Mapping Character Filter：用途：替换指定字符

Pattern Replace Character Filter：用途：基于正则表达式替换指定字符

2.Tokenizer 文本切为分词

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/analysis-tokenizers.html#_word_oriented_tokenizers 只能配置一个 用分词器对文本进行分词

3.Token filters 分词后再过滤

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/analysis-tokenfilters.html 可配置0个或多个 分词后再加工，比如转小写、删除某些特殊的停用词、增加同义词等

真题演练

有一个文档，内容类似 dag & cat, 要求索引这个文档，并且使用match_parase_query, 查询dag & cat 或者 dag and cat,都能够查到 题目分析： 1.何为match_parase_query：match_phrase 会将检索关键词分词。match_phrase的分词结果必须在被检索字段的分词中都包含，而且顺序必须相同，而且默认必须都是连续的。 2.要实现 & 和 and 查询结果要等价，那么就需要自定义分词器来实现了，定制化的需求 3.如何自定义一个分词器：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/analysis-custom-analyzer.html 4.解法1核心使用功能点，Mapping Character Filter 5.解法2核心使用功能点，https://www.elastic.co/guide/en/elasticsearch/reference/8.1/analysis-synonym-tokenfilter.html

解法1

# 新建索引PUT /test01{  "settings": {    "analysis": {      "analyzer": {        "my_analyzer": {          "char_filter": [            "my_mappings_char_filter"          ],          "tokenizer": "standard",        }      },      "char_filter": {        "my_mappings_char_filter": {          "type": "mapping",          "mappings": [            "& => and"          ]        }      }    }  },  "mappings": {    "properties": {      "content":{        "type": "text",        "analyzer": "my_analyzer"      }    }  }}// 说明// 三段论之Character filters，使用char_filter进行文本替换// 三段论之Token filters，使用默认分词器// 三段论之Token filters，未设定// 字段content 使用自定义分词器my_analyzer# 填充测试数据PUT test01/_bulk{"index":{"_id":1}}{"content":"doc & cat"}{"index":{"_id":2}}{"content":"doc and cat"}# 执行测试,doc & cat || oc and cat 结果输出都为两条POST test01/_search{  "query": {    "bool": {      "must": [        {          "match_phrase": {            "content": "doc & cat"          }        }      ]    }  }}

解法2

# 解题思路，将& 和 and  设定为同义词，使用Token filters# 创建索引PUT /test02{  "settings": {    "analysis": {      "analyzer": {        "my_synonym_analyzer": {          "tokenizer": "whitespace",          "filter": [            "my_synonym"          ]        }      },      "filter": {        "my_synonym": {          "type": "synonym",          "lenient": true,          "synonyms": [            "& => and"          ]        }      }    }  },  "mappings": {    "properties": {      "content": {        "type": "text",        "analyzer": "my_synonym_analyzer"      }    }  }}// 说明// 三段论之Character filters，未设定// 三段论之Token filters，使用whitespace空格分词器，为什么不用默认分词器？因为默认分词器会把&分词后剔除了，就无法在去做分词后的过滤操作了// 三段论之Token filters，使用synony分词后过滤器，对&和and做同义词// 字段content 使用自定义分词器my_synonym_analyzer# 填充测试数据PUT test02/_bulk{"index":{"_id":1}}{"content":"doc & cat"}{"index":{"_id":2}}{"content":"doc and cat"}# 执行测试POST test02/_search{  "query": {    "bool": {      "must": [        {          "match_phrase": {            "content": "doc & cat"          }        }      ]    }  }}

六.multi-fields

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/multi-fields.html

// 单字段多类型,比如一个字段我想设置两种分词器PUT my-index-000001{  "mappings": {    "properties": {      "city": {        "type": "text",        "analyzer":"standard",        "fields": {          "fieldText": {             "type":  "text",            "analyzer":"ik_smart",          }        }      }    }  }}

七.runtime_field 运行时字段

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/runtime.html

产生背景

假如业务中需要根据某两个数字类型字段的差值来排序，也就是我需要一个不存在的字段, 那么此时应该怎么办？ 当然你可以刷数，新增一个差值结果字段来实现，假如此时不允许你刷数新增字段怎么办？

