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MongoDB中索引的示例分析

发表于:2025-11-10 作者:千家信息网编辑
千家信息网最后更新 2025年11月10日,这篇文章主要介绍MongoDB中索引的示例分析,文中介绍的非常详细,具有一定的参考价值,感兴趣的小伙伴们一定要看完!一、索引究竟是什么东西?大部分开发者接触索引,大概知道索引类似书的目录,你要找到想要
千家信息网最后更新 2025年11月10日MongoDB中索引的示例分析

这篇文章主要介绍MongoDB中索引的示例分析,文中介绍的非常详细,具有一定的参考价值,感兴趣的小伙伴们一定要看完!

一、索引究竟是什么东西?

大部分开发者接触索引,大概知道索引类似书的目录,你要找到想要的内容,通过目录找到限定的关键字,进而找到对应的章节的pageno,再找到具体的内容。
在数据结构里面,最简单的索引实现类似hashmap,通过关键字key,映射到具体的位置,找到具体的内容。但除了hash的方式,还有多种的方式实现索引。

(一)索引的多种实现方式以及特色

hash / b-tree / b+-tree redis HSET / MongoDB&PostgreSQL / MySQL

hashmap

一图见b-tree & b+-tree 差别:

  • b+-tree 叶子存数据,非叶子存索引,不存数据,叶子间有link

  • b-tree 非叶子可存数据

算法查找复杂度上来说:

  • hash 接近O(1)

  • b-tree O(1)~ O(Log(n))更快的平均查找时间,不稳定的查询时间

  • b+ tree O(Log(n)) 连续数据, 查询的稳定性

至于为何MongoDB 的实现选择b-tree 而非 b+-tree ?
网上多篇文章有阐述,非本文重点。

(二)数据&索引的存储

index尽量存储在内存,data 其次。
注意只保留必要的index,内存尽量用在刀刃上。
如果index memory 都接近占满memory,那么就很容易读到disk,速度就下来了。

(三)知道索引的实现&存储原理后的思考

insert/update/delete 会触发rebalance tree,所以,增删改数据,索引会触发修改,性能会有损耗,索引不是越多越好。既然如此,选哪些字段作为索引呢?当查询用到这些条件,怎么办?
拿一个最简单的hashmap来讲,为什么复杂度不是O(1),而是所谓接近 O(1)。因为有key 冲突/重复,DB 去找的时候,key 冲突的数据一大堆的话,还是得轮着继续找。b-tree 看键(key)的选择也是如此。
因此一个大部分开发经常犯的错就是对没有区分度的key建索引。例如:很多就只有集中类别的 type/status 的 documents count 达几十万以上的collection,通常这种索引没什么帮助。

二、复合索引

(一)复合索引不是越多越好

如果不想多建多余的索引,开发的同事在复合 & 单个字段选择上有时候挺纠结的。 根据典型碰到的场景,来做几个实验:
这里创建了个loans collection。简化只有100条数据。这个是借贷的表有 _id, userId, status(借贷状态), amount(金额).

db.loans.count()100

db.loans.find({ "userId" : "59e022d33f239800129c61c7", "status" : "repayed", }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "$and" : [   {     "status" : {       "$eq" : "repayed"     }   },   {     "userId" : {       "$eq" : "59e022d33f239800129c61c7"     }   } ]},"queryHash" : "15D5A9A1","planCacheKey" : "15D5A9A1","winningPlan" : { "stage" : "COLLSCAN", "filter" : {   "$and" : [     {       "status" : {         "$eq" : "repayed"       }     },     {       "userId" : {         "$eq" : "59e022d33f239800129c61c7"       }     }   ] }, "direction" : "forward"},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

