mongodb笔记

最新推荐文章于 2025-11-24 15:52:13 发布

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#数据库 #大数据 #java

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1.查询数组只返回数组中存在的该条件的数组. db.tablename.find({"arryname.fieldname":value},{"arryname.$":1}) 如果有多条匹配，只返回第一条

2.根据mongodb自带的objectId(_id)来查询

db.wf_definitions.find({"_id":new ObjectId("53747052e4b080e26b0c0f22")})

java代码：

BasicDBObject bdb=new BasicDBObject("_id",new ObjectId("53747052e4b080e26b0c0f22"));

dbCollection.find(bdb);

3.删除数组对象内嵌文档

db.*****.update(
    {
        "_id" : new ObjectId("537ee7087c1f6fef727d9889"),
        "stepdefinitions.stepnumber":"end"
    },
     {
        "$pull":{"stepdefinitions":{"stepnumber":"end"}}
    }
);

4.mongodb使用了剥离后需要统计记录的条数

db.****.aggregate({"$unwind":"$*"},{"$match":{"****":"admin"}}, {"$group": { "_id": null, "count": { "$sum": 1 } }})

5.mongodb的group by 类似 mapreduce使用。

map的必须要使用emit函数，reduce 的vals 是emit第二个参数的集合

finalize 会重新解析返回数据

db.runCommand({ mapreduce: "wf_definitions", 
 map : function () {
var desc=this.description;

 if(this.status=='disable'){
  desc=desc+'(已停用)';
 }
emit(this.defname,{"description":desc,"status":this.status});
},
 reduce : function(key, vals) {  
 var desc=vals[0];
 var i=0;
 for(;i< vals.length;i++){
  if(vals[i].status=='enable'){
  desc=vals[i];
   break;
  }
 }
    return desc;  
} ,
 finalize : function (key, reduced) {
 return {"defname":key,"description":reduced.description,"status":reduced.status};
},
 query : { "$or" : [{ "defname" : { "$in" : ["工作转交子流程", "慰问子流程_产假", "员工", "新建测试使用工作流"] } }, { "status" : "enable" }] },
 keeptemp : false
 });

mongodb和sql 的转换对应:

MongoDB MySQL

aggregate: "DenormAggTable"

FROM DenormAggTable

{
    $match : {
        Filter1 : {$in : ['A','B']},
        Filter2 : 'C',
        Filter3 : {$gt : 123}
    }
}

WHERE (Filter1 IN (’A’,’B’))
  AND (Filter2 = ‘C’)
  AND (Filter3 > 123)

{
    $project : {
        Dim1 : 1,
        Dim2 : 1,
        Measure1 : 1,
        Measure2 : 1,
        lessThanAHundred : {
            $cond: [ 
                {$lt: ["$Measure2", 100] },
                "$Measure2", // if
                0]           // else
        }
    }
}

CASE
  WHEN Measure2 < 100
  THEN Measure2
END

{
    $group : {
        _id : {Dim1 : 1, Dim2 : 1},
        MSum : {$sum : "$Measure1"},
        RecordCount : {$sum : 1},
        MAvg : {$avg : "$Measure2"},
        MMin : {$min : "$Measure1"},
        MMax : {$max : "$lessThanAHundred"}
    }
}

SELECT
  Dim1, Dim2,
  SUM(Measure1) AS MSum,
  COUNT(*) AS RecordCount,
  AVG(Measure2) AS MAvg,
  MIN(Measure1) AS MMin
  MAX(CASE
    WHEN Measure2 < 100
    THEN Measure2
  END) AS MMax
 
GROUP BY Dim1, Dim2