索引简介

环境准备

索引操作

创建普通索引

查看索引信息

删除索引

创建唯一索引

explain 工具

索引简介

1、索引是用来加速查询的，实际项目中，需要对哪些字段进行快速检索，则可以为这些字段建立索引！

2、数据库索引与书籍的索引类似：有了索引就不需要翻遍整本书，数据库则可以直接在索引中查找，使得查找速度能提高几个数量级。在索引中找到条目以后，就可以直接跳转到目标文档的位置。

环境准备

1、既然索引是为了提高检索速度的，本文将新建一个数据库 mydb2，创建一个集合 c1、然后往里面添加五百万条数据，接着查询其中的某一条数据需要花费多少时间，然后为它建立索引之后再次检索，看花费多少时间。

2、先启动 MongoDB 数据库：mongod --dbpath=D:\MongoDB\Data

3、客户端连接 MongoDB 数据库：mongo ，这些操作不熟悉的可以从参考《MongoDB 下载_安装_配置及启动与连接》

4、如下所示，创建数据库 mydb2，往集合 c1 中插入 5 百万条数据，Win10 64位系统 8G内存，插入操作执行了约 20分钟。

> show dbs
admin   0.000GB
config  0.000GB
local   0.000GB
mydb1   0.000GB
> use mydb2
switched to db mydb2
> for(var i=0;i<5000000;i++){
... db.c1.insert({name:"华安"+i,age:i});
... }
WriteResult({ "nInserted" : 1 })
>

5、如下所示，可以再新开一个 cmd 窗口，然后连接 MongoDB 数据库，实时查看数据插入的情况。

> use mydb2
switched to db mydb2
> show tables
c1
> db.c1.find().count()
308624
> db.c1.find().count()
311139
> db.c1.find().count()
314849
> db.c1.find().count()
411957
> db.c1.find().count()
432314
> db.c1.find().count()
505586
> db.c1.find().count()
625517
> db.c1.find().count()
632710
> db.c1.find().count()
1817546
> db.c1.find().count()
4301947
> db.c1.find().count()
5000000
> db.c1.find().count()
5000000
> db.c1.find().count()
5000000
>

6、如下所示，此时查询时，它会扫描整个 c1 集合中的 5百万条数据，检索 name 等于 "华安500" 的时间约 2346 豪秒

7、后面的索引操作部分会为 age 字段创建索引，然后再次检索进行对比。

8、explain("executionStats") 方法可以看到检索的详细信息，后面会详细介绍

9、executionTimeMillis 表示检索耗费的时间(毫秒)

10、totalDocsExamined 表示扫描的总文档数

> db.c1.find({age:500})
{ "_id" : ObjectId("5b98716247640bc808f6ef2d"), "name" : "华安500", "age" : 500 }
> db.c1.find({name:"华安500"}).explain("executionStats");
{"queryPlanner" : {"plannerVersion" : 1,"namespace" : "mydb2.c1","indexFilterSet" : false,"parsedQuery" : {"name" : {"$eq" : "华安500"}},"winningPlan" : {"stage" : "COLLSCAN","filter" : {"name" : {"$eq" : "华安500"}},"direction" : "forward"},"rejectedPlans" : [ ]},"executionStats" : {"executionSuccess" : true,"nReturned" : 1,"executionTimeMillis" : 2346,"totalKeysExamined" : 0,"totalDocsExamined" : 5000000,"executionStages" : {"stage" : "COLLSCAN","filter" : {"name" : {"$eq" : "华安500"}},"nReturned" : 1,"executionTimeMillisEstimate" : 2113,"works" : 5000002,"advanced" : 1,"needTime" : 5000000,"needYield" : 0,"saveState" : 39154,"restoreState" : 39154,"isEOF" : 1,"invalidates" : 0,"direction" : "forward","docsExamined" : 5000000}},"serverInfo" : {"host" : "SC-201707281232","port" : 27017,"version" : "4.0.2-rc0","gitVersion" : "fc1573ba18aee42f97a3bb13b67af7d837826b47"},"ok" : 1
}
>

