spring封装mongodb的代码实现

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众所周知，spring集成的一些nosql或者sql数据库，都习惯用xxxxTemplate。一般看到xxxxTemplate，我们就可以认为是spring集成的。要和原生的使用方式区分开来。这里，我们不讨论在java项目中原生的mongodb的使用方式，单讨论spring提供的mongodb的封装。

在此之前，我们有必要了解下mongodb的数据存储格式。我一般用json格式存储，结构如下代码所示。如何查看mongodb的数据，可以使用mongoVUE工具。我们可以在Mongodb中存储数亿级别的这种数据而不影响效率。提醒一下：Mongodb不适合按照多条件查询，我们一般用id值来做查询。多条件查询时需要建索引，而且容易把库查死。

{  "_id" : "123456789",  "_class" : "com.OrderInfo",  "historyId" : "123456789_1_2",  "orderId" : NumberLong("123456789"),  "orderDirection" : "正向",  "overStatus" : "已完成",  "orgArea" : "华北",  "org" : "总公司",  "orderType" : "一般订单",  "paymentType" : "货到付款",  "paymentTpyeGroup" : "后款",  "orderPrice" : 0.0,  "duePrice" : 0.0,  "payPrice" : 1000.0,  "tuiKuanPrice" : 0.0,  "diffPrice" : -1000.0,  "memberId" : "testlzg",  "laiyuan" : "站点",  "invoicePutType" : "未开票",  "operationTime" : "20190104160726",  "status" : "完成",  "carrier" : "测试操作单位",  "ttsj" : "20190104160726",  "waybillSign" : "300000000000000",  "operateNodeSystem" : "站点-妥投",  "bizNodeType" : "站点",  "bizNodeName" : "测试操作单位",  "bizNodeCode" : "910",  "belongSystem" : "TMS",  "systemCode" : "josl",  "operater" : "张三",  "operaterErp" : "1122",  "distributeType" : "65",  "endDate" : "20190104160726",  "validTag" : "1",  "orderStatus" : "暂停",  "duizhangStatus" : "足额对账",  "updateTime" : ISODate("2016-10-10T03:16:52.068Z"),  "orgId" : "6",  "createTime" : "20161010111636",  "damagedPrice" : 0.0,  "tmplateNode" : "妥投"}

要想在spring程序中使用mongodb，我们应该怎么做呢。

首先：

引入mongodb的jar包

<dependency>            <groupId>org.springframework.data</groupId>            <artifactId>spring-data-mongodb</artifactId></dependency>

当然，如果不使用maven，你有可以单独直接下载spring-data-mongodb-1.3.3.jar引入到你的项目中。

其次：

需要在我们的spring的配置文件中增加Mongodb的配置。

<beans xmlns="http://www.springframework.org/schema/beans"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:context="http://www.springframework.org/schema/context"xmlns:mongo="http://www.springframework.org/schema/data/mongo"xsi:schemaLocation="http://www.springframework.org/schema/context          http://www.springframework.org/schema/context/spring-context-3.0.xsd          http://www.springframework.org/schema/data/mongo          http://www.springframework.org/schema/data/mongo/spring-mongo-1.0.xsd          http://www.springframework.org/schema/beans          http://www.springframework.org/schema/beans/spring-beans-3.0.xsd">    <mongo:mongo id="mongo_Test" replica-set="ip1:port1,ip2:port2"><!--配置mongodb服务器和端口，这里是基于复制级的，可以配置一主多从-->    <mongo:options connections-per-host="100"                       threads-allowed-to-block-for-connection-multiplier="4"                       connect-timeout="2000"                       max-wait-time="3000"                       auto-connect-retry="true"                       socket-keep-alive="true"                       socket-timeout="10000"                       slave-ok="true"                       write-number="1"                       write-timeout="0"                       write-fsync="false"/> <!--控制数据写的时候，是否刷新完磁盘返回-->    </mongo:mongo>    <mongo:db-factory id="mongoDbFactoryPrism" dbname="dbname" username="username" password="${password}" mongo-ref="mongo_Test"/>    <bean id="mongoTemplateTest" class="org.springframework.data.mongodb.core.MongoTemplate">        <constructor-arg name="mongoDbFactory" ref="<span style="font-family: Arial, Helvetica, sans-serif;">mongoDbFactoryPrism</span><span style="font-family: Arial, Helvetica, sans-serif;">" /></span>  <property name="writeResultChecking" value="EXCEPTION" /><!--控制mongodb是否抛异常-->  <property name="writeConcern" value="SAFE" /><!--控制mongodb的安全级别-->    </bean>    <bean id="mongoDBCache" class="com..MongoDBCacheImpl">        <property name="mongoOperations" ref="mongoTemplateTest"/>    </bean></beans>

