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17830004266(重庆移动)
时间:2020-11-14 13:37 作者:admin610456
前言
本文主要给大家介绍了关于MongoDB中索引和explain使用的相关内容，分享出来供大家参考学习，下面话不多说了，来一起看看详细的介绍：
mongodb 索引使用
作用
索引通常能够极大的提高查询。 索引是一种数据结构，他搜集一个集合中文档特定字段的值。 B-Tree索引来实现。创建索引
db.collection.createIndex(keys, options)
keys
keys由文档字段和索引类型组成。如{"name":1} key 表示字段 value 1,-1 1表示升序，-1降序options
options 创建索引的选项。
查看索引
db.collection.getIndexes()
{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.userdatas" }, { "v" : 1, "key" : { "name" : 1 //索引字段 }, "name" : "name_1", //索引名称 "ns" : "leyue.userdatas" }删除索引
db.collection.dropIndex(index) 删除指定的索引。
db.collection.dropIndexes() 删除除了_id 以外的所有索引。
创建/查看/删除 示例
查看数据
db.userdatas.find(){ "_id" : ObjectId("597f357a09c84cf58880e412"), "name" : "u3", "age" : 32 }{ "_id" : ObjectId("597f357a09c84cf58880e411"), "name" : "u4", "age" : 30, "score" : [ 7, 4, 2, 0 ] }{ "_id" : ObjectId("597fcc0f411f2b2fd30d0b3f"), "age" : 20, "score" : [ 7, 4, 2, 0, 10, 9, 8, 7 ], "name" : "lihao" }{ "_id" : ObjectId("597f357a09c84cf58880e413"), "name" : "u2", "age" : 33, "wendang" : { "yw" : 80, "xw" : 90 } }{ "_id" : ObjectId("5983f5c88eec53fbcd56a7ca"), "date" : ISODate("2017-08-04T04:19:20.693Z") }{ "_id" : ObjectId("597f357a09c84cf58880e40e"), "name" : "u1", "age" : 26, "address" : "中国砀山" }{ "_id" : ObjectId("597f357a09c84cf58880e40f"), "name" : "u1", "age" : 37, "score" : [ 10, 203, 12, 43, 56, 22 ] }{ "_id" : ObjectId("597f357a09c84cf58880e410"), "name" : "u5", "age" : 78, "address" : "china beijing chaoyang" }给字段name 创建索引
// 创建索引 db.userdatas.createIndex({"name":1}) { "createdCollectionAutomatically" : false, "numIndexesBefore" : 1, "numIndexesAfter" : 2, "ok" : 1 } // 查看索引 db.userdatas.getIndexes() [ { "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.userdatas" }, { "v" : 1, "key" : { "name" : 1 }, "name" : "name_1", "ns" : "leyue.userdatas" } ]给字段name 创建索引并命名为myindex
db.userdatas.createIndex({"name":1}) db.userdatas.createIndex({"name":1},{"name":"myindex"}) db.userdatas.getIndexes() [ { "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.userdatas" }, { "v" : 1, "key" : { "name" : 1 }, "name" : "myindex", "ns" : "leyue.userdatas" } ]给字段name 创建索引 创建的过程在后台执行
当mongodb 集合里面的数据过大时 创建索引很耗时，可以在放在后台运行。
db.userdatas.dropIndex("myindex") db.userdatas.createIndex({"name":1},{"name":"myindex","background":true})给age 字段创建唯一索引
db.userdatas.createIndex({"age":-1},{"name":"ageIndex","unique":true,"sparse":true}) db.userdatas.getIndexes()[ { "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.userdatas" }, { "v" : 1, "key" : { "name" : 1 }, "name" : "myindex", "ns" : "leyue.userdatas", "background" : true }, { "v" : 1, "unique" : true, "key" : { "age" : -1 }, "name" : "ageIndex", "ns" : "leyue.userdatas", "sparse" : true }]// 插入一个已存在的age db.userdatas.insert({ "name" : "u8", "age" : 32})WriteResult({ "nInserted" : 0, "writeError" : { "code" : 11000, "errmsg" : "E11000 duplicate key error index: leyue.userdatas.$ageIndex dup key: { : 32.0 }" }})创建复合索引
db.userdatas.createIndex({"name":1,"age":-1}) db.userdatas.getIndexes()[ { "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.userdatas" }, { "v" : 1, "key" : { "name" : 1, "age" : -1 }, "name" : "name_1_age_-1", "ns" : "leyue.userdatas" }]所有的字段都存在集合 system.indexes 中
db.system.indexes.find(){ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.userdatas" }{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.scores" }{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.test" }{ "v" : 1, "key" : { "user" : 1, "name" : 1 }, "name" : "myindex", "ns" : "leyue.test" }{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "leyue.mycapped" }{ "v" : 1, "key" : { "user" : 1 }, "name" : "user_1", "ns" : "leyue.test" }{ "v" : 1, "key" : { "name" : 1 }, "name" : "myindex", "ns" : "leyue.userdatas" }索引总结
1:创建索引时,1表示按升序存储,-1表示按降序存储。
2:可以创建复合索引,如果想用到复合索引,必须在查询条件中包含复合索引中的前N个索引列
3: 如果查询条件中的键值顺序和复合索引中的创建顺序不一致的话,
MongoDB可以智能的帮助我们调整该顺序,以便使复合索引可以为查询所用。
4: 可以为内嵌文档创建索引,其规则和普通文档创建索引是一样的。
5: 一次查询中只能使用一个索引,$or特殊,可以在每个分支条件上使用一个索引。