解决方案

​

应用场景

1. 在不重新建立索引的情况下，向现有文档新增字段
2. 在不了解数据结构的情况下处理数据
3. 在查询时覆盖从原索引字段返回的值
4. 为特定用途定义字段而不修改底层架构

功能特性

1. Lucene完全无感知，因没有被索引化，没有doc_values
2. 不支持评分，因为没有倒排索引
3. 打破传统先定义后使用的方式
4. 能阻止mapping爆炸
5. 增加了API的灵活性
6. 注意，会使得搜索变慢

实际使用

• 运行时检索指定，即检索环节可使用（也就是哪怕mapping中没有这个字段，我也可以查询）
• 动态或静态mapping指定，即mapping环节可使用（也就是在mapping中添加一个运行时的字段）

真题演练1

# 假定有以下索引和数据PUT test03{  "mappings": {    "properties": {      "emotion": {        "type": "integer"      }    }  }}POST test03/_bulk{"index":{"_id":1}}{"emotion":2}{"index":{"_id":2}}{"emotion":5}{"index":{"_id":3}}{"emotion":10}{"index":{"_id":4}}{"emotion":3}# 要求：emotion > 5, 返回emotion_falg = "1",  # 要求：emotion < 5, 返回emotion_falg = "-1",  # 要求：emotion = 5, 返回emotion_falg = "0",  

解法1

检索时指定运行时字段: https://www.elastic.co/guide/en/elasticsearch/reference/8.1/runtime-search-request.html 该字段本质上是不存在的，所以需要检索时要加上 fields *

GET test03/_search{  "fields": [    "*"  ],   "runtime_mappings": {    "emotion_falg": {      "type": "keyword",      "script": {        "source": """          if(doc["emotion"].value>5)emit("1");          if(doc["emotion"].value<5)emit("-1");          if(doc["emotion"].value==5)emit("0");          """      }    }  }}

解法2

创建索引时指定运行时字段：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/runtime-mapping-fields.html 该方式支持通过运行时字段做检索

# 创建索引并指定运行时字段PUT test03_01{  "mappings": {    "runtime": {      "emotion_falg": {        "type": "keyword",        "script": {          "source": """          if(doc["emotion"].value>5)emit("1");          if(doc["emotion"].value<5)emit("-1");          if(doc["emotion"].value==5)emit("0");          """        }      }    },    "properties": {      "emotion": {        "type": "integer"      }    }  }}# 导入测试数据POST test03_01/_bulk{"index":{"_id":1}}{"emotion":2}{"index":{"_id":2}}{"emotion":5}{"index":{"_id":3}}{"emotion":10}{"index":{"_id":4}}{"emotion":3}# 查询测试GET test03_01/_search{  "fields": [    "*"  ]}

真题演练2

# 有以下索引和数据PUT test04{  "mappings": {    "properties": {      "A":{        "type": "long"      },      "B":{        "type": "long"      }    }  }}PUT task04/_bulk{"index":{"_id":1}}{"A":100,"B":2}{"index":{"_id":2}}{"A":120,"B":2}{"index":{"_id":3}}{"A":120,"B":25}{"index":{"_id":4}}{"A":21,"B":25}# 需求：在task04索引里，创建一个runtime字段，其值是A-B，名称为A_B； 创建一个range聚合，分为三级：小于0，0-100，100以上；返回文档数// 使用知识点：// 1.检索时指定运行时字段: https://www.elastic.co/guide/en/elasticsearch/reference/8.1/runtime-search-request.html// 2.范围聚合 https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-bucket-range-aggregation.html

解法

# 结果测试GET task04/_search{  "fields": [    "*"  ],   "size": 0,   "runtime_mappings": {    "A_B": {      "type": "long",      "script": {        "source": """          emit(doc["A"].value - doc["B"].value);          """      }    }  },  "aggs": {    "price_ranges_A_B": {      "range": {        "field": "A_B",        "ranges": [          { "to": 0 },          { "from": 0, "to": 100 },          { "from": 100 }        ]      }    }  }}