注意上面 COLLSCAN 全表扫描了,因为没有索引。接下来我们分别建立几个索引。
step 1 先建立 {userId:1, status:1}

db.loans.createIndex({userId:1, status:1}){"createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1}
db.loans.find({ "userId" : "59e022d33f239800129c61c7", "status" : "repayed", }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "$and" : [   {     "status" : {       "$eq" : "repayed"     }   },   {     "userId" : {       "$eq" : "59e022d33f239800129c61c7"     }   } ]},"queryHash" : "15D5A9A1","planCacheKey" : "BB87F2BA","winningPlan" : { "stage" : "FETCH", "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "userId" : 1,     "status" : 1   },   "indexName" : "userId_1_status_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "userId" : [ ],     "status" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "userId" : [       "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"     ],     "status" : [       "["repayed", "repayed"]"     ]   } }},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

结果:如愿命中 {userId:1, status:1} 作为 winning plan。

step2:再建立个典型的索引 userId

db.loans.createIndex({userId:1}){"createdCollectionAutomatically" : false,"numIndexesBefore" : 2,"numIndexesAfter" : 3,"ok" : 1}
db.loans.find({ "userId" : "59e022d33f239800129c61c7", "status" : "repayed", }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "$and" : [   {     "status" : {       "$eq" : "repayed"     }   },   {     "userId" : {       "$eq" : "59e022d33f239800129c61c7"     }   } ]},"queryHash" : "15D5A9A1","planCacheKey" : "1B1A4861","winningPlan" : { "stage" : "FETCH", "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "userId" : 1,     "status" : 1   },   "indexName" : "userId_1_status_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "userId" : [ ],     "status" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "userId" : [       "[\"59e022d33f239800129c61c7\", \"59e022d33f239800129c61c7\"]"     ],     "status" : [       "[\"repayed\", \"repayed\"]"     ]   } }},"rejectedPlans" : [ {   "stage" : "FETCH",   "filter" : {     "status" : {       "$eq" : "repayed"     }   },   "inputStage" : {     "stage" : "IXSCAN",     "keyPattern" : {       "userId" : 1     },     "indexName" : "userId_1",     "isMultiKey" : false,     "multiKeyPaths" : {       "userId" : [ ]     },     "isUnique" : false,     "isSparse" : false,     "isPartial" : false,     "indexVersion" : 2,     "direction" : "forward",     "indexBounds" : {       "userId" : [         "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"       ]     }   } }]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

留意到 DB 检测到 {userId:1, status:1} 为更优执行的方案.

db.loans.find({ "userId" : "59e022d33f239800129c61c7" }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "userId" : {   "$eq" : "59e022d33f239800129c61c7" }},"queryHash" : "B1777DBA","planCacheKey" : "1F09D68E","winningPlan" : { "stage" : "FETCH", "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "userId" : 1   },   "indexName" : "userId_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "userId" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "userId" : [       "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"     ]   } }},"rejectedPlans" : [ {   "stage" : "FETCH",   "inputStage" : {     "stage" : "IXSCAN",     "keyPattern" : {       "userId" : 1,       "status" : 1     },     "indexName" : "userId_1_status_1",     "isMultiKey" : false,     "multiKeyPaths" : {       "userId" : [ ],       "status" : [ ]     },     "isUnique" : false,     "isSparse" : false,     "isPartial" : false,     "indexVersion" : 2,     "direction" : "forward",     "indexBounds" : {       "userId" : [         "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"       ],       "status" : [         "[MinKey, MaxKey]"       ]     }   } }]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

留意到 DB 检测到 {userId:1} 为更优执行的方案,嗯~,如我们所料.

db.loans.find({ "status" : "repayed" }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "status" : {   "$eq" : "repayed" }},"queryHash" : "E6304EB6","planCacheKey" : "7A94191B","winningPlan" : { "stage" : "COLLSCAN", "filter" : {   "status" : {     "$eq" : "repayed"   } }, "direction" : "forward"},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

