Elasticsearch 认证模拟题 - 8
一、题目
在集群中输入以下指令：
PUT phones/_doc/1
{"brand":"Samsumg","model":"Galaxy S9+","features":[{"type":"os", "value":"Android"},{"type":"storage", "value":"64"},{"type":"camera_resolution", "value":"12"}]
}
PUT phones/_doc/2
{"brand":"Apple","model":"iPhone XR","features":[{"type":"os", "value":"Apple 10s"},{"type":"storage", "value":"128"},{"type":"camera_resolution", "value":"12"}]
}GET /phones/_search
{"query": {"bool": {"must": [{"match": {"features.type": "storage"}},{"match": {"features.value": "12"}}]}}
}
注意查询语句的查询结果，尽管它们的 type 字段值为 storage 时，value 字段的值都不等于 12，不知道为什么，特征数组的类型和值对象之间的关系丢失了。
现要求新建一个索引 task10，能够保持特征数组中对象和值之间的关系。并将上述两个文档写入到 task10 中，然后编写一个查询 type 字段值为 storage 时，value 字段的值等于 12 的 查询。此时上面两个文档都应该不在你的查询范围内。
1.1 考点
讲真的，刚看这个题属实懵了，印象中确实有这个知识点，但是死活找不到！！！！
- nested 字段
- nested 查询
1.2 答案
# 创建索引
PUT task10
{"mappings": {"properties": {"brand": {"type": "keyword"},"model": {"type": "keyword"},"features": {"type": "nested", "properties": {"type": {"type" : "keyword"},"value": {"type": "keyword"}}}}}
}# 写入数据
POST task10/_bulk
{"index":{}}
{"brand":"Samsumg","model":"Galaxy S9+","features":[{"type":"os","value":"Android"},{"type":"storage","value":"64"},{"type":"camera_resolution","value":"12"}]}
{"index":{}}
{"brand":"Apple","model":"iPhone XR","features":[{"type":"os","value":"Apple 10s"},{"type":"storage","value":"128"},{"type":"camera_resolution","value":"12"}]}
{"index":{}}
{"brand":"Apple","model":"iPhone XR","features":[{"type":"os","value":"Apple 10s"},{"type":"storage","value":"12"},{"type":"camera_resolution","value":"12"}]}# 查询
GET /task10/_search
{"query": {"nested": {"path": "features","query": {"bool": {"must": [{"match": {"features.type": "storage"}},{"match": {"features.value": "12"}}]}}}}
}
二、题目
二个索引，主索引是 miantable，用户索引是 usertable，miantable 通过 userid 关联 usertable， usertable 总共有4个用户数据。
要求：
- 新建表
miantable_v1，miantable_v1包含miantable的所有字段 miantable_v1新增userName，通过userid将usertable索引中userName关联到miantable_v1
# 创建索引结构
PUT usertable
{"mappings": {"properties": {"userid": {"type": "integer"},"username": {"type": "keyword"}}}
}PUT miantable
{"mappings": {"properties": {"f_crm_id": {"type": "integer"},"miantable_name": {"type": "keyword"},"userid": {"type": "integer"}}}
}# 批量写入数据
POST usertable/_bulk
{"index":{"_id":1}}
{"userid":1, "username":"tom"}
{"index":{"_id":2}}
{"userid":2, "username":"white"}
{"index":{"_id":3}}
{"userid":3, "username":"john"}
{"index":{"_id":4}}
{"userid":4, "username":"green"}POST miantable/_bulk
{"index":{"_id":1}}
{"f_crm_id":1, "miantable_name":"name1", "userid":1}
{"index":{"_id":2}}
{"f_crm_id":2, "miantable_name":"name2", "userid":2}
{"index":{"_id":3}}
{"f_crm_id":3, "miantable_name":"name3", "userid":3}
{"index":{"_id":4}}
{"f_crm_id":4, "miantable_name":"name4", "userid":1}
{"index":{"_id":5}}
{"f_crm_id":5, "miantable_name":"name5", "userid":1}
{"index":{"_id":6}}
{"f_crm_id":6, "miantable_name":"name6", "userid":2}
{"index":{"_id":7}}
{"f_crm_id":7, "miantable_name":"name7", "userid":2}
{"index":{"_id":8}}
{"f_crm_id":8, "miantable_name":"name8", "userid":4}
{"index":{"_id":9}}
{"f_crm_id":9, "miantable_name":"name9", "userid":4}
{"index":{"_id":10}}
{"f_crm_id":10, "miantable_name":"name10", "userid":1}
{"index":{"_id":11}}
{"f_crm_id":11, "miantable_name":"name11", "userid":2}
{"index":{"_id":12}}
{"f_crm_id":12, "miantable_name":"name12", "userid":5}
2.1 考点
- Enrich
- 重建索引
这里我认为直接看 enrich 的三个例子是最快能理解的
2.2 答案
# 新建enrich 策略
PUT /_enrich/policy/my-policy
{"match": {"indices": "usertable","match_field": "userid","enrich_fields": ["username"]}
}# 执行策略
POST /_enrich/policy/my-policy/_execute# 建立管道
PUT _ingest/pipeline/my-pipeline
{"processors" : [{"enrich": {"policy_name": "my-policy","field": "userid","target_field": "add_field","max_matches": "1"}},{"rename": {"field": "add_field.username","target_field": "username","ignore_failure": true}},{"remove": {"field": "add_field","ignore_failure": true}}]
}# 重建索引
POST _reindex
{"source": {"index": "miantable"},"dest": {"index": "miantable_v1","pipeline": "my-pipeline"}
}# 查询结果
GET miantable_v1/_search