比较常用的有：
•$project - 可以重构数据•$match - 可以实现类似query的功能•$limit - 限制返回个数•$skip - 同上•$unwind - 可以将一个包含数组的文档切分成多个, 比如你的文档有数组字段 A, A中有10个元素, 那么 经过 $unwind处理后会产生10个文档，这些文档只有 字段 A不同•$group - 统计操作， 还提供了一系列子命令 –$avg, $sum …•$sort - 排序
接下来要实现4个功能：
task 1：统计上海学生平均年龄 从这个需求来讲，要实现功能要有几个步骤: 1. 找出上海的学生. 2. 统计平均年龄 (当然也可以先算出所有省份的平均值再找出上海的)。select province, avg(age) from student where province = '上海' group by province
java代码：
/*创建 $match, 作用相当于query*/ DBObject match = new BasicDBObject("$match", new BasicDBObject("province", "上海")); /* Group操作*/ DBObject groupFields = new BasicDBObject("_id", "$province"); groupFields.put("AvgAge", new BasicDBObject("$avg", "$age")); DBObject group = new BasicDBObject("$group", groupFields); /* 查看Group结果 */ AggregationOutput output = connection.aggregate(match, group); // 执行 aggregation命令 System.out.println(output.getCommandResult());
输出结果：
"result" : [ { "_id" : "上海" , "AvgAge" : 32.09375} ] , "ok" : 1.0
task2：统计每个省各科平均成绩
首先更具数据库文档结构，subjects是数组形式，需要先分组，然后再进行统计
主要处理步骤如下：
1.先用$unwind 拆数组 2. 按照 province, subject 分租并求各科目平均分
/* 创建 $unwind 操作, 用于切分数组*/ DBObject unwind = new BasicDBObject("$unwind", "$subjects"); /* Group操作*/ DBObject groupFields = new BasicDBObject("_id", new BasicDBObject("subjname", "$subjects.name").append("province", "$province")); groupFields.put("AvgScore", new BasicDBObject("$avg", "$subjects.scores")); DBObject group = new BasicDBObject("$group", groupFields); /* 查看Group结果 */ AggregationOutput output = connection.aggregate(unwind, group); // 执行 aggregation命令 System.out.println(output.getCommandResult()); 输出结果：
"result" : [ { "_id" : { "subjname" : "英语" , "province" : "海南"} , "AvgScore" : 58.1} , { "_id" : { "subjname" : "数学" , "province" : "海南"} , "AvgScore" : 60.485} , { "_id" : { "subjname" : "语文" , "province" : "江西"} , "AvgScore" : 55.538} , { "_id" : { "subjname" : "英语" , "province" : "上海"} , "AvgScore" : 57.65625} , { "_id" : { "subjname" : "数学" , "province" : "广东"} , "AvgScore" : 56.690} , { "_id" : { "subjname" : "数学" , "province" : "上海"} , "AvgScore" : 55.671875} , { "_id" : { "subjname" : "语文" , "province" : "上海"} , "AvgScore" : 56.734375} , { "_id" : { "subjname" : "英语" , "province" : "云南"} , "AvgScore" : 55.7301 } , . . . . "ok" : 1.0 task3:
将同一省份的科目成绩统计到一起( 即，期望 ‘province’:’xxxxx’, avgscores:[ {‘xxx’:xxx}, ….] 这样的形式)
要做的有一件事，在前面的统计结果的基础上，先用 project将平均分和成绩揉到一起，再按省份group，将各科目的平均分push到一块,使用 group 再次分组.
Mongo m = new Mongo("localhost", 27017);DB db = m.getDB("test");DBCollection coll = db.getCollection("student");/* 创建 $unwind 操作, 用于切分数组*/DBObject unwind = new BasicDBObject("$unwind", "$subjects");/* Group操作*/DBObject groupFields = new BasicDBObject("_id", new BasicDBObject("subjname", "$subjects.name").append("province", "$province"));groupFields.put("AvgScore", new BasicDBObject("$avg", "$subjects.scores"));DBObject group = new BasicDBObject("$group", groupFields);/* Reshape Group Result*/DBObject projectFields = new BasicDBObject();projectFields.put("province", "$_id.province");projectFields.put("subjinfo", new BasicDBObject("subjname","$_id.subjname").append("avgscore", "$AvgScore"));DBObject project = new BasicDBObject("$project", projectFields);/* 将结果push到一起*/DBObject groupAgainFields = new BasicDBObject("_id", "$province");groupAgainFields.put("avginfo", new BasicDBObject("$push", "$subjinfo"));DBObject reshapeGroup = new BasicDBObject("$group", groupAgainFields);/* 查看Group结果 */AggregationOutput output = coll.aggregate(unwind, group, project, reshapeGroup);System.out.println(output.getCommandResult()); "result" : [ { "_id" : "辽宁" , "avginfo" : [ { "subjname" : "数学" , "avgscore" : 56.46666666666667} , { "subjname" : "英语" , "avgscore" : 52.093333333333334} , { "subjname" : "语文" , "avgscore" : 50.53333333333333}]} , { "_id" : "四川" , "avginfo" : [ { "subjname" : "数学" , "avgscore" : 52.72727272727273} , { "subjname" : "英语" , "avgscore" : 55.90909090909091} , { "subjname" : "语文" , "avgscore" : 57.59090909090909}]} , { "_id" : "重庆" , "avginfo" : [ { "subjname" : "语文" , "avgscore" : 56.077922077922075} , { "subjname" : "英语" , "avgscore" : 54.84415584415584} , { "subjname" : "数学" , "avgscore" : 55.33766233766234}]} , { "_id" : "安徽" , "avginfo" : [ { "subjname" : "英语" , "avgscore" : 55.458333333333336} , { "subjname" : "数学" , "avgscore" : 54.47222222222222} , { "subjname" : "语文" , "avgscore" : 52.80555555555556}]} . . . ] , "ok" : 1.0}
task4:
DBCollection collection = MongoUtils.getCollection_Database( (String) ServletContextUtils.getSession().getAttribute( "game"), SysConst.TABLE_WAIGUA_RATIO); // query DBObject match = new BasicDBObject("$match", queryParam_n); // 利用$project拼装group需要的数据 DBObject fields = new BasicDBObject("name", 1); fields.put("count", 1); DBObject project = new BasicDBObject("$project", fields); DBObject groupFields = new BasicDBObject("_id", "$name"); groupFields.put("count", new BasicDBObject("$sum", "$count")); DBObject group = new BasicDBObject("$group", groupFields);// group DBObject limit = new BasicDBObject("$limit", Integer.parseInt(n)); DBObject sort = new BasicDBObject("$sort", new BasicDBObject( "count", -1)); AggregationOutput output = collection.aggregate(match, project, group, sort, limit); List nameList = new ArrayList (); for (DBObject obj : output.results()) { BasicDBObject obj2 = (BasicDBObject) obj; nameList.add(obj2.getString("_id")); }