索引操作

创建普通索引：db.collection.ensureIndex({key:1})

创建唯一索引：db.collection.ensureIndex({key:1}，{unique:true})

查看关于索引的相关信息：db.collection.stats()

查看查询使用索引的情况：db.collection.find({key:value}).explain()

删除索引：db.collection.dropIndex({key:1})

删除集合，也会将集合中的索引全部删除

创建普通索引

1、创建普通索引：db.collection.ensureIndex({key:1})

2、如下所示，为 age 字段创建普通索引成功（说明：本文使用 MongoDB 4.0.2 版本）

> db.c1.ensureIndex({age:1})
{"createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1
}

MongoDB 客户端运行创建索引的命令后，在 MongoDB 服务端 cmd 面板中会看到执行的进度信息，如下所示就是索引构建的进度，耗时 14 秒构建完成 5百万条文档的索引

2018-09-12T10:34:44.562+0800 I INDEX    [conn1]          building index using bulk method; build may temporarily use up to 500 megabytes of RAM
2018-09-12T10:34:47.000+0800 I -        [conn1]   Index Build: 1457800/5000000 29%
2018-09-12T10:34:50.000+0800 I -        [conn1]   Index Build: 3314600/5000000 66%
2018-09-12T10:34:58.882+0800 I INDEX    [conn1] build index done.  scanned 5000000 total records. 14 secs

如下所示，为 age 字段构建了索引之后，再次查询 age 字段时，完全是秒查。

通过 explain("executionStats") 方法可以看到

executionTimeMillis : 0，即检索时间为 0秒，完全秒查

totalDocsExamined : 1，即扫描的文档总数为1，因为有索引，根据索引可以直接找到文档。

> db.c1.find({age:1000});
{ "_id" : ObjectId("5b98716347640bc808f6f121"), "name" : "华安1000", "age" : 1000 }
> db.c1.find({age:1000}).explain("executionStats");
{"queryPlanner" : {"plannerVersion" : 1,"namespace" : "mydb2.c1","indexFilterSet" : false,"parsedQuery" : {"age" : {"$eq" : 1000}},"winningPlan" : {"stage" : "FETCH","inputStage" : {"stage" : "IXSCAN","keyPattern" : {"age" : 1},"indexName" : "age_1","isMultiKey" : false,"multiKeyPaths" : {"age" : [ ]},"isUnique" : false,"isSparse" : false,"isPartial" : false,"indexVersion" : 2,"direction" : "forward","indexBounds" : {"age" : ["[1000.0, 1000.0]"]}}},"rejectedPlans" : [ ]},"executionStats" : {"executionSuccess" : true,"nReturned" : 1,"executionTimeMillis" : 0,"totalKeysExamined" : 1,"totalDocsExamined" : 1,"executionStages" : {"stage" : "FETCH","nReturned" : 1,"executionTimeMillisEstimate" : 0,"works" : 2,"advanced" : 1,"needTime" : 0,"needYield" : 0,"saveState" : 0,"restoreState" : 0,"isEOF" : 1,"invalidates" : 0,"docsExamined" : 1,"alreadyHasObj" : 0,"inputStage" : {"stage" : "IXSCAN","nReturned" : 1,"executionTimeMillisEstimate" : 0,"works" : 2,"advanced" : 1,"needTime" : 0,"needYield" : 0,"saveState" : 0,"restoreState" : 0,"isEOF" : 1,"invalidates" : 0,"keyPattern" : {"age" : 1},"indexName" : "age_1","isMultiKey" : false,"multiKeyPaths" : {"age" : [ ]},"isUnique" : false,"isSparse" : false,"isPartial" : false,"indexVersion" : 2,"direction" : "forward","indexBounds" : {"age" : ["[1000.0, 1000.0]"]},"keysExamined" : 1,"seeks" : 1,"dupsTested" : 0,"dupsDropped" : 0,"seenInvalidated" : 0}}},"serverInfo" : {"host" : "SC-201707281232","port" : 27017,"version" : "4.0.2-rc0","gitVersion" : "fc1573ba18aee42f97a3bb13b67af7d837826b47"},"ok" : 1
}
>

