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}
}