MongoTemplate的使用

1.去重

mongoTemplate.getCollection(collectionName).distinct() 返回list集合，是去重后的结果

2.聚合

Aggregation aggregation=Aggregation.newAggregation(Criteria.where("").is()),Aggregation.group().first().addToSet());

3.查询

mongoTemplate.find()

4.简单的分组查询--使用Mongo本身提供的AggregationOutput进行分组查询

/**
     * 
     * 功能：使用Mongo本身提供的AggregationOutput进行分组查询
     * 参数：   
     * 创建人：OnTheRoad_Lee 
     * 修改人：OnTheRoad_Lee 
     * 最后修改时间：2014-5-26
     */
    public void testGroup1 () {
        //按照eval字段进行分组，注意$eval必须是存在mongodb里面的字段，不能写$evaluate(此字段是News类中定义的，和存入mongodb中的有区别)
        //{$group:{_id:{'AAA':'$BBB'},CCC:{$sum:1}}}固定格式：把要分组的字段放在_id:{}里面，BBB是mongodb里面的某个字段，AAA是BBB的重命名，CCC是$sum:1的重命名
        //此查询语句== select eval as eval, count(*) as docsNum from news group by eval having docsNum>=85 order by docsNum desc
        //具体的mongodb和sql的对照可以参考：http://docs.mongodb.org/manual/reference/sql-aggregation-comparison/
        String groupStr = "{$group:{_id:{'eval':'$eval'},docsNum:{$sum:1}}}";
        DBObject group = (DBObject) JSON.parse(groupStr);
        String matchStr = "{$match:{docsNum:{$gte:85}}}";
        DBObject match = (DBObject) JSON.parse(matchStr);
        String sortStr = "{$sort:{_id.docsNum:-1}}";
        DBObject sort = (DBObject) JSON.parse(sortStr);
        AggregationOutput output = mongoTemplate.getCollection("news").aggregate(group, match, sort);
        System.out.println(output.getCommand());
        //转换为执行原生的mongodb查询语句
        //{ "aggregate" : "news" , "pipeline" : [ { "$group" : { "_id" : { "eval" : "$eval"} , "docsNum" : { "$sum" : 1}}} , { "$match" : { "docsNum" : { "$gte" : 85}}} , { "$sort" : { "_id.docsNum" : -1}}]}
        System.out.println(output.getCommandResult());
        //查询结果
        //{ "serverUsed" : "localhost/127.0.0.1:47017" , "result" : [ { "_id" : { "evaluate" : 1} , "docsNum" : 9955} , { "_id" : { "evaluate" : 0} , "docsNum" : 10047}] , "ok" : 1.0}
        
        //也可以把查询结果封装到NewsNumDTO，这样以一个dto对象返回前台操作就更容易了
        NewsNumDTO dto = new NewsNumDTO();
        for( Iterator< DBObject > it = output.results().iterator(); it.hasNext(); ){
            BasicDBObject dbo = ( BasicDBObject ) it.next();
            BasicDBObject keyValus = (BasicDBObject)dbo.get("_id");
            int eval = keyValus.getInt("eval");
            long docsNum = ((Integer)dbo.get("docsNum")).longValue();
            if(eval == 1){
                dto.setPositiveNum(docsNum);
            }else {
                dto.setNegativeNum(docsNum);
            }
        }
        
    }

5.获取和testGroup1方法同样结果的另一种写法，Spring Data MongoDB隆重登场，语法更加简洁易懂

/**
     * 
     * 功能：获取和testGroup1方法同样结果的另一种写法，Spring Data MongoDB隆重登场，语法更加简洁易懂
     * 参数：   
     * 创建人：OnTheRoad_Lee 
     * 修改人：OnTheRoad_Lee 
     * 最后修改时间：2014-5-26
     */
    public void testAggregation1() {
        TypedAggregation<News> agg = Aggregation.newAggregation(
                News.class,
                project("evaluate")
                ,group("evaluate").count().as("totalNum")
                ,match(Criteria.where("totalNum").gte(85))
                ,sort(Sort.Direction.DESC, "totalNum")
            );