查看索引信息

1、查看关于索引的相关信息：db.collection.stats()

2、查看查询使用索引的情况：db.collection.find({key:value}).explain()

> db.c1.stats()
{"ns" : "mydb2.c1","size" : 293888890,"count" : 5000000,"avgObjSize" : 58,"storageSize" : 93253632,"capped" : false,"wiredTiger" : {"metadata" : {"formatVersion" : 1},"creationString" : "access_pattern_hint=none,allocation_size=4KB,app_metadata=(formatVersion=1),assert=(commit_timestamp=none,read_timestamp=none),block_allocation=best,block_compressor=snappy,cache_resident=false,checksum=on,colgroups=,collator=,columns=,dictionary=0,encryption=(keyid=,name=),exclusive=false,extractor=,format=btree,huffman_key=,huffman_value=,ignore_in_memory_cache_size=false,immutable=false,internal_item_max=0,internal_key_max=0,internal_key_truncate=true,internal_page_max=4KB,key_format=q,key_gap=10,leaf_item_max=0,leaf_key_max=0,leaf_page_max=32KB,leaf_value_max=64MB,log=(enabled=true),lsm=(auto_throttle=true,bloom=true,bloom_bit_count=16,bloom_config=,bloom_hash_count=8,bloom_oldest=false,chunk_count_limit=0,chunk_max=5GB,chunk_size=10MB,merge_custom=(prefix=,start_generation=0,suffix=),merge_max=15,merge_min=0),memory_page_image_max=0,memory_page_max=10m,os_cache_dirty_max=0,os_cache_max=0,prefix_compression=false,prefix_compression_min=4,source=,split_deepen_min_child=0,split_deepen_per_child=0,split_pct=90,type=file,value_format=u","type" : "file","uri" : "statistics:table:collection-0-7507112370645922167","LSM" : {"bloom filter false positives" : 0,"bloom filter hits" : 0,"bloom filter misses" : 0,"bloom filter pages evicted from cache" : 0,"bloom filter pages read into cache" : 0,"bloom filters in the LSM tree" : 0,"chunks in the LSM tree" : 0,"highest merge generation in the LSM tree" : 0,"queries that could have benefited from a Bloom filter that did not exist" : 0,"sleep for LSM checkpoint throttle" : 0,"sleep for LSM merge throttle" : 0,"total size of bloom filters" : 0},"block-manager" : {"allocations requiring file extension" : 11465,"blocks allocated" : 11560,"blocks freed" : 73,"checkpoint size" : 93204480,"file allocation unit size" : 4096,"file bytes available for reuse" : 32768,"file magic number" : 120897,"file major version number" : 1,"file size in bytes" : 93253632,"minor version number" : 0},"btree" : {"btree checkpoint generation" : 100,"column-store fixed-size leaf pages" : 0,"column-store internal pages" : 0,"column-store variable-size RLE encoded values" : 0,"column-store variable-size deleted values" : 0,"column-store variable-size leaf pages" : 0,"fixed-record size" : 0,"maximum internal page key size" : 368,"maximum internal page size" : 4096,"maximum leaf page key size" : 2867,"maximum leaf page size" : 32768,"maximum leaf page value size" : 67108864,"maximum tree depth" : 3,"number of key/value pairs" : 0,"overflow pages" : 0,"pages rewritten by compaction" : 0,"row-store internal pages" : 0,"row-store leaf pages" : 0},"cache" : {"bytes currently in the cache" : 683932272,"bytes read into cache" : 0,"bytes written from cache" : 325368864,"checkpoint blocked page eviction" : 0,"data source pages selected for eviction unable to be evicted" : 0,"eviction walk passes of a file" : 0,"eviction walk target pages histogram - 0-9" : 0,"eviction walk target pages histogram - 10-31" : 0,"eviction walk target pages histogram - 128 and higher" : 0,"eviction walk target pages histogram - 32-63" : 0,"eviction walk target pages histogram - 64-128" : 0,"eviction walks abandoned" : 0,"eviction walks gave up because they restarted their walk twice" : 0,"eviction walks gave up because they saw too many pages and found no candidates" : 0,"eviction walks gave up because they saw too many pages and found too few candidates" : 0,"eviction