6: $where,$exists不能使用索引,还有一些低效率的操作符,比如:$ne,$not,$nin等。
7: 设计多个字段的索引时,应该尽量将用于精确匹配的字段放在索引的前面。
explain 使用
语法
db.collection.explain().<method(...)>
explain() 可以设置参数 ：
queryPlanner。 executionStats。 allPlansExecution。示例
for(var i=0;i<100000;i++) { db.test.insert({"user":"user"+i});}没有使用索引
db.test.explain("executionStats").find({"user":"user200000"}){ "queryPlanner" : { "plannerVersion" : 1, "namespace" : "leyue.test", "indexFilterSet" : false, "parsedQuery" : { "user" : { "$eq" : "user200000" } }, "winningPlan" : { "stage" : "COLLSCAN", "filter" : { "user" : { "$eq" : "user200000" } }, "direction" : "forward" }, "rejectedPlans" : [ ] }, "executionStats" : { "executionSuccess" : true, "nReturned" : 2, "executionTimeMillis" : 326, "totalKeysExamined" : 0, "totalDocsExamined" : 1006497, "executionStages" : { "stage" : "COLLSCAN", "filter" : { "user" : { "$eq" : "user200000" } }, "nReturned" : 2, "executionTimeMillisEstimate" : 270, "works" : 1006499, "advanced" : 2, "needTime" : 1006496, "needYield" : 0, "saveState" : 7863, "restoreState" : 7863, "isEOF" : 1, "invalidates" : 0, "direction" : "forward", "docsExamined" : 1006497 } }, "serverInfo" : { "host" : "lihaodeMacBook-Pro.local", "port" : 27017, "version" : "3.2.1", "gitVersion" : "a14d55980c2cdc565d4704a7e3ad37e4e535c1b2" }, "ok" : 1} executionStats.executionTimeMillis: query的整体查询时间。 executionStats.nReturned : 查询返回的条目。 executionStats.totalKeysExamined ： 索引扫描条目。 executionStats.totalDocsExamined： 文档扫描条目。executionTimeMillis = 326 query 执行时间
nReturned=2 返回两条数据
totalKeysExamined=0 没有用到索引
totalDocsExamined 全文档扫描
理想状态：
nReturned=totalKeysExamined & totalDocsExamined=0
Stage状态分析
对于普通查询，我希望看到stage的组合(查询的时候尽可能用上索引)：
Fetch+IDHACK
Fetch+ixscan
Limit+（Fetch+ixscan）
PROJECTION+ixscan
SHARDING_FITER+ixscan
COUNT_SCAN
不希望看到包含如下的stage：
COLLSCAN(全表扫描),SORT(使用sort但是无index),不合理的SKIP,SUBPLA(未用到index的$or),COUNTSCAN(不使用index进行count)
使用索引
db.test.createIndex({"user":1},{"name":"myindex","background":true}) db.test.explain("executionStats").find({"user":"user200000"}){ "queryPlanner" : { "plannerVersion" : 1, "namespace" : "leyue.test", "indexFilterSet" : false, "parsedQuery" : { "user" : { "$eq" : "user200000" } }, "winningPlan" : { "stage" : "FETCH", "inputStage" : { "stage" : "IXSCAN", "keyPattern" : { "user" : 1 }, "indexName" : "myindex", "isMultiKey" : false, "isUnique" : false, "isSparse" : false, "isPartial" : false, "indexVersion" : 1, "direction" : "forward", "indexBounds" : { "user" : [ "[\"user200000\", \"user200000\"]" ] } } }, "rejectedPlans" : [ ] }, "executionStats" : { "executionSuccess" : true, "nReturned" : 2, "executionTimeMillis" : 0, "totalKeysExamined" : 2, "totalDocsExamined" : 2, "executionStages" : { "stage" : "FETCH", "nReturned" : 2, "executionTimeMillisEstimate" : 0, "works" : 3, "advanced" : 2, "needTime" : 0, "needYield" : 0, "saveState" : 0, "restoreState" : 0, "isEOF" : 1, "invalidates" : 0, "docsExamined" : 2, "alreadyHasObj" : 0, "inputStage" : { "stage" : "IXSCAN", "nReturned" : 2, "executionTimeMillisEstimate" : 0, "works" : 3, "advanced" : 2, "needTime" : 0, "needYield" : 0, "saveState" : 0, "restoreState" : 0, "isEOF" : 1, "invalidates" : 0, "keyPattern" : { "user" : 1 }, "indexName" : "myindex", "isMultiKey" : false, "isUnique" : false, "isSparse" : false, "isPartial" : false, "indexVersion" : 1, "direction" : "forward", "indexBounds" : { "user" : [ "[\"user200000\", \"user200000\"]" ] }, "keysExamined" : 2, "dupsTested" : 0, "dupsDropped" : 0, "seenInvalidated" : 0 } } }, "serverInfo" : { "host" : "lihaodeMacBook-Pro.local", "port" : 27017, "version" : "3.2.1", "gitVersion" : "a14d55980c2cdc565d4704a7e3ad37e4e535c1b2" }, "ok" : 1}executionTimeMillis: 0
totalKeysExamined: 2
totalDocsExamined:2
nReturned:2
stage:IXSCAN
使用索引和不使用差距很大，合理使用索引，一个集合适合做 4-5 个索引。
总结
以上就是这篇文章的全部内容了，希望本文的内容对大家的学习或者工作能带来一定的帮助，如果有疑问大家可以留言交流，谢谢大家对脚本之家的支持。
相关文章
http://www.mongoing.com/eshu_explain3
https://docs.mongodb.com/v3.2/reference/explain-results/#queryplanner
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