MongoDB 聚合Group
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原文:http://blog.csdn.net/congcong68/article/details/45012717
一.简介
db.collection.group()使用javascript,它受到了一些性能上的限制。大多数情况下,$ group在Aggregation Pipeline提供了一种具有较少的限制适用的替代。可以通过指定的键的集合中的文档和执行简单的聚合函数。在2.2版本中,返回的数组可以包含最多20000个元素;即最多20000个独特的分组。
我们比较熟悉的group by 的sql语句select key from table groupby key,而mongoDB没提供SQL那样通过Group By就轻松实现数据库的分组功能,我们通过接口来实现的
db.collection.group({ key, reduce, initial[, keyf] [, cond] [, finalize] })
key |
作为分组的key |
reduce |
一个聚合函数操作文档的分组操作期间。这些函数可以返回一个sum或count。该函数接受两个参数:当前文档和这个群体聚集的结果文档。 |
initial |
初始化聚合结果文档变量,为空时自动为每列提供初始变量。 |
keyf |
可选。替代的key 字段。指定一个函数创建一个“key object”作为分组的key。使用keyf而是通过group by领域而不是现有的文档域键组。 |
cond |
过滤条件 |
finalize |
在db.collection.group()返回最终结果之前,此功能可以修改的结果文档或替换的结果文档作为一个整体。 |
二.Mongo VUE操作Group By
1.MonogoDB数据库中添加了订单的数据
- /* 0 */
- {
- "_id" : ObjectId("552a330e05c27486b9b9b650"),
- "_class" : "com.mongo.model.Orders",
- "onumber" : "002",
- "date" : ISODate("2014-01-03T16:03:00Z"),
- "cname" : "zcy",
- "item" : {
- "quantity" : 1,
- "price" : 4.0,
- "pnumber" : "p002"
- }
- }
- /* 1 */
- {
- "_id" : ObjectId("552a331d05c275d8590a550d"),
- "_class" : "com.mongo.model.Orders",
- "onumber" : "003",
- "date" : ISODate("2014-01-04T16:03:00Z"),
- "cname" : "zcy",
- "item" : {
- "quantity" : 10,
- "price" : 2.0,
- "pnumber" : "p001"
- }
- }
- /* 2 */
- {
- "_id" : ObjectId("552a333105c2f28194045a72"),
- "_class" : "com.mongo.model.Orders",
- "onumber" : "003",
- "date" : ISODate("2014-01-04T16:03:00Z"),
- "cname" : "zcy",
- "item" : {
- "quantity" : 30,
- "price" : 4.0,
- "pnumber" : "p002"
- }
- }
- /* 3 */
- {
- "_id" : ObjectId("552a333f05c2b62c01cff50e"),
- "_class" : "com.mongo.model.Orders",
- "onumber" : "004",
- "date" : ISODate("2014-01-05T16:03:00Z"),
- "cname" : "zcy",
- "item" : {
- "quantity" : 5,
- "price" : 4.0,
- "pnumber" : "p002"
- }
- }
2.MongoDB实现分组并统计
1)我们要对日期和产品编码进行分组,并计算相同的产品的数量
Sql语句:Select date, pnumber,sum(quantity) as total from orders,items group by date, pnumber(少了两张表的关联的条件)
MongoDB:
db.orders.group({
key: { date:1,‘item.pnumber‘:1},
initial : {"total":0},
reduce : function Reduce(doc, out) {
out.total+=doc.item.quantity
} });
结果:
2)实现一天卖出了多少个产品,金额是多少,平均价格是多少
db.orders.group({
key: {date:1},
initial :{"total":0,"money":0},
reduce : function Reduce(doc, out) {
out.total+=doc.item.quantity;
out.money+=doc.item.quantity*doc.item.price;
},
finalize : function Finalize(out) {
out.avg=out.money/out.total
returnout;
}
});
结果:
3)keyf的使用
keyf 对日期进行处理并以作为key来进来分组
db.orders.group({
keyf: function (doc){
return{‘month‘:doc.date.getMonth()+1};
},
initial :{"total":0,"money":0},
reduce : function Reduce(doc, out) {
out.total+=doc.item.quantity;
out.money+=doc.item.quantity*doc.item.price;
},
finalize : function Finalize(out) {
out.avg=out.money/out.total
returnout;
}
});
结果:
三.Java MongoDB 实现
1)我们要对日期和产品编码进行分组,并计算相同的产品的数量
- <strong> </strong> @Override
- public void getGroupCount(String collectionName) {
- BasicDBObject key = new BasicDBObject();
- key.put("date", 1);
- key.put("item.pnumber", 1);
- //条件
- BasicDBObject cond = new BasicDBObject();
- //初始化
- BasicDBObject initial = new BasicDBObject();
- initial.append("total", 0);
- //reduce
- String reduce = "function Reduce(doc, out) { " +
- " out.total+=doc.item.quantity;" +
- "}";
- SimpleDateFormat format=new SimpleDateFormat("yyyy-mm-dd");
- BasicDBList groupList=(BasicDBList) mongoTemplate.getCollection(collectionName).group(key, cond, initial, reduce);
- if(groupList!=null&&groupList.size()>0){
- System.out.println("date item.pnumber total");
- for(int i=0;i<groupList.size();i++){
- BasicDBObject obj=(BasicDBObject) groupList.get(i);
- System.out.println(format.format(obj.getDate("date"))+" "+obj.getString("item.pnumber")+" "+obj.getInt("total"));
- }
- }
- }
结果:
2)实现一天卖出了多少个产品,金额是多少,平均价格是多少
- @Override
- public void getGroupAvg(String collectionName) {
- BasicDBObject key = new BasicDBObject();
- key.put("date", 1);
- //条件
- BasicDBObject cond = new BasicDBObject();
- //初始化
- BasicDBObject initial = new BasicDBObject();
- initial.append("total", 0);
- initial.append("money", 0.0);
- //reduce
- String reduce = "function Reduce(doc, out) { " +
- " out.total+=doc.item.quantity;" +
- " out.money+=doc.item.quantity*doc.item.price;" +
- "}";
- String finalize="function Finalize (out) { " +
- " out.avg=out.money/out.total;" +
- " return out;" +
- "}";
- SimpleDateFormat format=new SimpleDateFormat("yyyy-mm-dd");
- BasicDBList groupList=(BasicDBList) mongoTemplate.getCollection(collectionName).group(key, cond, initial, reduce, finalize);
- if(groupList!=null&&groupList.size()>0){
- System.out.println("date total money avg");
- for(int i=0;i<groupList.size();i++){
- BasicDBObject obj=(BasicDBObject) groupList.get(i);
- System.out.println(format.format(obj.getDate("date"))+" "+obj.getInt("total")+" "+obj.getInt("money")+" "+obj.getDouble("avg"));
- }
- }
- }
结果:
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