walks reached end of tree" : 0,"eviction walks started from root of tree" : 0,"eviction walks started from saved location in tree" : 0,"hazard pointer blocked page eviction" : 0,"in-memory page passed criteria to be split" : 150,"in-memory page splits" : 75,"internal pages evicted" : 0,"internal pages split during eviction" : 0,"leaf pages split during eviction" : 0,"modified pages evicted" : 0,"overflow pages read into cache" : 0,"page split during eviction deepened the tree" : 0,"page written requiring lookaside records" : 0,"pages read into cache" : 0,"pages read into cache after truncate" : 1,"pages read into cache after truncate in prepare state" : 0,"pages read into cache requiring lookaside entries" : 0,"pages requested from the cache" : 5314066,"pages seen by eviction walk" : 0,"pages written from cache" : 11507,"pages written requiring in-memory restoration" : 0,"tracked dirty bytes in the cache" : 0,"unmodified pages evicted" : 0},"cache_walk" : {"Average difference between current eviction generation when the page was last considered" : 0,"Average on-disk page image size seen" : 0,"Average time in cache for pages that have been visited by the eviction server" : 0,"Average time in cache for pages that have not been visited by the eviction server" : 0,"Clean pages currently in cache" : 0,"Current eviction generation" : 0,"Dirty pages currently in cache" : 0,"Entries in the root page" : 0,"Internal pages currently in cache" : 0,"Leaf pages currently in cache" : 0,"Maximum difference between current eviction generation when the page was last considered" : 0,"Maximum page size seen" : 0,"Minimum on-disk page image size seen" : 0,"Number of pages never visited by eviction server" : 0,"On-disk page image sizes smaller than a single allocation unit" : 0,"Pages created in memory and never written" : 0,"Pages currently queued for eviction" : 0,"Pages that could not be queued for eviction" : 0,"Refs skipped during cache traversal" : 0,"Size of the root page" : 0,"Total number of pages currently in cache" : 0},"compression" : {"compressed pages read" : 0,"compressed pages written" : 11393,"page written failed to compress" : 0,"page written was too small to compress" : 114,"raw compression call failed, additional data available" : 0,"raw compression call failed, no additional data available" : 0,"raw compression call succeeded" : 0},"cursor" : {"bulk-loaded cursor-insert calls" : 0,"create calls" : 3,"cursor operation restarted" : 0,"cursor-insert key and value bytes inserted" : 313806525,"cursor-remove key bytes removed" : 0,"cursor-update value bytes updated" : 0,"cursors cached on close" : 0,"cursors reused from cache" : 5000013,"insert calls" : 5000000,"modify calls" : 0,"next calls" : 40000008,"prev calls" : 1,"remove calls" : 0,"reserve calls" : 0,"reset calls" : 10313408,"search calls" : 8,"search near calls" : 313375,"truncate calls" : 0,"update calls" : 0},"reconciliation" : {"dictionary matches" : 0,"fast-path pages deleted" : 0,"internal page key bytes discarded using suffix compression" : 26736,"internal page multi-block writes" : 27,"internal-page overflow keys" : 0,"leaf page key bytes discarded using prefix compression" : 0,"leaf page multi-block writes" : 102,"leaf-page overflow keys" : 0,"maximum blocks required for a page" : 1,"overflow values written" : 0,"page checksum matches" : 2599,"page reconciliation calls" : 156,"page reconciliation calls for eviction" : 0,"pages deleted" : 0},"session" : {"cached cursor count" : 3,"object compaction" : 0,"open cursor count" : 0},"transaction" : {"update conflicts" : 0}},"nindexes" : 2,"totalIndexSize" : 117092352,"indexSizes" : {"_id_" : 50466816,"age_1" : 66625536},"ok" : 1
}
>