            AggregationResults<BasicDBObject> result = mongoTemplate.aggregate(agg, BasicDBObject.class);
            System.out.println(agg.toString());
            //执行语句差不多
            //{ "aggregate" : "__collection__" , "pipeline" : [ { "$project" : { "evaluate" : 1}} , { "$group" : { "_id" : "$evaluate" , "totalNum" : { "$sum" : 1}}} , { "$match" : { "totalNum" : { "$gte" : 85}}} , { "$sort" : { "totalNum" : -1}}]}
            System.out.println(result.getMappedResults());
            //查询结果简洁明了
            //[{ "_id" : 0 , "totalNum" : 10047}, { "_id" : 1 , "totalNum" : 9955}]
            
            //使用此方法，如果封装好了某一个类，类里面的属性和结果集的属性一一对应，那么，Spring是可以直接把结果集给封装进去的
            //就是AggregationResults<BasicDBObject> result = mongoTemplate.aggregate(agg, BasicDBObject);中的BasicDBObject改为自己封装的类
            //但是感觉这样做有点不灵活，其实吧，应该是自己现在火候还不到，还看不到他的灵活性，好处在哪里；等火候旺了再说呗
            //所以，就用这个万能的BasicDBObject类来封装返回结果
            List<BasicDBObject> resultList = result.getMappedResults();
            NewsNumDTO dto = new NewsNumDTO();
            for(BasicDBObject dbo : resultList){
                int eval = dbo.getInt("_id");
                long num = dbo.getLong("totalNum");
                if(eval == 1){
                    dto.setPositiveNum(num);
                }else {
                    dto.setNegativeNum(num);
                }
            }
            System.out.println(dto.getPositiveNum());
    }

6、previousOperation的简单使用--为分组的字段（_id）建立别名

/**
     * 
     * 功能：previousOperation的简单使用--为分组的字段（_id）建立别名
     * 参数：   
     * 创建人：OnTheRoad_Lee 
     * 修改人：OnTheRoad_Lee 
     * 最后修改时间：2014-5-26
     */
    public void testAggregation2() {
        TypedAggregation<News> agg = Aggregation.newAggregation(
                News.class,
//                match(Criteria.where("mediaType").is(100))
                project("evaluate")
                ,group("evaluate").count().as("totalNum")
                ,project("evaluate", "totalNum")
                    .and("eval").previousOperation()
                    //为分组的字段（_id）建立别名
            );
            AggregationResults<BasicDBObject> result = mongoTemplate.aggregate(agg, BasicDBObject.class);
            System.out.println(agg.toString());
//            { "aggregate" : "__collection__" , "pipeline" : [ { "$project" : { "evaluate" : 1}} , { "$group" : { "_id" : "$evaluate" , "totalNum" : { "$sum" : 1}}} , { "$project" : { "evaluate" : "$_id.evaluate" , "totalNum" : 1 , "_id" : 0 , "eval" : "$_id"}}]}
            System.out.println(result.getMappedResults());
//            [{ "totalNum" : 10047 , "eval" : 0}, { "totalNum" : 9955 , "eval" : 1}]
    }

7.Spring Data MongoDB，按照时间（字符串）分组

/**
     * 
     * 功能：Spring Data MongoDB，按照时间（字符串）分组
     * 参数：   
     * 创建人：OnTheRoad_Lee 
     * 修改人：OnTheRoad_Lee 
     * 最后修改时间：2014-5-26
     */
    public void testAggregation4() {
        TypedAggregation<News> agg = Aggregation.newAggregation(
                News.class,
                //project().andExpression()里面是一个表达式
//                详见api：http://docs.spring.io/spring-data/data-mongodb/docs/current/reference/htmlsingle/#mongo.aggregation
//                搜索  .andExpression 定位到具体的方法模块
                project("evaluate")
                    .andExpression("substr(publishTimeStr,0,10)").as("publishDate")
                ,group("evaluate", "publishDate").count().as("totalNum")
                ,sort(Sort.Direction.DESC, "totalNum")
            );