八.Search-highlighted

highlighted语法初识

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/highlighting.html

​

九.Search-Order

Order语法初识

官网文档地址： https://www.elastic.co/guide/en/elasticsearch/reference/8.1/sort-search-results.html

// 注意：text类型默认是不能排或聚合的，如果非要排序或聚合，需要开启fielddataGET /kibana_sample_data_ecommerce/_search{  "query": {    "match": {      "customer_last_name": "wood"    }  },  "highlight": {    "number_of_fragments": 3,    "fragment_size": 150,    "fields": {      "customer_last_name": {        "pre_tags": [          ""        ],        "post_tags": [          ""        ]      }    }  },  "sort": [    {      "currency": {        "order": "desc"      },      "_score": {        "order": "asc"      }    }  ]}

十.Search-Page

page语法初识

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/paginate-search-results.html

# 注意 from的起始值是 0 不是 1GET kibana_sample_data_ecommerce/_search{  "from": 5,  "size": 20,  "query": {    "match": {      "customer_last_name": "wood"    }  }}

真题演练1

# 题目In the spoken lines of the play, highlight the word Hamlet (int the text_entry field) startint the highlihnt with "#aaa#" and ending it with "#bbb#"return all of speech_number field lines in reverse order; "20" speech lines per page,starting from line "40"# highlight 处理 text_entry 字段 ； 关键词 Hamlet 高亮# page分页：from：40；size:20# speech_number：倒序POST test09/_search{  "from": 40,  "size": 20,  "query": {    "bool": {      "must": [        {          "match": {            "text_entry": "Hamlet"          }        }      ]    }  },  "highlight": {    "fields": {      "text_entry": {        "pre_tags": [          "#aaa#"        ],        "post_tags": [          "#bbb#"        ]      }    }  },  "sort": [    {      "speech_number.keyword": {        "order": "desc"      }    }  ]}

十一.Search-AsyncSearch

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/async-search.html

发行版本

7.7.0

适用场景

允许用户在异步搜索结果时可以检索，从而消除了仅在查询完成后才等待最终响应的情况

常用命令

• 执行异步检索
• POST /sales*/_async_search?size=0
• 查看异步检索
• GET /_async_search/id值
• 查看异步检索状态
• GET /_async_search/id值
• 删除、终止异步检索
• DELETE /_async_search/id值

异步查询结果说明

十二.Aliases索引别名

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/aliases.html

Aliases的作用

在ES中，索引别名（index aliases）就像一个快捷方式或软连接，可以指向一个或多个索引。别名带给我们极大的灵活性，我们可以使用索引别名实现以下功能：

1. 在一个运行中的ES集群中无缝的切换一个索引到另一个索引上（无需停机）
2. 分组多个索引，比如按月创建的索引，我们可以通过别名构造出一个最近3个月的索引
3. 查询一个索引里面的部分数据构成一个类似数据库的视图（views

假设没有别名，如何处理多索引的检索

方式1：POST index_01,index_02.index_03/_search 方式2：POST index*/search

创建别名的三种方式

1. 创建索引的同时指定别名

# 指定test05的别名为 test05_aliasesPUT test05{  "mappings": {    "properties": {      "name":{        "type": "keyword"      }    }  },  "aliases": {    "test05_aliases": {}  }}

1. 使用索引模板的方式指定别名

PUT _index_template/template_1{  "index_patterns": ["te*", "bar*"],  "template": {    "settings": {      "number_of_shards": 1    },    "mappings": {      "_source": {        "enabled": true      },      "properties": {        "host_name": {          "type": "keyword"        },        "created_at": {          "type": "date",          "format": "EEE MMM dd HH:mm:ss Z yyyy"        }      }    },    "aliases": {      "mydata": { }    }  },  "priority": 500,  "composed_of": ["component_template1", "runtime_component_template"],   "version": 3,  "_meta": {    "description": "my custom"  }}

