第五章 MongoDb索引优化 5.1

此章节，是作者阅读网上资料，通过结合自身项目的实践。

引用：原文链接：http://iamcaihuafeng.blog.sohu.com/151638529.html

(本文是一篇转载文章，作者在对MongoDB文档进行了细致的阅读后，总结出了MongoDB的各种索引的用法。)

索引能提高检索数据的速度，你可以想像成在MySQL中创建索引一样，同样索引也是用B-Tree也实现的。

创建schedule的collection：

DB db = m.getDB("ms_basic");

DBCollection coll = db.getCollection("schedule");

//插入数据略过

List<DBObject> indexList = coll.getIndexInfo();

for (DBObject o : indexList) {

System.out.println("index ---------" + o);

}

运行结果：

index ---------

{ "name" : "_id_" , "ns" : "ms_basic.schedule" , "key" : { "_id" : 1}}

此时可以看到，索引为_id,内置的，按照升序排列

System.out.println("SELECT * FROM schedule WHERE rsc='ATM033101'");

startTime = System.currentTimeMillis();

query = new BasicDBObject();

query.put("rsc","ATM033101");

cur = coll.find(query);

System.out.println("查询获得的长度"+cur.count());

System.out.println("查询耗

时:"+(System.currentTimeMillis()-startTime)+"毫秒.");

运行结果：

-----------华丽分隔线无rsc索引查询---------------

SELECT * FROM schedule WHERE rsc='ATM033101'

查询获得的长度1

查询耗时:63毫秒.

explain分析:{ "cursor" : "BasicCursor" , "indexBounds" : [ ] , "nscanned" : 4597 , "nscannedObjects" : 4597 , "n" : 1 , "millis" : 0 , "oldPlan" : { "cursor" : "BasicCursor" , "indexBounds" : [ ]} , "allPlans" : [ { "cursor" : "BasicCursor" , "indexBounds" : [ ]}]}

看看官方的解释：

public DBObject explain()

Returns an object containing basic information about the exectution of the query that created this cursor This creates a DBObject with the key/value pairs: "cursor" : cursor type "nScanned" : number of records examined by the database for this query "n" : the number of records that the database returned "millis" : how long it took the database to execute the query

1、单列索引

在字段rsc上创建索引，1 (ascending) or -1 (descending)

MongoDb提供两种接口给我们创建索引：

ensureIndex和createIndex

具体可以查查在线的API：http://api.mongodb.org/java/2.0/index.html

coll.createIndex(new BasicDBObject("rsc", 1));

运行：

List<DBObject> indexList = coll.getIndexInfo();

for (DBObject o : indexList) {

System.out.println("index ---------" + o);

}

结果为：

index ---------

{ "name" : "_id_" , "ns" : "ms_basic.schedule" , "key" : { "_id" : 1}}

index ---------

{ "name" : "rsc_1" , "ns" : "ms_basic.schedule" , "key" : { "rsc" : 1}}

再次查找：query.put("rsc","ATM033101");

-----------华丽分隔线有rsc索引查询---------------

SELECT * FROM schedule WHERE rsc='ATM033101'

查询获得的长度1

查询耗时:47毫秒.

explain分析:{ "cursor" : "BtreeCursor rsc_1" , "indexBounds" : [ [ { "rsc" : "ATM033101"} , { "rsc" : "ATM033101"}]] , "nscanned" : 1 , "nscannedObjects" : 1 , "n" : 1 , "millis" : 0 , "oldPlan" : { "cursor" : "BtreeCursor rsc_1" , "indexBounds" : [ [ { "rsc" : "ATM033101"} , { "rsc" : "ATM033101"}]]} , "allPlans" : [ { "cursor" : "BtreeCursor rsc_1" , "indexBounds" : [ [ { "rsc" : "ATM033101"} , { "rsc" : "ATM033101"}]]}]}

此时花费了：47毫秒

从explain分析中，可以看到："cursor" : "BtreeCursor rsc_1" , "indexBounds" : [ [ { "rsc" : "ATM033101"}，说明使用了索引来进行查询。

2、默认索引

刚刚看到，一共显示有2个索引，包括自己创建的，其中_id是创建表的时候自动创建的索引，此索引是不能够删除的。

An index is always created on _id. This index is special and cannot be deleted. The _id index enforces uniqueness for its keys.

本文出自 “lee” 博客，请务必保留此出处http://jooben.blog.51cto.com/253727/365893