MongoDB 提供了多样性的索引支持。
来源：互联网 发布：如何破解网络尖兵 编辑：程序博客网 时间：2024/05/21 21:43
MongoDB 提供了多样性的索引支持。
> for (var i = 0; i < 30; i++) {... u = { name : "user" + i,... age : 20 + i,... contact : {... address : ["address1_" + i, "address2_" + i],... postcode : 100000 + i,... }... };... db.users.insert(u);... }索引信息被保存在 system.indexes 中，且默认总是为 _id 创建索引。
> show collectionssystem.indexesusers> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }1. ensureIndex / dropIndex / reIndex
使用 ensureIndex 创建索引，dropIndex() 删除索引，dropIndexes() 删除全部索引(不包括 _id 等系统索引)。
> db.users.ensureIndex({name:1})> db.users.ensureIndex({age:1})> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }{ "_id" : ObjectId("4c4a...b798"), "ns" : "blog.users", "key" : { "name" : 1 }, "name" : "name_1" }{ "_id" : ObjectId("4c4a...b799"), "ns" : "blog.users", "key" : { "age" : 1 }, "name" : "age_1" }> db.users.dropIndex({age:1}){ "nIndexesWas" : 3, "ok" : true }> db.users.dropIndexes(){ "nIndexesWas" : 2, "msg" : "non-_id indexes dropped for collection", "ok" : true}> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }reIndex 则是重建索引。
> db.users.ensureIndex({name:1})> db.users.ensureIndex({age:1})> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }{ "_id" : ObjectId("4c4a...b82a"), "ns" : "blog.users", "key" : { "name" : 1 }, "name" : "name_1" }{ "_id" : ObjectId("4c4a...b82b"), "ns" : "blog.users", "key" : { "age" : 1 }, "name" : "age_1" }> db.users.reIndex(){ "nIndexesWas" : 3, "msg" : "indexes dropped for collection", "ok" : 1, "nIndexes" : 3, "indexes" : [ { "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }, { "_id" : ObjectId("4c4a...b82a"), "ns" : "blog.users", "key" : { "name" : 1 }, "name" : "name_1" }, { "_id" : ObjectId("4c4a...b82b"), "ns" : "blog.users", "key" : { "age" : 1 }, "name" : "age_1" } ], "ok" : 1}当系统已有大量数据时，创建索引就是个非常耗时的活，我们可以在后台执行。
> db.users.dropIndexes(){ "nIndexesWas" : 3, "msg" : "non-_id indexes dropped for collection", "ok" : true}> db.users.ensureIndex({name:1}, {backgroud:true})> db.users.reIndex({backgroud:true}){ "nIndexesWas" : 2, "msg" : "indexes dropped for collection", "ok" : 1, "nIndexes" : 2, "indexes" : [ { "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }, { "_id" : ObjectId("4c4a...b79c"), "ns" : "blog.users", "key" : { "name" : 1 }, "name" : "name_1", "backgroud" : true } ], "ok" : 1}2. explain
MongoDB 提供了一个 explain 命令让我们获知系统如何处理查询请求。
> db.users.ensureIndex({name:1})> db.users.ensureIndex({age:1})> db.users.find({age:{$gt:45}}, {name:1, age:1}){ "_id" : ObjectId("4c4a8edeeb257107735eb826"), "name" : "user26", "age" : 46 }{ "_id" : ObjectId("4c4a8edeeb257107735eb827"), "name" : "user27", "age" : 47 }{ "_id" : ObjectId("4c4a8edeeb257107735eb828"), "name" : "user28", "age" : 48 }{ "_id" : ObjectId("4c4a8edeeb257107735eb829"), "name" : "user29", "age" : 49 }> db.users.find({age:{$gt:45}}, {name:1, age:1}).explain(){ "cursor" : "BtreeCursor age_1", "nscanned" : 5, "nscannedObjects" : 4, "n" : 4, "millis" : 0, "indexBounds" : [ [ { "age" : 45 }, { "age" : 1.7976931348623157e+308 } ] ]}返回结果信息包括:
- cursor: 返回游标类型(BasicCursor 或 BtreeCursor)。