1. 对已有的索引创建别名

POST _aliases{  "actions": [    {      "add": {        "index": "logs-nginx.access-prod",        "alias": "logs"      }    }  ]}

删除别名

POST _aliases{  "actions": [    {      "remove": {        "index": "logs-nginx.access-prod",        "alias": "logs"      }    }  ]}

真题演练1

# Define an index alias for "accounts-row" called "accounts-male": Apply a filter to only show the male account owners# 为"accounts-row"定义一个索引别名，称为"accounts-male":应用一个过滤器，只显示男性账户所有者POST _aliases{  "actions": [    {      "add": {        "index": "accounts-row",        "alias": "accounts-male",        "filter": {          "bool": {            "filter": [              {                "term": {                  "gender.keyword": "male"                }              }            ]          }        }      }    }  ]}

十三.Search-template

官网文档地址:https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-template.html

功能特点

模板接受在运行时指定参数。搜索模板存储在服务器端，可以在不更改客户端代码的情况下进行修改。

初识search-template

# 创建检索模板PUT _scripts/my-search-template{  "script": {    "lang": "mustache",    "source": {      "query": {        "match": {          "{{query_key}}": "{{query_value}}"        }      },      "from": "{{from}}",      "size": "{{size}}"    }  }}# 使用检索模板查询GET my-index/_search/template{  "id": "my-search-template",  "params": {    "query_key": "your filed",    "query_value": "your filed value",    "from": 0,    "size": 10  }}

索引模板的操作

创建索引模板

PUT _scripts/my-search-template{  "script": {    "lang": "mustache",    "source": {      "query": {        "match": {          "message": "{{query_string}}"        }      },      "from": "{{from}}",      "size": "{{size}}"    },    "params": {      "query_string": "My query string"    }  }}

验证索引模板

POST _render/template{  "id": "my-search-template",  "params": {    "query_string": "hello world",    "from": 20,    "size": 10  }}

执行检索模板

GET my-index/_search/template{  "id": "my-search-template",  "params": {    "query_string": "hello world",    "from": 0,    "size": 10  }}

获取全部检索模板

GET _cluster/state/metadata?pretty&filter_path=metadata.stored_scripts

删除检索模板

DELETE _scripts/my-search-templateath=metadata.stored_scripts

十四.Search-dsl 简单检索

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/query-dsl.html

检索选型

​

检索分类

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自定义评分

如何自定义评分

​

1.index Boost索引层面修改相关性

// 一批数据里，有不同的标签，数据结构一致，不同的标签存储到不同的索引（A、B、C），最后要严格按照标签来分类展示的话，用什么查询比较好?// 要求：先展示A类，然后B类，然后C类# 测试数据如下put /index_a_123/_doc/1{  "title":"this is index_a..."}put /index_b_123/_doc/1{  "title":"this is index_b..."}put /index_c_123/_doc/1{  "title":"this is index_c..."}# 普通不指定的查询方式，该查询方式下，返回的三条结果数据评分是相同的POST index_*_123/_search{  "query": {    "bool": {      "must": [        {          "match": {            "title": "this"          }        }      ]    }  }}官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-search.htmlindices_boost# 也就是索引层面提升权重POST index_*_123/_search{  "indices_boost": [    {      "index_a_123": 10    },    {      "index_b_123": 5    },    {      "index_c_123": 1    }  ],   "query": {    "bool": {      "must": [        {          "match": {            "title": "this"          }        }      ]    }  }}

