如何高效利用Elasticsearch的nested类型处理复杂嵌套数据？

Elasticsearch嵌套类型nested使用指南 嵌套类型nested的特点 可以存储数组对象 每个对象独立存储为隐藏的子文档 嵌套类型nested和object类型的区别和应用场景 nested 每个对象独立存储为隐藏的子文档 适合存储数组 查询的时候有特定的语法 nested查询 且字段要用对象.字段名 性能略低 因为要维护子文档 object 扁平化存储，数组中的对象相同字段会合并成数组 适合存储单层的json对象 查询的时候指定对象.字段名称即可 查询性能高 嵌套类型nested如何使用 索引结构 "properties" : { "create_time" : { "format" : "yyyy-MM-dd HH:mm:ss Z||yyyy-MM-dd HH:mm:ss||yyyy-MM-dd HH:mm:ss.SSS Z||yyyy-MM-dd HH:mm:ss.SSS||yyyy-MM-dd HH:mm:ss,SSS||yyyy/MM/dd HH:mm:ss||yyyy-MM-dd HH:mm:ss,SSS Z||yyyy/MM/dd HH:mm:ss,SSS Z||epoch_millis||yyyy-MM-dd", "index" : true, "type" : "date", "doc_values" : true }, "title" : { "index" : true, "type" : "text" }, "users" : { "type" : "nested", "properties" : { "sex" : { "type" : "keyword" }, "age" : { "type" : "integer" }, "username" : { "type" : "keyword" } } } } 插入数据 POST cn_taoym_json_to_nested/_bulk {"index":{}} {"create_time":"2023-10-01 10:00:00","title":"第一条数据","users":[{"username":"user1","age":25,"sex":"male"}]} {"index":{}} {"create_time":"2023-10-02 14:30:00","title":"第二条数据","users":[{"username":"user2","age":30,"sex":"female"}]} {"index":{}} {"create_time":"2023-10-03 09:15:00","title":"第三条数据","users":[{"username":"user3","age":28,"sex":"male"},{"username":"user4","age":22,"sex":"female"}]} {"index":{}} {"create_time":"1696300800000","title":"第四条数据（时间戳格式）","users":[{"username":"user5","age":35,"sex":"male"}]} {"index":{}} {"create_time":"2023/10/05 16:45:00","title":"第五条数据（不同日期格式）","users":[{"username":"user6","age":27,"sex":"female"}]} 查询username为user3的数据 GET cn_taoym_json_to_nested/_search { "query": { "nested": { "path": "users", "query": { "term": { "users.username": { "value": "user3" } } }, "inner_hits": {} }