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使用morphia对基于mongodb应用开发

12-01-08

最近初学了下mongoDB,作为比较火的一个NoSQL数据库,确实比较强大,但是这几天学下来更多的感觉到的是学习、使用都很方便。 首先是初学者体验使用方便,直接下载(http://www.mongodb.org/downloads)解压,然...

  最近初学了下mongoDB,作为比较火的一个NoSQL数据库,确实比较强大,但是这几天学下来更多的感觉到的是学习、使用都很方便。
 
          首先是初学者体验使用方便,直接下载(http://www.mongodb.org/downloads)解压,然后启一下服务便可使用:mongod --dbpath your_db_data_dir,启动以后默认端口27017,  默认http端口28017,可以通过http://localhost: 28017 查看基本信息。当然,如果你还没有下载的想法,可以直接在其官网上尝试Try The Online Shell,就可以使用其来做各种操作,当然online的功能较少。
 
         其次,一改关系数据库的表模型,mongodb是一个以松散的集合形势呈现,这种no shema让我感觉非常方便。从开发人员的角度看,mongodb中的每一个数据对象就是一个JSON,所有的操作(save,update,find etc.)都可以像操作JSON一样,当然mongodb数据是一种叫做BSON格式的,即Binary JSON:http://bsonspec.org/ 。例如:
 
将文档{ name:”abc”,age:12}插入到users集合:
 
db.users.insert ({name:”abc”,age:12})
 
修改文档,增加其emails属性:
 
db.users.update(
 
{name:"abc"},
 
{"$set": {emails:["abc@gmail.com","abc@163.com"]}}
 
)
 
查找所有users文档:
 
db.users.find();
 
查找age > 20的前5个:
 
db.users.find({
 
age: {“$gt”:20}
 
                }).limit(5)
 
删除:db.users.delete({name:”abc”})
 
         这些基本的操作不一一例举,包括像index的操作,统计函数等,总之,一切都是文档:查询表达式是文档、返回数据是文档、修改数据的新值是文档、index的操作也是文档形式等等。另外,诸如其支持的MAPREDUCE操作,只需在其规范内定义自己的map和reduce函数即可完成简单MR计算;使用GridFS规范来存储大文件。
 
          最后的方便之处就是对很多开发语言的支持,PHP, Java, Python, Ruby, Perl。这里我就使用Morphia来做一个非常简单demo: 假设一千个店铺(store)分布在不同的地方(place),每个地方都有一个二维的坐标(x,y)用来表示其位置,我们可以很方便的查找到诸如 离***地方最近的***店铺。整个例子分三步:
 
1)      准备数据
 
2)      测试数据是否准备好
 
3)      查找店铺
 
        使用jars:  mongo-2.7.0.jar,   morphia-0.98.jar
 
    下面是两个model类:
 
 
 
@Entity(value="stores",noClassnameStored=true)  
public class Store {  
    @Id 
    private ObjectId id;  
    private String name;  
    private String desc;  
    @Embedded 
    public Place place;  
    @Override 
    public String toString() {  
       return "Store [desc=" + desc + ", id=" + id + ", name=" +   
                          name + ", place=" + place + "]";  
    }  
 
    public Store(){}  
    public Store(String name, String desc, Place place) {  
        this.name = name;  
        this.desc = desc;  
        this.place = place;  
    }  
//省略getter,setters  

 
@Entity(value="stores",noClassnameStored=true)
public class Store {
       @Id
       private ObjectId id;
       private String name;
       private String desc;
       @Embedded
       public Place place;
       @Override
       public String toString() {
          return "Store [desc=" + desc + ", id=" + id + ", name=" +
                          name + ", place=" + place + "]";
       }
 
       public Store(){}
       public Store(String name, String desc, Place place) {
              this.name = name;
              this.desc = desc;
              this.place = place;
       }
//省略getter,setters
}
 
 
 
 
@Embedded 
public class Place {  
 
    private String name = "";  
    @Indexed(IndexDirection.GEO2D)  
    private double[] loc = null;  
 
    public Place(String name, double[] loc) {  
        this.name = name;  
        this.loc = loc;  
    }  
 
    public Place() {  
    }  
 
    @Override 
    public String toString() {  
        return "Place [loc=" + Arrays.toString(loc) + ", name=" + name + "]";  
    }  
    //省略getter,setters    