2.boosting 修改文档相关性

某索引index_a有多个字段， 要求实现如下的查询：1）针对字段title，满足"ssas"或者"sasa’。2）针对字段tags（数组字段），如果tags字段包含"pingpang",则提升评分。要求：写出实现的DSL？# 测试数据如下put index_a/_bulk{"index":{"_id":1}}{"title":"ssas","tags":"basketball"}{"index":{"_id":2}}{"title":"sasa","tags":"pingpang; football"}# 解法1POST index_a/_search{  "query": {    "bool": {      "must": [        {          "bool": {            "should": [              {                "match": {                  "title": "ssas"                }              },              {                "match": {                  "title": "sasa"                }              }            ]          }        }      ],      "should": [        {          "match": {            "tags": {              "query": "pingpang",              "boost": 1            }                      }        }      ]    }  }}# 解法2// https://www.elastic.co/guide/en/elasticsearch/reference/8.1/query-dsl-function-score-query.htmlPOST index_a/_search{  "query": {    "bool": {      "should": [        {          "function_score": {            "query": {              "match": {                "tags": {                  "query": "pingpang"                }              }            },            "boost": 1          }        }      ],      "must": [        {          "bool": {            "should": [              {                "match": {                  "title": "ssas"                }              },              {                "match": {                  "title": "sasa"                }              }            ]          }        }      ]    }  }}

3.negative_boost降低相关性

对于某些结果不满意，但又不想通过 must_not 排除掉，可以考虑可以考虑boosting query的negative_boost。即：降低评分negative_boost(Required, float) Floating point number between 0 and 1.0 used to decrease the relevance scores of documents matching the negative query.官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/query-dsl-boosting-query.htmlPOST index_a/_search{  "query": {    "boosting": {      "positive": {        "term": {          "tags": "football"        }      },      "negative": {        "term": {          "tags": "pingpang"        }      },      "negative_boost": 0.5    }  }}

4.function_score 自定义评分

如何同时根据 销量和浏览人数进行相关度提升？问题描述：针对商品，例如有想要有一个提升相关度的计算，同时针对销量和浏览人数？例如oldScore*(销量+浏览人数)**************************  商品        销量        浏览人数  A         10           10      B         20           20C         30           30************************** # 示例数据如下    put goods_index/_bulk{"index":{"_id":1}}{"name":"A","sales_count":10,"view_count":10}{"index":{"_id":2}}{"name":"B","sales_count":20,"view_count":20}{"index":{"_id":3}}{"name":"C","sales_count":30,"view_count":30}官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/query-dsl-function-score-query.html知识点：script_scorePOST goods_index/_search{  "query": {    "function_score": {      "query": {        "match_all": {}      },      "script_score": {        "script": {          "source": "_score * (doc["sales_count"].value+doc["view_count"].value)"        }      }    }  }}

十五.Search-del Bool复杂检索

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/query-dsl-bool-query.html

基本语法

​

真题演练

写一个查询，要求某个关键字再文档的四个字段中至少包含两个以上功能点：bool 查询，should / minimum_should_match    1.检索的bool查询    2.细节点 minimum_should_match注意：minimum_should_match 当有其他子句的时候，默认值为0，当没有其他子句的时候默认值为1POST test_index/_search{  "query": {    "bool": {      "should": [        {          "match": {            "filed1": "kr"          }        },        {          "match": {            "filed2": "kr"          }        },        {          "match": {            "filed3": "kr"          }        },        {          "match": {            "filed4": "kr"          }        }      ],      "minimum_should_match": 2    }  }}

十六.Search-Aggregations

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations.html

聚合分类

​

​

分桶聚合（bucket）

terms

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-bucket-terms-aggregation.html# 按照作者统计文档数POST bilili_elasticsearch/_search{  "size": 0,  "aggs": {    "agg_user": {      "terms": {        "field": "user",        "size": 1      }    }  }}

date_histogram

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-bucket-datehistogram-aggregation.html# 按照up_time 按月进行统计POST bilili_elasticsearch/_search{  "size": 0,  "aggs": {    "agg_up_time": {      "date_histogram": {        "field": "up_time",        "calendar_interval": "month"      }    }  }}

指标聚合 （metrics）

Max

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-metrics-max-aggregation.html# 获取up_time最大的POST bilili_elasticsearch/_search{  "size": 0,  "aggs": {    "agg_max_up_time": {      "max": {        "field": "up_time"      }    }  }}

