("total"))
r.ft().aggregate(req).rows

[[b'total', b'4']]