 
@Embedded
public class Place {
 
       private String name = "";
       @Indexed(IndexDirection.GEO2D)
       private double[] loc = null;
 
       public Place(String name, double[] loc) {
              this.name = name;
              this.loc = loc;
       }
 
       public Place() {
       }
 
       @Override
       public String toString() {
              return "Place [loc=" + Arrays.toString(loc) + ", name=" + name + "]";
       }
       //省略getter,setters      
}
 
   因为morphia提供了BasicDao,所以这里就准备一个简单的Dao:
 
 
package morphia.dao;  
import java.util.List;  
import morphia.model.Place;  
import morphia.model.Store;  
import com.google.code.morphia.Datastore;  
import com.google.code.morphia.dao.BasicDAO;  
import com.google.code.morphia.query.Query;  
 
public class StoreDao extends BasicDAO<Store, String> {  
    public StoreDao(Datastore ds) {  
        super(ds);  
        ds.ensureIndexes();  
        ds.ensureCaps();  
    }  
    /** 
     * 查找离p 最近的5个店铺 
     * @param p 
     * @return 
     */ 
    public List<Store> findNearPlace(Place p) {  
        return ds.createQuery(Store.class).field("place.loc").near(p.getLoc()[0], p.getLoc()[1]).limit(5).asList();  
    }  
    /** 
     * 查找离p 最近的5个肯德基店 
     * @param p 
     * @return 
     */ 
    public List<Store> findKFCNearPlace(Place p) {  
        return ds.createQuery(Store.class).filter("name", "肯德基").field("place.loc").near(p.getLoc()[0], p.getLoc()[1]).limit(5).asList();  
    }  
    /** 
     * 删除所有店铺 
     */ 
    public void deleteAllStore(){  
        Query<Store> q = ds.createQuery(Store.class);  
        ds.delete(q);  
    }  

 
package morphia.dao;
import java.util.List;
import morphia.model.Place;
import morphia.model.Store;
import com.google.code.morphia.Datastore;
import com.google.code.morphia.dao.BasicDAO;
import com.google.code.morphia.query.Query;
 
public class StoreDao extends BasicDAO<Store, String> {
       public StoreDao(Datastore ds) {
              super(ds);
              ds.ensureIndexes();
              ds.ensureCaps();
       }
       /**
        * 查找离p 最近的5个店铺
        * @param p
        * @return
        */
       public List<Store> findNearPlace(Place p) {
              return ds.createQuery(Store.class).field("place.loc").near(p.getLoc()[0], p.getLoc()[1]).limit(5).asList();
       }
       /**
        * 查找离p 最近的5个肯德基店
        * @param p
        * @return
        */
       public List<Store> findKFCNearPlace(Place p) {
              return ds.createQuery(Store.class).filter("name", "肯德基").field("place.loc").near(p.getLoc()[0], p.getLoc()[1]).limit(5).asList();
       }
       /**
        * 删除所有店铺
        */
       public void deleteAllStore(){
              Query<Store> q = ds.createQuery(Store.class);
              ds.delete(q);
       }
}
 
 
    接下来就可以写测试类了:
 
 
package mongo.morphia.test;  
import java.util.List;  
import morphia.dao.PlaceDao;  
import morphia.dao.StoreDao;  
import morphia.model.Place;  
import morphia.model.Store;  
import com.google.code.morphia.Datastore;  
import com.google.code.morphia.Morphia;  
import com.mongodb.Mongo;  
public class StoreDaoTest {  
    public static String[] STORE_TYPE = {"肯德基","麦当劳","必胜客","吉野家","蒸功夫"};  
    public static StoreDaoTest m = new StoreDaoTest();  
    static DaoHolder daoHolder = new DaoHolder();  
    //测试保存,准备一千家店铺的数据  
    public void testSave(){  
        long start = System.currentTimeMillis();  
        for( int i = 0; i < 1000; i++){  
            double x = Math.round(Math.random() * 10000)/100.0D;  
            double y = Math.round(Math.random() * 10000)/100.0D;  
            Place p = new Place("Place_"+x+"_"+y,new double[]{x,y});  
            Store s = new Store(STORE_TYPE[i%5],STORE_TYPE[i%5]+"@"+p.getName(),p);  
            daoHolder.storeDao.save(s);  
        }  
        System.out.println(System.currentTimeMillis() - start);  
    }  
    //测试删除  
    public void testDeleteAll(){  
        System.out.println("Before delete the number of stores is: " + daoHolder.storeDao.count());  
        daoHolder.storeDao.deleteAllStore();  
        System.out.println("After delete the number of stores is: " + daoHolder.storeDao.count());  
    }  
    //根据地理位置查找  
    public void testFindNearPlace(){  
        Place p = new Place("somewhere",new double[]{23.5,67.8});  
        System.out.println("Find 5 stores near "+ p.toString());  
        List<Store> list = daoHolder.storeDao.findNearPlace(p);  
        for( Store s : list)  
            System.out.println(s.toString());  
          