Top_hits

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-metrics-top-hits-aggregation.html# 根据user聚合只取一个聚合结果，并且获取命中数据的详情前3条，并按照指定字段排序POST bilili_elasticsearch/_search{  "size": 0,  "aggs": {    "terms_agg_user": {      "terms": {        "field": "user",        "size": 1      },      "aggs": {        "top_user_hits": {          "top_hits": {            "_source": {              "includes": [                "video_time",                "title",                "see",                "user",                "up_time"              ]            },             "sort": [              {                "see":{                  "order": "desc"                }              }            ],             "size": 3          }        }      }    }  }}// 返回结果如下{  "took" : 91,  "timed_out" : false,  "_shards" : {    "total" : 1,    "successful" : 1,    "skipped" : 0,    "failed" : 0  },  "hits" : {    "total" : {      "value" : 1000,      "relation" : "eq"    },    "max_score" : null,    "hits" : [ ]  },  "aggregations" : {    "terms_agg_user" : {      "doc_count_error_upper_bound" : 0,      "sum_other_doc_count" : 975,      "buckets" : [        {          "key" : "Elastic搜索",          "doc_count" : 25,          "top_user_hits" : {            "hits" : {              "total" : {                "value" : 25,                "relation" : "eq"              },              "max_score" : null,              "hits" : [                {                  "_index" : "bilili_elasticsearch",                  "_id" : "5ccCVoQBUyqsIDX6wIcm",                  "_score" : null,                  "_source" : {                    "video_time" : "03:45",                    "see" : "92",                    "up_time" : "2021-03-19",                    "title" : "Elastic 社区大会2021: 用加 Gatling 进行Elasticsearch的负载测试，寓教于乐。",                    "user" : "Elastic搜索"                  },                  "sort" : [                    "92"                  ]                },                {                  "_index" : "bilili_elasticsearch",                  "_id" : "8scCVoQBUyqsIDX6wIgn",                  "_score" : null,                  "_source" : {                    "video_time" : "10:18",                    "see" : "79",                    "up_time" : "2020-10-20",                    "title" : "为Elasticsearch启动htpps访问",                    "user" : "Elastic搜索"                  },                  "sort" : [                    "79"                  ]                },                {                  "_index" : "bilili_elasticsearch",                  "_id" : "7scCVoQBUyqsIDX6wIcm",                  "_score" : null,                  "_source" : {                    "video_time" : "04:41",                    "see" : "71",                    "up_time" : "2021-03-19",                    "title" : "Elastic 社区大会2021: Elasticsearch作为一个地理空间的数据库",                    "user" : "Elastic搜索"                  },                  "sort" : [                    "71"                  ]                }              ]            }          }        }      ]    }  }}

子聚合 （Pipeline）

Pipeline：基于聚合的聚合 官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-pipeline.html

bucket_selector

官网文档地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-pipeline-bucket-selector-aggregation.html

# 根据order_date按月分组，并且求销售总额大于1000POST kibana_sample_data_ecommerce/_search{  "size": 0,  "aggs": {    "date_his_aggs": {      "date_histogram": {        "field": "order_date",        "calendar_interval": "month"      },      "aggs": {        "sum_aggs": {          "sum": {            "field": "total_unique_products"          }        },        "sales_bucket_filter": {          "bucket_selector": {            "buckets_path": {              "totalSales": "sum_aggs"            },            "script": "params.totalSales > 1000"          }        }      }    }  }}

真题演练

earthquakes索引中包含了过去30个月的地震信息，请通过一句查询，获取以下信息l 过去30个月，每个月的平均 magl 过去30个月里，平均mag最高的一个月及其平均magl 搜索不能返回任何文档    max_bucket 官网地址：https://www.elastic.co/guide/en/elasticsearch/reference/8.1/search-aggregations-pipeline-max-bucket-aggregation.htmlPOST earthquakes/_search{  "size": 0,   "query": {    "range": {      "time": {        "gte": "now-30M/d",        "lte": "now"      }    }  },  "aggs": {    "agg_time_his": {      "date_histogram": {        "field": "time",        "calendar_interval": "month"      },      "aggs": {        "avg_aggs": {          "avg": {            "field": "mag"          }        }      }    },    "max_mag_sales": {      "max_bucket": {        "buckets_path": "agg_time_his>avg_aggs"       }    }  }}