- nscanned: 被扫描的文档数量。
- n: 返回的文档数量。
- millis: 耗时(毫秒)。
- indexBounds: 所使用的索引。
利用 explain 命令，我们可以很好地观察系统如何使用索引来加快检索，同时可以针对性优化索引。
3. Embedded Keys Index
我 们可以创建深层索引，甚至直接用文档(sub-document)作为索引键。
> db.users.ensureIndex({"contact.postcode":1})> db.users.find({"contact.postcode":{$lt:100009}}, {name:1, "contact.postcode":1}){ "_id" : ObjectId("4c4a8edeeb257107735eb80c"), "name" : "user0", "contact" : { "postcode" : 100000 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb80d"), "name" : "user1", "contact" : { "postcode" : 100001 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb80e"), "name" : "user2", "contact" : { "postcode" : 100002 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb80f"), "name" : "user3", "contact" : { "postcode" : 100003 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb810"), "name" : "user4", "contact" : { "postcode" : 100004 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb811"), "name" : "user5", "contact" : { "postcode" : 100005 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb812"), "name" : "user6", "contact" : { "postcode" : 100006 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb813"), "name" : "user7", "contact" : { "postcode" : 100007 } }{ "_id" : ObjectId("4c4a8edeeb257107735eb814"), "name" : "user8", "contact" : { "postcode" : 100008 } }> db.users.find({"contact.postcode":{$lt:100009}}, {name:1, "contact.postcode":1}).explain(){ "cursor" : "BtreeCursor contact.postcode_1", "nscanned" : 10, "nscannedObjects" : 9, "n" : 9, "millis" : 0, "indexBounds" : [ [ { "contact.postcode" : -1.7976931348623157e+308 }, { "contact.postcode" : 100009 } ] ]}我们直接用 contact 创建索引，查找其下属性时可使用该索引，但需注意语法。
(附注: 在 1.5.4 mongo 中，一直无法使用 contact:{postcode:xxx} 这样的 SubObject 语法查询数据，只能用 “contact.postcode” DotNotation 语法)
> db.users.dropIndex({"contact.postcode":1}){ "nIndexesWas" : 4, "ok" : true }> db.users.ensureIndex({contact:1})> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }{ "_id" : ObjectId("4c4a...b82a"), "ns" : "blog.users", "key" : { "name" : 1 }, "name" : "name_1" }{ "_id" : ObjectId("4c4a...b82b"), "ns" : "blog.users", "key" : { "age" : 1 }, "name" : "age_1" }{ "_id" : ObjectId("4c4a...b82d"), "ns" : "blog.users", "key" : { "contact" : 1 }, "name" : "contact_1" }> db.users.find({contact:{postcode:{$lt:100009}}}).explain(){ "cursor" : "BtreeCursor contact_1", "nscanned" : 0, "nscannedObjects" : 0, "n" : 0, "millis" : 0, "indexBounds" : [ [ { "contact" : { "postcode" : { "$lt" : 100009 } } }, { "contact" : { "postcode" : { "$lt" : 100009 } } } ] ]}> db.users.find({"contact.postcode":{$lt:100009}}).explain() // 无法使用索引{ "cursor" : "BasicCursor", "nscanned" : 30, "nscannedObjects" : 30, "n" : 9, "millis" : 0, "indexBounds" : [ ]}> db.users.find({contact:{address:"address2_23"}}).explain(){ "cursor" : "BtreeCursor contact_1", "nscanned" : 0, "nscannedObjects" : 0, "n" : 0, "millis" : 0, "indexBounds" : [ [ { "contact" : { "address" : "address2_23" } }, { "contact" : { "address" : "address2_23" } } ] ]}> db.users.find({"contact.address":"address2_23"}).explain() // 无法使用索引{ "cursor" : "BasicCursor", "nscanned" : 30, "nscannedObjects" : 30, "n" : 1, "millis" : 0, "indexBounds" : [ ]}同样的语法问题在 Python 中一样生效。
