MongoDB学习三

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MongoDB的高级操作：聚合和游标

(1)聚合操作：

<1>count

获取搜索结果的数据条数

<2>distinct

获取指定地段的集合，不允许重复

>>> db.student.find();{ "_id" : ObjectId("55eb9d9d900da635cb33f220"), "name" : "liumengyang", "city" : "dalian" }{ "_id" : ObjectId("55eb9da9900da635cb33f221"), "name" : "lidongqing", "city" :"dalian" }{ "_id" : ObjectId("55ebd440900da635cb33f222"), "name" : "ketty", "city" : "hengshui" }>>>> db.student.distinct("city");[ "dalian", "hengshui" ]

<3>group

key：要进行分组的key

initial：每组都分享的一个初始化函数

$reduce：这个函数的第一个参数就是当前的文档对象，第二个参数是上一次function操作的累计对象，第一次为initial中的函数。

condition：过滤条件

finalize：每一组文档执行完毕以后，多会触发这个方法，可以用来在集合里面加上count属性【用来表名每一组的数据量】

使用实例：

> db.student.group({... "key":{"city":true},... "initial":{"person":[]},... "$reduce":function(cur,prev){ prev.person.push(cur.name); },... "condition":{"city":{$nin:["beijing"]}},... "finalize":function(out){...... out.count = out.person.length;... }...... })[        {                "city" : "dalian",                "person" : [                        "liumengyang",                        "lidongqing"                ],                "count" : 2        },        {                "city" : "hengshui",                "person" : [                        "ketty"                ],                "count" : 1        },        {                "city" : "handan",                "person" : [                        "horse",                        "xiaowanzi"                ],                "count" : 2        },        {                "city" : "xingtai",                "person" : [                        "bird"                ],                "count" : 1        }]>

（4）mapreduce

mapreduce是一种编程模型，用在分布式计算中，包括两个函数：map函数和reduce函数

> var map = function(){... emit(this.name,{count:1});... }>>> var reduce =... function(key,value){... var result = {count:0};... for(var i=0;i<value.length;i++){... result.count += value[i].count;... }... return result;... }>>> db.student.mapReduce(map,reduce,{"out":"collection"});{        "result" : "collection",        "timeMillis" : 64,        "counts" : {                "input" : 7,                "emit" : 7,                "reduce" : 0,                "output" : 7        },        "ok" : 1}>>> db.collection.find();{ "_id" : "bird", "value" : { "count" : 1 } }{ "_id" : "horse", "value" : { "count" : 1 } }{ "_id" : "ketty", "value" : { "count" : 1 } }{ "_id" : "lidongqing", "value" : { "count" : 1 } }{ "_id" : "liumengyang", "value" : { "count" : 1 } }{ "_id" : "monkey", "value" : { "count" : 1 } }{ "_id" : "xiaowanzi", "value" : { "count" : 1 } }>>>

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