        System.out.println("Find 5 KFC stores near "+ p.toString());  
        list = daoHolder.storeDao.findKFCNearPlace(p);  
        for( Store s : list)  
            System.out.println(s.toString());  
    }  
    //查找所有store  
    public void testFindAll(){  
        long start = System.currentTimeMillis();  
        List<Store> list = daoHolder.storeDao.find().asList();  
        for( Store s : list)  
            System.out.println(s.toString());  
        System.out.println(System.currentTimeMillis() - start);  
    }  
      
    static class DaoHolder{  
        PlaceDao placeDao;  
        StoreDao storeDao;  
        public DaoHolder(){  
            try {  
                Mongo mongo = new Mongo("localhost",27017);  
                Morphia morphia = new Morphia();  
                Datastore ds = morphia.createDatastore(mongo, "testDB");  
                placeDao = new PlaceDao(ds);  
                storeDao = new StoreDao(ds);  
            } catch (Exception e) {  
                e.printStackTrace();  
            }  
        }  
    }  

 
package mongo.morphia.test;
import java.util.List;
import morphia.dao.PlaceDao;
import morphia.dao.StoreDao;
import morphia.model.Place;
import morphia.model.Store;
import com.google.code.morphia.Datastore;
import com.google.code.morphia.Morphia;
import com.mongodb.Mongo;
public class StoreDaoTest {
       public static String[] STORE_TYPE = {"肯德基","麦当劳","必胜客","吉野家","蒸功夫"};
       public static StoreDaoTest m = new StoreDaoTest();
       static DaoHolder daoHolder = new DaoHolder();
       //测试保存,准备一千家店铺的数据
       public void testSave(){
              long start = System.currentTimeMillis();
              for( int i = 0; i < 1000; i++){
                     double x = Math.round(Math.random() * 10000)/100.0D;
                     double y = Math.round(Math.random() * 10000)/100.0D;
                     Place p = new Place("Place_"+x+"_"+y,new double[]{x,y});
                     Store s = new Store(STORE_TYPE[i%5],STORE_TYPE[i%5]+"@"+p.getName(),p);
                     daoHolder.storeDao.save(s);
              }
              System.out.println(System.currentTimeMillis() - start);
       }
       //测试删除
       public void testDeleteAll(){
              System.out.println("Before delete the number of stores is: " + daoHolder.storeDao.count());
              daoHolder.storeDao.deleteAllStore();
              System.out.println("After delete the number of stores is: " + daoHolder.storeDao.count());
       }
       //根据地理位置查找
       public void testFindNearPlace(){
              Place p = new Place("somewhere",new double[]{23.5,67.8});
              System.out.println("Find 5 stores near "+ p.toString());
              List<Store> list = daoHolder.storeDao.findNearPlace(p);
              for( Store s : list)
                     System.out.println(s.toString());
             