有趣的部分:status不命中索引,全表扫描
接下来的步骤,加个sort :

db.loans.find({ "userId" : "59e022d33f239800129c61c7" }).sort({status:1}).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "userId" : {   "$eq" : "59e022d33f239800129c61c7" }},"queryHash" : "F5ABB1AA","planCacheKey" : "764CBAA8","winningPlan" : { "stage" : "FETCH", "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "userId" : 1,     "status" : 1   },   "indexName" : "userId_1_status_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "userId" : [ ],     "status" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "userId" : [       "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"     ],     "status" : [       "[MinKey, MaxKey]"     ]   } }},"rejectedPlans" : [ {   "stage" : "SORT",   "sortPattern" : {     "status" : 1   },   "inputStage" : {     "stage" : "SORT_KEY_GENERATOR",     "inputStage" : {       "stage" : "FETCH",       "inputStage" : {         "stage" : "IXSCAN",         "keyPattern" : {           "userId" : 1         },         "indexName" : "userId_1",         "isMultiKey" : false,         "multiKeyPaths" : {           "userId" : [ ]         },         "isUnique" : false,         "isSparse" : false,         "isPartial" : false,         "indexVersion" : 2,         "direction" : "forward",         "indexBounds" : {           "userId" : [             "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"           ]         }       }     }   } }]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}
(二)其他尝试

有趣的部分:status 不命中索引

db.loans.find({ "status" : "repayed","userId" : "59e022d33f239800129c61c7", }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "$and" : [   {     "status" : {       "$eq" : "repayed"     }   },   {     "userId" : {       "$eq" : "59e022d33f239800129c61c7"     }   } ]},"queryHash" : "15D5A9A1","planCacheKey" : "1B1A4861","winningPlan" : { "stage" : "FETCH", "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "userId" : 1,     "status" : 1   },   "indexName" : "userId_1_status_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "userId" : [ ],     "status" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "userId" : [       "[\"59e022d33f239800129c61c7\", \"59e022d33f239800129c61c7\"]"     ],     "status" : [       "[\"repayed\", \"repayed\"]"     ]   } }},"rejectedPlans" : [ {   "stage" : "FETCH",   "filter" : {     "status" : {       "$eq" : "repayed"     }   },   "inputStage" : {     "stage" : "IXSCAN",     "keyPattern" : {       "userId" : 1     },     "indexName" : "userId_1",     "isMultiKey" : false,     "multiKeyPaths" : {       "userId" : [ ]     },     "isUnique" : false,     "isSparse" : false,     "isPartial" : false,     "indexVersion" : 2,     "direction" : "forward",     "indexBounds" : {       "userId" : [         "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"       ]     }   } }]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

命中索引,跟query的各个字段顺序不相关,如我们猜测。
有趣部分再来, 我们删掉索引{userId:1}

db.loans.dropIndex({"userId":1}){ "nIndexesWas" : 3, "ok" : 1 }db.loans.find({"userId" : "59e022d33f239800129c61c7", }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "userId" : {   "$eq" : "59e022d33f239800129c61c7" }},"queryHash" : "B1777DBA","planCacheKey" : "5776AB9C","winningPlan" : { "stage" : "FETCH", "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "userId" : 1,     "status" : 1   },   "indexName" : "userId_1_status_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "userId" : [ ],     "status" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "userId" : [       "["59e022d33f239800129c61c7", "59e022d33f239800129c61c7"]"     ],     "status" : [       "[MinKey, MaxKey]"     ]   } }},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

DB 执行分析器觉得索引{userId:1, status:1} 能更优,没有命中复合索引,这个是因为status不是leading field。

db.loans.find({ "status" : "repayed" }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "status" : {   "$eq" : "repayed" }},"queryHash" : "E6304EB6","planCacheKey" : "7A94191B","winningPlan" : { "stage" : "COLLSCAN", "filter" : {   "status" : {     "$eq" : "repayed"   } }, "direction" : "forward"},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

再换个角度sort 一遍, 与前面query & sort互换,之前是:

db.loans.find({userId:1}).sort({ "status" : "repayed" })

看看有啥不一样?

db.loans.find({ "status" : "repayed" }).sort({userId:1}).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "status" : {   "$eq" : "repayed" }},"queryHash" : "56EA6313","planCacheKey" : "2CFCDA7F","winningPlan" : { "stage" : "FETCH", "filter" : {   "status" : {     "$eq" : "repayed"   } }, "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "userId" : 1,     "status" : 1   },   "indexName" : "userId_1_status_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "userId" : [ ],     "status" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "userId" : [       "[MinKey, MaxKey]"     ],     "status" : [       "[MinKey, MaxKey]"     ]   } }},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

