@Test

    public  void save() {

        News n = null;

        for (int i = ; i < ; i++) {

            n = new News();

            n.setTitle("title_" + i);

            n.setUrl("url_" + i);

            //2014-01-01到2014-01-01之间的随机时间

            Date randomDate=DateUtil.randomDate("2014-01-01","2014-05-11");

            //MongoDB里如果时间类型存的是Date，那么会差8个小时的时区，因为MongoDB使用的格林威治时间，中国所处的是+8区，so……

            //比如我保存的是2014-05-01 00:00:00，那么保存到MongoDB里则是2014-05-01 08:00:00，所以为了统一方面，那就保存字符串类型，底下保存的long类型

            n.setPublishTimeStr(DateUtil.formatDateTimeByDate(randomDate));

            //long类型在查询速度中肯定会比较快

            n.setPublishTime(randomDate.getTime());

            n.setPublishDate(randomDate);

            n.setPublishMedia("publishMedia_" + i);

            String[] areaArr = {"", "", "", "", "", "", "", "", ""

                    , "", "", "", "", "", "", "", ""

                    , "", "", "", "", "", "", "", ""};

            int areaNum=(int)(Math.random() * areaArr.length);//产生0-strs.length的整数随机数

            String area = areaArr[areaNum];

            n.setArea(area);

            String[] ckeyArr = {"A101", "A102", "A201", "A202", "A203"

                    , "B101", "B102", "B103", "C201", "C202", "C203", "", "", "", "", ""};

            int ckeyNum=(int)(Math.random() * ckeyArr.length);//产生0-strs.length的整数随机数

            List<String> list = new ArrayList<String>();

            for (int j = ; j < ckeyNum; j ++) {

                int ckeyNum1=(int)(Math.random() * ckeyArr.length);//产生0-strs.length的整数随机数

                list.add(ckeyArr[ckeyNum1]);

            }

            n.setClassKey(list);

            Integer[] evalArr = {, };

            int evalNum=(int)(Math.random() * evalArr.length);//产生0-strs.length的整数随机数

            n.setEvaluate(evalArr[evalNum]);

            Integer[] mproArr = {, , };

            int mproNum=(int)(Math.random() * mproArr.length);//产生0-strs.length的整数随机数

            n.setMediaProperty(mproArr[mproNum]);

            Integer[] mtypeArr = {, , , , , , , , , , };

            int mtypeNum=(int)(Math.random() * mtypeArr.length);//产生0-strs.length的整数随机数

            n.setMediaType(mtypeArr[mtypeNum]);

            Integer[] levelArr = {, , , , , , , , , , , };

            int levelNum=(int)(Math.random() * levelArr.length);//产生0-strs.length的整数随机数

            n.setLevel(levelArr[levelNum]);

            newsService.save(n);

        }

        System.out.println("OK");

    }

/**

     *

     * 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 == ){

                dto.setPositiveNum(docsNum);

            }else {

                dto.setNegativeNum(docsNum);

            }

        }

    }

    /**

     * 按日期排序显示错误的poi信息

     */

    @Override

    public PageEntity<GroupEntity> getFaildPoisByPage(Long page, Integer pageSize) {

        Criteria criteria = Criteria.where("status").is();

        Aggregation aggregationall = Aggregation.newAggregation(Aggregation.match(criteria),

                Aggregation.group("task_ids").count().as("totalCount"),

                Aggregation.sort(Sort.Direction.DESC, "totalCount"));

        AggregationResults<GroupEntity> aggResall = mongoTemplate.aggregate(aggregationall, "scrapy_error_pois",

                GroupEntity.class);

        List<GroupEntity> listResall = aggResall.getMappedResults();

        long totalCount = listResall.size();

        System.out.println(totalCount);

        PageEntity<GroupEntity> pageEntity = new PageEntity<>();

        pageEntity.setPage(page);

        pageEntity.setPageSize(pageSize);

        pageEntity.setTotalCount(totalCount);

        @SuppressWarnings("deprecation")

        Aggregation aggregation = Aggregation.newAggregation(Aggregation.match(criteria),

                Aggregation.group("task_ids").count().as("totalCount"),

                Aggregation.sort(Sort.Direction.DESC, "totalCount"), Aggregation.skip(pageEntity.getStart().intValue()),

                Aggregation.limit(pageSize));

        // Aggregation.skip(1), Aggregation.limit(3));

        // System.out.println("--mongoDBSQL--" + aggregation.toString());

        AggregationResults<GroupEntity> aggRes = mongoTemplate.aggregate(aggregation, "scrapy_error_pois",

                GroupEntity.class);

        // BasicDBList bdbl =(BasicDBList) aggRes.getRawResults().get("result");

        List<GroupEntity> listRes = aggRes.getMappedResults();

        for (GroupEntity error : listRes) {

            ScrapyJob scrapyJob = mongoTemplate.findOne(

                    Query.query(Criteria.where("_id").is(error.get_id().split(", *")[])), ScrapyJob.class);

//            error.setTask_one_id(scrapyJob.getTask_name());

            error.setTask_one_id(scrapyJob == null ? DateUtils.getDate() : scrapyJob.getTask_name());

            // System.out.println(error.get_id());

        }

        pageEntity.setRows(listRes);

        return pageEntity;

    }