>>> db.users.find({"contact":{"postcode":{"$lt":100009}}}).explain(){u'allPlans': [{u'cursor': u'BtreeCursor contact_1', u'indexBounds': [[{u'contact': {u'postcode': {u'$lt': 100009}}}, {u'contact': {u'postcode': {u'$lt': 100009}}}]]}], u'cursor': u'BtreeCursor contact_1', u'indexBounds': [[{u'contact': {u'postcode': {u'$lt': 100009}}}, {u'contact': {u'postcode': {u'$lt': 100009}}}]], u'millis': 0, u'n': 0, u'nscanned': 0, u'nscannedObjects': 0, u'oldPlan': {u'cursor': u'BtreeCursor contact_1', u'indexBounds': [[{u'contact': {u'postcode': {u'$lt': 100009}}}, {u'contact': {u'postcode': {u'$lt': 100009}}}]]}}>>> db.users.find({"contact.postcode":{"$lt":100009}}).explain(){u'allPlans': [{u'cursor': u'BasicCursor', u'indexBounds': []}], u'cursor': u'BasicCursor', u'indexBounds': [], u'millis': 0, u'n': 8, u'nscanned': 30, u'nscannedObjects': 30, u'oldPlan': {u'cursor': u'BasicCursor', u'indexBounds': []}}4. Compound Keys Index
创建复合索引也很简单 (1: ascending; -1: descending)。
> db.users.ensureIndex({name:1, age:-1})> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }{ "_id" : ..., "ns" : "blog.users", "key" : { "name" : 1 }, "name" : "name_1" }{ "_id" : ..., "ns" : "blog.users", "key" : { "age" : 1 }, "name" : "age_1" }{ "_id" : ..., "ns" : "blog.users", "key" : { "contact" : 1 }, "name" : "contact_1" }{ "_id" : ..., "ns" : "blog.users", "key" : { "name" : 1, "age" : -1 }, "name" : "name_1_age_-1" }> db.users.find({age:{$lt:25}, name:"user2"}, {name:1, age:1}){ "_id" : ObjectId("4c4a8edeeb257107735eb80e"), "name" : "user2", "age" : 22 }> db.users.find({age:{$lt:25}, name:"user2"}, {name:1, age:1}).explain(){ "cursor" : "BtreeCursor name_1_age_-1", "nscanned" : 1, "nscannedObjects" : 1, "n" : 1, "millis" : 0, "indexBounds" : [ [ { "name" : "user2", "age" : 25 }, { "name" : "user2", "age" : -1.7976931348623157e+308 } ] ]}复合索引同样可用于局部属性的搜索，但必须依照索引字段顺序。比如创建索引字段顺序 “a,b,c”，那么仅对 “a,b,c”、”a,b”、”a” 查询有效，而对 “b,c” 之类的组合无效。
> db.users.dropIndex({name:1}){ "nIndexesWas" : 5, "ok" : true }> db.users.dropIndex({age:1}){ "nIndexesWas" : 4, "ok" : true }> db.users.dropIndex({contact:1}){ "nIndexesWas" : 3, "ok" : true }> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }{ "_id" : ObjectId("4c4a9...b82e"), "ns" : "blog.users", "key" : { "name" : 1, "age" : -1 }, "name" : "name_1_age_-1" }> db.users.find({name:"user12"}).explain() // 索引有效{ "cursor" : "BtreeCursor name_1_age_-1", "nscanned" : 1, "nscannedObjects" : 1, "n" : 1, "millis" : 0, "indexBounds" : [ [ { "name" : "user12", "age" : { "$maxElement" : 1 } }, { "name" : "user12", "age" : { "$minElement" : 1 } } ] ]}> db.users.find({age:18}).explain() // 索引无效{ "cursor" : "BasicCursor", "nscanned" : 30, "nscannedObjects" : 30, "n" : 0, "millis" : 0, "indexBounds" : [ ]}5. Unique Index
只需在 ensureIndex 命令中指定 unique 即可创建唯一索引。