            AggregationResults<BasicDBObject> result = mongoTemplate.aggregate(agg, BasicDBObject.class);
            System.out.println(agg.toString());
//            { "aggregate" : "__collection__" , "pipeline" : [ { "$project" : { "evaluate" : 1 , "publishDate" : { "$substr" : [ "$publishTimeStr" , 0 , 10]}}} , { "$group" : { "_id" : { "evaluate" : "$evaluate" , "publishDate" : "$publishDate"} , "totalNum" : { "$sum" : 1}}} , { "$sort" : { "totalNum" : -1}}]}
            System.out.println(result.getMappedResults());
//            [{ "evaluate" : 0 , "publishDate" : "2014-03-09" , "totalNum" : 101}, { "evaluate" : 1 , "publishDate" : "2014-02-14" , "totalNum" : 100}, { "evaluate" : 1 , "publishDate" : "2014-02-11" , "totalNum" : 99}, { "evaluate" : 0 , "publishDate" : "2014-03-17" , "totalNum" : 98}, { "evaluate" : 1 , "publishDate" : "2014-03-26" , "totalNum" : 98},  ……]
//            这个查询结果貌似不是我们想要的效果，理想，一目了然的效果应该是，以日期为单位，日期底下正面多少，负面多少：
//            [
//            { "publishDate" : "2014-03-09" , "evalInfo" : [{"evaluate" : 0 , "totalNum" : 101}, {"evaluate" : 1 , "totalNum" : 44}]}
//            { "publishDate" : "2014-03-12" , "evalInfo" : [{"evaluate" : 0 , "totalNum" : 11}, {"evaluate" : 1 , "totalNum" : 32}]},
//            ……
//            ]
//            无奈本人功力尚浅，查了N多资料，各种论坛，中文的，英文的都查了，就是找不到Spring Data MongoDB 分组方法
//            ，所以就引出了testAggregation5
    }

8.使用原生态mongodb语法，按照时间（字符串）分组，整合查询结果，使用$push命令

/**
     * 
     * 功能：使用原生态mongodb语法，按照时间（字符串）分组，整合查询结果，使用$push命令
     * 参数：   
     * 创建人：OnTheRoad_Lee 
     * 修改人：OnTheRoad_Lee 
     * 最后修改时间：2014-5-26
     */
    public void testAggregation5() {
                     
        /* Group操作*/
        String groupStr = "{$group:{_id:{'evaluate':'$eval','ptimes':{$substr:['$ptimes',0,10]}},totalNum:{$sum:1}}}";
        DBObject group = (DBObject) JSON.parse(groupStr);
                     
        /* Reshape Group Result*/
        DBObject projectFields = new BasicDBObject();
        projectFields.put("ptimes", "$_id.ptimes");
        projectFields.put("evalInfo", new BasicDBObject("evaluate","$_id.evaluate").append("totalNum", "$totalNum"));
        DBObject project = new BasicDBObject("$project", projectFields);
                     
        /* 将结果push到一起*/
        DBObject groupAgainFields = new BasicDBObject("_id", "$ptimes");
        groupAgainFields.put("evalInfo", new BasicDBObject("$push", "$evalInfo"));
        DBObject reshapeGroup = new BasicDBObject("$group", groupAgainFields);
         
        /* 查看Group结果 */
        AggregationOutput output = mongoTemplate.getCollection("news").aggregate(group, project, reshapeGroup);
        System.out.println(output.getCommand());
//        { "aggregate" : "news" , "pipeline" : [ { "$group" : { "_id" : { "evaluate" : "$eval" , "ptimes" : { "$substr" : [ "$ptimes" , 0 , 10]}} , "totalNum" : { "$sum" : 1}}} , { "$project" : { "ptimes" : "$_id.ptimes" , "evalInfo" : { "evaluate" : "$_id.evaluate" , "totalNum" : "$totalNum"}}} , { "$group" : { "_id" : "$ptimes" , "evalInfo" : { "$push" : "$evalInfo"}}}]}
        System.out.println(output.getCommandResult());
//        { "serverUsed" : "localhost/127.0.0.1:47017" , "result" : [ 
//          { "_id" : "2014-04-24" , "evalInfo" : [ { "evaluate" : 1 , "totalNum" : 67} , { "evaluate" : 0 , "totalNum" : 76}]} 
//        , { "_id" : "2014-02-05" , "evalInfo" : [ { "evaluate" : 1 , "totalNum" : 70} , { "evaluate" : 0 , "totalNum" : 84}]}
//        , { "_id" : "2014-03-21" , "evalInfo" : [ { "evaluate" : 0 , "totalNum" : 82} , { "evaluate" : 1 , "totalNum" : 89}]}}……] 
//        , "ok" : 1.0}
    }

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