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。
参数 | 类型 | 描述 |
---|---|---|
background | boolean | 创建索引在后台运行,不会阻止其他对数据库操作 |
unique | boolean | 创建唯一索引,文档的值不会重复 |
name | string | 索引名称,默认是:字段名_排序类型 开始排序 |
sparse | boolean | 过滤掉null,不存在的字段 |
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。
- index 是字符串 表示按照索引名称 name 删除字段。
- index 是{字段名称:1} 表示按照key 删除索引。
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
stage | 描述 |
---|---|
COLLSCAN | 全表扫描 |
IXSCAN | 扫描索引 |
FETCH | 根据索引去检索指定document |
SHARD_MERGE | 将各个分片返回数据进行merge |
SORT | 表明在内存中进行了排序 |
LIMIT | 使用limit限制返回数 |
SKIP | 使用skip进行跳过 |
IDHACK | 针对_id进行查询 |
SHARDING_FILTER | 通过mongos对分片数据进行查询 |
COUNT | 利用db.coll.explain().count()之类进行count运算 |
COUNTSCAN | count不使用Index进行count时的stage返回 |
COUNT_SCAN | count使用了Index进行count时的stage返回 |
SUBPLA | 未使用到索引的$or查询的stage返回 |
TEXT | 使用全文索引进行查询时候的stage返回 |
PROJECTION | 限定返回字段时候stage的返回 |
对于普通查询,我希望看到stage的组合(查询的时候尽可能用上索引):
Fetch+IDHACK
Fetch+ixscan
Limit+(Fetch+ixscan)
PROJECTION+ixscan
SHARDING_FITER+ixscan
COUNT_SCAN
不希望看到包含如下的stage:
COLLSCAN(全表扫描),SORT(使用sort但是无index),不合理的SKIP,SUBPLA(未用到index的$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。
相关文章
http://www.mongoing.com/eshu_explain3
https://docs.mongodb.com/v3.2/reference/explain-results/#queryplanner