如上所示，可以看到最后的 "indexSizes" 部分中有两个索引，分别是 _id_，与 age_

_id_：这是 MongoDB 自己维护的主键字段 (_id)，默认是建索引的

age_：这是为 age 字段新建的索引，索引名称是字段名称加下斜杠。

删除索引

删除索引：db.collection.dropIndex({key:1})，如下所示删除 age 字段的索引，再次使用 stats() 查看信息时，已经没有 age_ 索引了

> db.c1.dropIndex({age:1})
{ "nIndexesWas" : 2, "ok" : 1 }
> db.c1.stats()
{"ns" : "mydb2.c1","size" : 293888890,"count" : 5000000,"avgObjSize" : 58,"storageSize" : 93253632,"capped" : false,"wiredTiger" : {
..............},"nindexes" : 1,"totalIndexSize" : 50466816,"indexSizes" : {"_id_" : 50466816},"ok" : 1
}

创建唯一索引

1、创建唯一索引：db.collection.ensureIndex({key:1}，{unique:true})

2、为某个字段建立唯一索引，则这个键对应的值必须不能重复，相当于 Mysql 的唯一约束，此字段的值必须唯一！

3、唯一索引与普通索引的区别在于索引字段的值能不能重复，普通索引的字段的值可以重复，唯一索引不能重复！

4、如下所示为 name 字段建立唯一索引成功。

> db.c1.ensureIndex({name:1},{unique:true})
{"createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1
}
>

同理可以在 MongoDB 服务端的 cmd 面板中看到索引构建的状态信息。

2018-09-12T11:31:08.471+0800 I INDEX    [conn1]          building index using bulk method; build may temporarily use up to 500 megabytes of RAM
2018-09-12T11:31:11.000+0800 I -        [conn1]   Index Build: 1377500/5000000 27%
2018-09-12T11:31:14.000+0800 I -        [conn1]   Index Build: 3082200/5000000 61%
2018-09-12T11:31:17.000+0800 I -        [conn1]   Index Build: 4731000/5000000 94%
2018-09-12T11:31:24.570+0800 I INDEX    [conn1] build index done.  scanned 5000000 total records. 16 secs

如下所示，根据 name 字段进行查询，速度与之前为 age 字段创建普通索引时的检索速度一样，都是秒查，没有明显区别

> db.c1.find({name:"华安45000"})
{ "_id" : ObjectId("5b98717147640bc808f79d01"), "name" : "华安45000", "age" : 45000 }
> db.c1.find({name:"华安45000"}).explain("executionStats")
{"queryPlanner" : {"plannerVersion" : 1,"namespace" : "mydb2.c1","indexFilterSet" : false,"parsedQuery" : {"name" : {"$eq" : "华安45000"}},"winningPlan" : {"stage" : "FETCH","inputStage" : {"stage" : "IXSCAN","keyPattern" : {"name" : 1},"indexName" : "name_1","isMultiKey" : false,"multiKeyPaths" : {"name" : [ ]},"isUnique" : true,"isSparse" : false,"isPartial" : false,"indexVersion" : 2,"direction" : "forward","indexBounds" : {"name" : ["[\"华安45000\", \"华安45000\"]"]}}},"rejectedPlans" : [ ]},"executionStats" : {"executionSuccess" : true,"nReturned" : 1,"executionTimeMillis" : 0,"totalKeysExamined" : 1,"totalDocsExamined" : 1,"executionStages" : {"stage" : "FETCH","nReturned" : 1,"executionTimeMillisEstimate" : 0,"works" : 2,"advanced" : 1,"needTime" : 0,"needYield" : 0,"saveState" : 0,"restoreState" : 0,"isEOF" : 1,"invalidates" : 0,"docsExamined" : 1,"alreadyHasObj" : 0,"inputStage" : {"stage" : "IXSCAN","nReturned" : 1,"executionTimeMillisEstimate" : 0,"works" : 2,"advanced" : 1,"needTime" : 0,"needYield" : 0,"saveState" : 0,"restoreState" : 0,"isEOF" : 1,"invalidates" : 0,"keyPattern" : {"name" : 1},"indexName" : "name_1","isMultiKey" : false,"multiKeyPaths" : {"name" : [ ]},"isUnique" : true,"isSparse" : false,"isPartial" : false,"indexVersion" : 2,"direction" : "forward","indexBounds" : {"name" : ["[\"华安45000\", \"华安45000\"]"]},"keysExamined" : 1,"seeks" : 1,"dupsTested" : 0,"dupsDropped" : 0,"seenInvalidated" : 0}}},"serverInfo" : {"host" : "SC-201707281232","port" : 27017,"version" : "4.0.2-rc0","gitVersion" : "fc1573ba18aee42f97a3bb13b67af7d837826b47"},"ok" : 1
}
>