这种配置是不是一目了然呢。spring中好多封装配置也就这样，一环扣一环，最后给我们一个可以用的手把，例如 mongoDBCache。

最后：

我们就可以通过实现我们的MongoDBCacheImpl来写我们的业务逻辑了。

public class MongoDBCacheImpl {    public void setMongoOperations(MongoOperations mongoOperations) {        this.mongoOperations = mongoOperations;    }    private MongoOperations mongoOperations;//根据key获取    public <T> T getByKey(Object key, Class<T> entityClass) {        return mongoOperations.findById(key, entityClass);    }    public <T> List<T> getByColumn(String columnName, Object columeValue, Class<T> entityClass) {        return mongoOperations.find(new Query(Criteria.where(columnName).is(columeValue)), entityClass);    }//保存    public void save(Object obj) {        mongoOperations.save(obj);    }//移除    public void remove(Object obj) {        mongoOperations.remove(obj);    }    public <T> Long getCountByDate(Date beginTime, Date endTime, Class<T> entityClass) {        Assert.notNull(beginTime, "beginTime is not null.");        Assert.notNull(endTime, "endTime is not null.");        Assert.isTrue(endTime.after(beginTime), "endTime must be after beginTime.");        return mongoOperations.count(new Query(Criteria.where("createdate").gte(beginTime).and("createdate").lt(endTime)), entityClass);    }    public <T> List<T> findAllByDate(Date beginTime, Date endTime, Class<T> entityClass) {        Assert.notNull(beginTime, "beginTime is not null.");        Assert.notNull(endTime, "endTime is not null.");        Assert.isTrue(endTime.after(beginTime), "endTime must be after beginTime.");        Query query = new Query().addCriteria(                Criteria.where("riqi").exists(true)                        .andOperator(Criteria.where("riqi").gte(beginTime),Criteria.where("riqi").lt(endTime)));        return mongoOperations.find(query, entityClass);    }    public <T> List<T> findAllByDateAndColumn(String dateColumnName, Date beginTime, Date endTime, String columnName, Object columeValue, Class<T> entityClass) {        Query query = new Query().addCriteria(                Criteria.where(dateColumnName).exists(true)                        .andOperator(Criteria.where(dateColumnName).gte(beginTime),Criteria.where(dateColumnName).lt(endTime))                        .and(columnName).is(columeValue));        return mongoOperations.find(query, entityClass);    }    //统计    public <T> Long  getCountByDateAndColumn(String dateColumnName, Date beginTime, Date endTime, String columnName, Object columeValue, Class<T> entityClass) {        Query query = new Query().addCriteria(                Criteria.where(dateColumnName).exists(true)                        .andOperator(Criteria.where(dateColumnName).gte(beginTime),Criteria.where(dateColumnName).lt(endTime))                        .and(columnName).is(columeValue));        return mongoOperations.count(query,entityClass);    }//分页查询    public <T> Pagination<T> getPageListByDateColumn(String dateColumnName, Date beginTime, Date endTime, Pagination<T> page, Class<T> entityClass) {        Query query = new Query().addCriteria(                Criteria.where(dateColumnName).exists(true)                        .andOperator(Criteria.where(dateColumnName).gte(beginTime),Criteria.where(dateColumnName).lte(endTime)));        if (null != page && page.getTotalCount()>0){                page.setTotalCount(page.getTotalCount());                query.skip(page.getFirstResult());                query.limit(page.getPageSize());        }else {            return null;        }        List<T> pageData = mongoOperations.find(query,entityClass);        page.setDatas(pageData);        return page;    }//按照Key更新    public <T> void updateByKey(Object key, String updateColumn, Object value, Class<T> entityClass) {        Query query = new Query(Criteria.where( "_id" ).is(key));        mongoOperations.updateFirst(query,Update.update(updateColumn,value),entityClass);    }//删除指定key    public <T> void deleteByKey(Object key, Class<T> entityClass) {        Query query = new Query(Criteria.where( "_id" ).is(key));        mongoOperations.remove(query,entityClass);    }//删除所有    public <T> void removeAll(String dateColumnName, Date beginTime, Date endTime, String columnName, Object columeValue, Class<T> entityClass){        Query query = new Query().addCriteria(                Criteria.where(dateColumnName).exists(true)                        .andOperator(Criteria.where(dateColumnName).gte(beginTime),Criteria.where(dateColumnName).lte(endTime))                        .and(columnName).is(columeValue));        mongoOperations.remove(query,entityClass);    }}

至此，我们就可以用mongodb对我们的数据进行增删改查了，对于复制级的mongodb，数据量在3亿以上，更新查询操作也一般在5ms之内。

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