如猜测,命中索引。
再来玩玩,确认下leading filed试验:

db.loans.dropIndex("userId_1_status_1"){ "nIndexesWas" : 2, "ok" : 1 }
db.loans.getIndexes()[{"v" : 2,"key" : { "id" : 1},"name" : "id_","ns" : "cashLoan.loans"}]
db.loans.createIndex({status:1, userId:1}){"createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1}
db.loans.getIndexes()[{"v" : 2,"key" : { "id" : 1},"name" : "id_","ns" : "cashLoan.loans"},{"v" : 2,"key" : { "status" : 1, "userId" : 1},"name" : "status_1_userId_1","ns" : "cashLoan.loans"}]
db.loans.find({ "status" : "repayed" }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "status" : {   "$eq" : "repayed" }},"queryHash" : "E6304EB6","planCacheKey" : "7A94191B","winningPlan" : { "stage" : "FETCH", "inputStage" : {   "stage" : "IXSCAN",   "keyPattern" : {     "status" : 1,     "userId" : 1   },   "indexName" : "status_1_userId_1",   "isMultiKey" : false,   "multiKeyPaths" : {     "status" : [ ],     "userId" : [ ]   },   "isUnique" : false,   "isSparse" : false,   "isPartial" : false,   "indexVersion" : 2,   "direction" : "forward",   "indexBounds" : {     "status" : [       "["repayed", "repayed"]"     ],     "userId" : [       "[MinKey, MaxKey]"     ]   } }},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}
db.loans.getIndexes()[{"v" : 2,"key" : { "id" : 1},"name" : "id_","ns" : "cashLoan.loans"},{"v" : 2,"key" : { "status" : 1, "userId" : 1},"name" : "status_1_userId_1","ns" : "cashLoan.loans"}]
db.loans.find({"userId" : "59e022d33f239800129c61c7", }).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "cashLoan.loans","indexFilterSet" : false,"parsedQuery" : { "userId" : {   "$eq" : "59e022d33f239800129c61c7" }},"queryHash" : "B1777DBA","planCacheKey" : "5776AB9C","winningPlan" : { "stage" : "COLLSCAN", "filter" : {   "userId" : {     "$eq" : "59e022d33f239800129c61c7"   } }, "direction" : "forward"},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "RMBAP","port" : 27017,"version" : "4.1.11","gitVersion" : "1b8a9f5dc5c3314042b55e7415a2a25045b32a94"},"ok" : 1}

看完这个试验,明白了 {userId:1, status:1} vs {status:1,userId:1} 的差别了吗?

PS:这个case 里面其实status 区分度不高,这里只是作为实例展示。

三、总结:

  • 注意使用上、使用频率上、区分高的/常用的在前面;

  • 如果需要减少索引以节省memory/提高修改数据的性能的话,可以保留区分度高,常用的,去除区分度不高,不常用的索引。

  • 学会用explain()验证分析性能:

DB 一般都有执行器优化的分析,MySQL & MongoDB 都是 用explain 来做分析。
语法上MySQL :

explain your_sql

MongoDB:

yoursql.explain()

总结典型:理想的查询是结合explain 的指标,他们通常是多个的混合:

  • IXSCAN : 索引命中;

  • Limit : 带limit;

  • Projection : 相当于非 select * ;

  • Docs Size less is better ;

  • Docs Examined less is better ;

  • nReturned=totalDocsExamined=totalKeysExamined ;

  • SORT in index :sort 也是命中索引,否则,需要拿到数据后,再执行一遍排序;

  • Limit Array elements : 限定数组返回的条数,数组也不应该太多数据,否则schema 设计不合理。

以上是"MongoDB中索引的示例分析"这篇文章的所有内容,感谢各位的阅读!希望分享的内容对大家有帮助,更多相关知识,欢迎关注行业资讯频道!

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