              System.out.println("Find 5 KFC stores near "+ p.toString());
              list = daoHolder.storeDao.findKFCNearPlace(p);
              for( Store s : list)
                     System.out.println(s.toString());
       }
       //查找所有store
       public void testFindAll(){
              long start = System.currentTimeMillis();
              List<Store> list = daoHolder.storeDao.find().asList();
              for( Store s : list)
                     System.out.println(s.toString());
              System.out.println(System.currentTimeMillis() - start);
       }
      
       static class DaoHolder{
              PlaceDao placeDao;
              StoreDao storeDao;
              public DaoHolder(){
                     try {
                            Mongo mongo = new Mongo("localhost",27017);
                            Morphia morphia = new Morphia();
                            Datastore ds = morphia.createDatastore(mongo, "testDB");
                            placeDao = new PlaceDao(ds);
                            storeDao = new StoreDao(ds);
                     } catch (Exception e) {
                            e.printStackTrace();
                     }
              }
       }
}
 
 
    首先, 通过调用StoreDaoTest.m.testSave()保存一千家店铺,用来做数据准备。
 
     其次,通过调用StoreDaoTest.m.testFindAll()查看数据是否ok,当然也可以通过shell窗口查看。
 
     现在可以通过StoreDaoTest.m.testFindNearPlace()来查找地方p附近的相关店铺了,在这个方法中,我查了两次,一次是查找离p[loc=[23.5, 67.8], name=somewhere]最近的任意五个店铺,dao中这样写:
 
ds.createQuery(Store.class).field("place.loc").near(p.getLoc()[0], p.getLoc()[1]).limit(5).asList();
 
第二次是查找离p[loc=[23.5, 67.8], name=somewhere]最近的五个肯德基店铺,dao中这样写:
 
ds.createQuery(Store.class).filter("name", "肯德基")
 
.field("place.loc").near(p.getLoc()[0], p.getLoc()[1]).limit(5).asList();
 
输出结果:
 
Find 5 stores near Place [loc=[23.5, 67.8], name=somewhere]
Store [desc=麦当劳@Place_24.42_67.77, id=4ef9cc2cec9dcb16b1b552d2, name=麦当劳, place=Place [loc=[24.42, 67.77], name=Place_24.42_67.77]]
Store [desc=蒸功夫@Place_24.32_70.0, id=4ef9cc2dec9dcb16b1b553b6, name=蒸功夫, place=Place [loc=[24.32, 70.0], name=Place_24.32_70.0]]
Store [desc=必胜客@Place_24.08_64.89, id=4ef9cc2dec9dcb16b1b5544f, name=必胜客, place=Place [loc=[24.08, 64.89], name=Place_24.08_64.89]]
Store [desc=肯德基@Place_21.05_65.88, id=4ef9cc2dec9dcb16b1b5539e, name=肯德基, place=Place [loc=[21.05, 65.88], name=Place_21.05_65.88]]
Store [desc=吉野家@Place_25.78_65.66, id=4ef9cc2cec9dcb16b1b551f3, name=吉野家, place=Place [loc=[25.78, 65.66], name=Place_25.78_65.66]]
Find 5 KFC stores near Place [loc=[23.5, 67.8], name=somewhere]
Store [desc=肯德基@Place_21.05_65.88, id=4ef9cc2dec9dcb16b1b5539e, name=肯德基, place=Place [loc=[21.05, 65.88], name=Place_21.05_65.88]]
Store [desc=肯德基@Place_21.13_74.42, id=4ef9cc2dec9dcb16b1b5550b, name=肯德基, place=Place [loc=[21.13, 74.42], name=Place_21.13_74.42]]
Store [desc=肯德基@Place_20.26_77.73, id=4ef9cc2cec9dcb16b1b55204, name=肯德基, place=Place [loc=[20.26, 77.73], name=Place_20.26_77.73]]
Store [desc=肯德基@Place_32.55_73.14, id=4ef9cc2cec9dcb16b1b552ae, name=肯德基, place=Place [loc=[32.55, 73.14], name=Place_32.55_73.14]]
Store [desc=肯德基@Place_19.01_77.68, id=4ef9cc2cec9dcb16b1b55209, name=肯德基, place=Place [loc=[19.01, 77.68], name=Place_19.01_77.68]]
 
 
 
 
 
     最后当然也可以通过StoreDaoTest.m.testDeleteAll() 删除所有测试数据。例子很简单,是我这个礼拜学习的一个小结吧,不罗嗦了。当然很多mongodb的操作命令就不记录了,有用到了再查吧,接下来会去学习一下spring data整合mongodb

摘自 wilson
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