mongodb-分组分页
1, 添加测试数据
@Test public void save() { News n = null; for (int i = 0; i < 10000; 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 = {"1024", "102401", "102402", "102403", "102404", "102405", "102406", "102407", "102408" , "10240101", "10240102", "10240201", "10240202", "10240301", "10240302", "10240401", "10240402" , "10240501", "10240502", "10240601", "10240602", "10240701", "10240702", "10240801", "10240802"}; 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", "22", "23", "24", "25", "26"}; 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 = 0; 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 = {1, 0}; int evalNum=(int)(Math.random() * evalArr.length);//产生0-strs.length的整数随机数 n.setEvaluate(evalArr[evalNum]); Integer[] mproArr = {1, 2, 100}; int mproNum=(int)(Math.random() * mproArr.length);//产生0-strs.length的整数随机数 n.setMediaProperty(mproArr[mproNum]); Integer[] mtypeArr = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}; int mtypeNum=(int)(Math.random() * mtypeArr.length);//产生0-strs.length的整数随机数 n.setMediaType(mtypeArr[mtypeNum]); Integer[] levelArr = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}; 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"); }
2, 使用 dbCollection进行分页:
/** * * 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); } } }
3, 使用mongotemplate 进行分组分页
/** * 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(1); 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(", *")[0])), 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; }
原地址: http://www.cnblogs.com/ontheroad_lee/p/3756247.html
http://ask.csdn.net/questions/237974
