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mongodb实践 4

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#存入数据

#基于document的数据

*定义一个文档对象@

---

> doc = { author: 'joe',
		  created : new Date('03/28/2009'),
		  title : 'Yet another blog post',
		  text : 'Here is the text...',
		  tags : [ 'example', 'joe' ],
		  comments : [ { author: 'jim', comment: 'I disagree' },
			      { author: 'nancy', comment: 'Good post' }
		  ]
		}
   

*保存该文档@

> db.posts.insert(doc);
 

*检索该文档@

> db.posts.find({"comments.author":"jim"});
		{ "_id" : ObjectId("4ee9550cbd3e00000000337e"), "author" : "joe", "created" : "Sat Mar 28 2009 00:00:00 GMT+0800", "title" : "Yet another blog post", "text" : "Here is the text...", "tags" : [ "example", "joe" ], "comments" : [
			{
				"author" : "jim",
				"comment" : "I disagree"
			},
			{
				"author" : "nancy",
				"comment" : "Good post"
			}
		] }
 

ps:在使用java driver 的时候,可以通过WriteConcern来返回异常信息,如@

db.test.insert(obj, WriteConcern.SAFE);
 

#mongodb优化

 

*使用索引@

db.things.ensureIndex({i:1});
 

 

*限制返回数据条数@

db.things.find().sort({i:1}).limit(10);
 

 

*只返回需要的列@

db.things.find({},{i2:true}).sort({i:-1}).limit(10);
 

返回i2域

db.things.find({},{i2:false}).sort({i:-1}).limit(10);
 

返回除i2的域,即i,i3

db.things.find({},{i2:false,_id:0}).sort({i:-1}).limit(10);
 

返回除i2、_id的剩余域

*还可以这么写(照搬官网示例)@

db.posts.find({}, {comments:{$slice: 5}}) // first 5 comments
		db.posts.find({}, {comments:{$slice: -5}}) // last 5 comments
		db.posts.find({}, {comments:{$slice: [20, 10]}}) // skip 20, limit 10
		db.posts.find({}, {comments:{$slice: [-20, 10]}}) // 20 from end, limit 10
 

 

*使用mongodb profiler(剖面测量仪,性能监视)@

> db.commandHelp("profile");
		help for: profile enable or disable performance profiling
		{ profile : <n> }
		0=off 1=log slow ops 2=log all
		http://www.mongodb.org/display/DOCS/Database+Profiler
		> db.setProfilingLevel(2);
		{ "was" : 0, "slowms" : 100, "ok" : 1 }
 

首选查一下帮助信息,然后将profillingLevel设置为2,was表示以前的设置。查看当前设置@

> db.getProfilingLevel();
		2
 

slowms值>100ms即被认为慢,可以通过如下命令修改默认值@

> db.setProfilingLevel(2,20)
		{ "was" : 2, "slowms" : 20, "ok" : 1 }
 

 

*明确的指明需要使用的索引@

> db.things.find({i:4}).hint({i:1});
		{ "_id" : ObjectId("4ee8510a0c16000000006ec9"), "i" : 4, "i2" : 16 }
		{ "_id" : ObjectId("4ee8514d0c16000000006edd"), "i" : 4, "i2" : 16, "i3" : 64 }
 

 

 

PS:贴一段使用索引的性能测试代码:(测试环境:window7 64 4G RAM)

 

 

 

  
import com.mongodb.BasicDBObject;
import com.mongodb.DB;
import com.mongodb.DBCollection;
import com.mongodb.DBCursor;
import com.mongodb.DBObject;
import com.mongodb.Mongo;
import com.mongodb.MongoException;

public class PerformanceTest {

	private Mongo mongo = null;

	public PerformanceTest() {
	}

	private Mongo getInstance() {
		if (mongo == null)
			try {
				mongo = new Mongo();
			} catch (UnknownHostException e) {
				e.printStackTrace();
			} catch (MongoException e) {
				e.printStackTrace();
			}
		return mongo;
	}

	/**
	 * 插入简单数据
	 */
	public static void Performance() {
		PerformanceTest pt = new PerformanceTest();
		Mongo mongo = pt.getInstance();
		DB db = mongo.getDB("mytest");
		/*// make a document and insert it
		BasicDBObject doc = new BasicDBObject();

		doc.put("name", "MongoDB");
		doc.put("type", "database");
		doc.put("count", 1);

		BasicDBObject info = new BasicDBObject();

		info.put("x", 203);
		info.put("y", 102);

		doc.put("info", info);
		Set<String> colls = db.getCollectionNames();
		for (String s : colls) {
			System.out.println(s);
		}*/

		DBCollection coll = db.getCollection("testCollection");
		int i = 0;

		
		DBObject myDoc = coll.findOne();
//		System.out.println(myDoc);

		for (i = 0; i < 6000000; i++) {
			coll.insert(new BasicDBObject().append("i", i).append("j", i).append("k", i));
		}

		/*DBCursor cur = coll.find();
		while (cur.hasNext()) {
			System.out.println(cur.next());
		}
		coll.drop();*/
		System.out.println(coll.count());
	}
	
	public static void creatIndex(){
		PerformanceTest pt = new PerformanceTest();
		Mongo mongo = pt.getInstance();
		
		DB db = mongo.getDB("mytest");
		DBCollection coll = db.getCollection("testCollection");
		coll.createIndex(new BasicDBObject("i", 1));
	}
	
	public static void query(){
		PerformanceTest pt = new PerformanceTest();
		Mongo mongo = pt.getInstance();
		DB db = mongo.getDB("mytest");
		
		BasicDBObject query = new BasicDBObject();
        query.put("i", new BasicDBObject("$gt", 1234).append("$lte", 1240));  // i.e.   20 < i <= 30
        DBCollection coll = db.getCollection("testCollection");
        DBCursor cur = coll.find(query);

        while(cur.hasNext()) {
            System.out.println(cur.next());
        }
	}
	
	public static void main(String[] args) {
		
		Long cost = System.currentTimeMillis();
		
		PerformanceTest pt = new PerformanceTest();
		Mongo mongo = pt.getInstance();
		DB db = mongo.getDB("mytest");
		
		DBCollection coll = db.getCollection("testCollection");
		System.out.println("count:"+coll.count());
		System.out.println(Integer.MAX_VALUE);
		System.out.println(Long.MAX_VALUE);
		//创建索引后,效率有大幅度的提升,6000000条数据(仅有一列)没有索引时查询耗时2865毫秒,
		//创建索引后,查询耗时111毫秒。
//		creatIndex();
		query();

//		Performance();
		cost = System.currentTimeMillis() - cost;
		System.out.println("cost:"+cost);
		
		/*
		coll.dropIndexes();
		coll.drop();
		db.dropDatabase();
		*/
	}

}
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