> db.users.ensureIndex({name:1}, {unique:true})> db.system.indexes.find(){ "name" : "_id_", "ns" : "blog.users", "key" : { "_id" : 1 } }{ "_id" : ..., "ns" : "blog.users", "key" : { "name" : 1, "age" : -1 }, "name" : "name_1_age_-1" }{ "_id" : ..., "ns" : "blog.users", "key" : { "name" : 1 }, "name" : "name_1", "unique" : true }> db.users.insert({name:"user1"})E11000 duplicate key error index: blog.users.$name_1 dup key: { : "user1" }如 果创建唯一索引前已经有重复文档，那么可以用 dropDups 删除多余的数据。
> db.users.dropIndexes(){ "nIndexesWas" : 3, "msg" : "non-_id indexes dropped for collection", "ok" : true}> db.users.insert({name:"user1"})> db.users.find({name:"user1"}, {name:1}){ "_id" : ObjectId("4c4a9573eb257107735eb831"), "name" : "user1" }{ "_id" : ObjectId("4c4a8edeeb257107735eb80d"), "name" : "user1" }> db.users.ensureIndex({name:1}, {unique:true, dropDups:true})E11000 duplicate key error index: blog.users.$name_1 dup key: { : "user1" }> db.users.find({name:"user1"}, {name:1}){ "_id" : ObjectId("4c4a9573eb257107735eb831"), "name" : "user1" }6. Multikeys
对于数组类型属性，会自动索引全部数组元素。
> db.users.dropIndexes(){ "nIndexesWas" : 1, "msg" : "non-_id indexes dropped for collection", "ok" : true}> db.users.ensureIndex({"contact.address":1})> db.users.find({"contact.address":"address2_13"}).explain(){ "cursor" : "BtreeCursor contact.address_1", "nscanned" : 1, "nscannedObjects" : 1, "n" : 1, "millis" : 0, "indexBounds" : [ [ { "contact.address" : "address2_13" }, { "contact.address" : "address2_13" } ] ]}7. hint
hint 命令可以强制使用某个索引。
> db.users.dropIndexes(){ "nIndexesWas" : 2, "msg" : "non-_id indexes dropped for collection", "ok" : true}> db.users.ensureIndex({name:1, age:1})> db.users.find({age:{$lt:30}}).explain(){ "cursor" : "BasicCursor", "nscanned" : 30, "nscannedObjects" : 30, "n" : 9, "millis" : 0, "indexBounds" : [ ]}> db.users.find({age:{$lt:30}}).hint({name:1, age:1}).explain(){ "cursor" : "BtreeCursor name_1_age_1", "nscanned" : 30, "nscannedObjects" : 9, "n" : 9, "millis" : 0, "indexBounds" : [ [ { "name" : { "$minElement" : 1 }, "age" : -1.7976931348623157e+308 }, { "name" : { "$maxElement" : 1 }, "age" : 30 } ] ]}注意 Python 代码中写法。
>>> db.users.find({"age":{"$lt":30}}).hint([("name", ASCENDING), ("age", ASCENDING)]).explain(){u'cursor': u'BtreeCursor name_1_age_1', u'indexBounds': [[{u'age': -1.7976931348623157e+308, u'name': {u'$minElement': 1}}, {u'age': 30, u'name': {u'$maxElement': 1}}]], u'millis': 0, u'n': 9, u'nscanned': 30, u'nscannedObjects': 9}8. totalIndexSize
MongoDB 会将索引数据载入内存，以提高查询速度。我们可以用 totalIndexSize 获取全部索引数据大小。
> db.users.totalIndexSize()16384
- MongoDB 提供了多样性的索引支持。
- Android的屏幕多样性支持
- Android的屏幕多样性支持
- Android的屏幕多样性支持
- 报表多样性数据源之MongoDB
- RestFaces提供了对JSF的书签支持
- Spring对IBatis提供了完善的内建支持
- Linux 系统对 pthreads 提供了良好的支持
- Spring提供了编写DAO的支持类
- MongoDB发布1.4版，提供商业支持
- MongoDB：mongodb的索引操作
- MongoDB：mongodb的索引操作
- 素材的多样性
- 企业信息化的多样性
- mongodb的地理位置索引
- mongodb的地理位置索引
- mongoDB的索引
- Mongodb的索引
- 触摸屏驱动
- No 2 · 使用Response.BinaryWrite方法输出二进制图形
- MongoDB设置访问权限、设置用户
- oracle每天一句sql
- 代码复查一
- MongoDB 提供了多样性的索引支持。
- 分治法 求最大元和最小元 Java语言
- 改变MTU
- POJ 2665 Trees
- No 3 · 使用Request对象的Browser属性获取客户端浏览器信息
- C#如何把Editor设计的内容上传到服务器端
- 如何把matlab命令窗口中的信息输出（重定向）到文件？
- 面向对象编程（C++描述）总结
- C语言回调函数与函数指针