如下所示 name 字段建立唯一索引之后，如果添加的新文档中的 name 字段值重复时，则添加失败

> db.c1.find({name:"华安45000"})
{ "_id" : ObjectId("5b98717147640bc808f79d01"), "name" : "华安45000", "age" : 45000 }
> db.c1.insert({name:"华安45000",age:45000})
WriteResult({"nInserted" : 0,"writeError" : {"code" : 11000,"errmsg" : "E11000 duplicate key error collection: mydb2.c1 index: name_1 dup key: { : \"鍗庡畨45000\" }"}
})

explain 工具

explain 是非常有用的工具，能获得查询方面诸多有用的信息

如下所示，explain 方法不带参数时，返回信息如下

> db.c1.find().explain();
{"queryPlanner" : {"plannerVersion" : 1,"namespace" : "mydb2.c1","indexFilterSet" : false,"parsedQuery" : {},"winningPlan" : {"stage" : "COLLSCAN","direction" : "forward"},"rejectedPlans" : [ ]},"serverInfo" : {"host" : "SC-201707281232","port" : 27017,"version" : "4.0.2-rc0","gitVersion" : "fc1573ba18aee42f97a3bb13b67af7d837826b47"},"ok" : 1
}
>

通常应该为 explain 方法带上参数 executionStats，即 .explain("executionStats")，这样信息会更加全面

> db.c1.find().explain("executionStats");
{"queryPlanner" : {"plannerVersion" : 1,"namespace" : "mydb2.c1","indexFilterSet" : false,"parsedQuery" : {},"winningPlan" : {"stage" : "COLLSCAN","direction" : "forward"},"rejectedPlans" : [ ]},"executionStats" : {"executionSuccess" : true,"nReturned" : 5000000,"executionTimeMillis" : 1381,"totalKeysExamined" : 0,"totalDocsExamined" : 5000000,"executionStages" : {"stage" : "COLLSCAN","nReturned" : 5000000,"executionTimeMillisEstimate" : 952,"works" : 5000002,"advanced" : 5000000,"needTime" : 1,"needYield" : 0,"saveState" : 39104,"restoreState" : 39104,"isEOF" : 1,"invalidates" : 0,"direction" : "forward","docsExamined" : 5000000}},"serverInfo" : {"host" : "SC-201707281232","port" : 27017,"version" : "4.0.2-rc0","gitVersion" : "fc1573ba18aee42f97a3bb13b67af7d837826b47"},"ok" : 1
}
>

executionStats 信息部分参数解释如下：

"executionSuccess" : true ————是否执行成功，true 表示成功

"nReturned" : 5000000 ————检索返回的数据条数，此处为 5 百万条

"executionTimeMillis" : 1375 ————本次检索耗费的时间，此处为 1357 毫秒，即约 1.3 秒

"totalDocsExamined" : 5000000 ————本次检索扫描的文档数，此处为 5 百万条

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