MongoDB Basic Command Summary

MongoDB Basic Command Summary MONGO additions and deletions change

Batch update based on query criteria

> DB. Goodsinfo.update ({"Type": 1}, {$set: {"name": "Birdben"}}, False, True);

Delete data for a specified condition

> DB. Goodsinfo.remove ({goodsstatus:1});

Query modification Delete

> DB. Goodsinfo.findandmodify ({
    query: {price: {$gte: +},
    sort: {Price:-1},
    update: {$set: {name: ' Birdben '} , $inc: {price:10}},
    remove:true
});

> Db.runcommand ({findandmodify: "Goodsinfo",
    query: {price: {$gte: +}},
    sort: {Price:-1},
    Update: {$set: {name: ' Birdben '}, $inc: {price:10}},
    remove:true
});

MONGO Query

Query the specified column (view name, price data only)

Db. Goodsinfo.find ({"_id": "123456"}, {"Name": 1, Price:1}}). Pretty ();
Of course name can also be used with true or false, as in the case of Ture River Name:1 effect, if False is to exclude name, display column information other than name.

Distinct usage

Db. Goodsinfo.distinct ("name");
Filter the results of distinct

Interval query

Db. Goodsinfo.find ({price: {$gte: +, $lte: 200}});

Like fuzzy query

The name contains the MONGO data
db. Goodsinfo.find ({name:/mongo/});
Data db that begins with MONGO
. Goodsinfo.find ({name:/^mongo/});

or query

Db. Goodsinfo.find ({$or: [{price:100}, {price:200}]});

exists query

Db. Goodsinfo.find ({price: {$exists: true}});
Query the number of exists
db. Goodsinfo.find ({price: {$exists: true}}). Count ();

Querying sub-documents

Db. Goodsinfo.find ({"Array.key": "Value"});

Group queries

Group query for a time period, according to the main paste grouping, statistics of the number of replies per main Post db. Postinfo.aggregate ([{$match: {"Createtime": {"$gt": 1443628800000, "$lt": 1446436799000}, "Srcpostid": {$exists: true}

}}, {$group: {_id: "$srcPostId", total: {$sum: 1}}}, {$sort: {total:-1}}]); Statistics are based on the reason for rejection, the number of each reason, and the number of filtered results is greater than or equal to 5 db.  Reviewrecord.aggregate ([{$group: {_id: ' $rejectReason ', Count: {$sum: 1}}}, {$sort: {count:-1}}, {


$limit: Ten}, {$match: {count: {$gte: 5}}]); After grouping, in the number of statistics, the number of statistics after grouping is greater than or equal to 5 of how many db. Reviewrecord.aggregate ([{$group: {_id: {rejectreason: ' $rejectReason '}, Count: 
    {$sum: 1}}, {$match: {count: {$gte: 5}}}, {$group: {_id:null, Count: {$sum: 1}

}
  }
] );

Similar to Sql:select count (*) from (SELECT Rejectreason, Count from Reviewrecord GROUP by Rejectreason); Complex statistical calculations that count the total number of users per city in 2015-10-29, number of new users, number of old users, number of unusual users Db.runcommand ({"group": {"ns": "LandpushtypecoUnt "," key ": {" Cityid ": true}," initial ": {codecount:0, newcount:0, oldcount:0, errorcount:0}," $reduce ": function
　　　　(Doc,prev)
            {prev.totalcount++;
            if (doc.isnew = = 0) {prev.newcount++;
            } else {prev.oldcount++;
            } if (doc.isoldequipmement = = 1) {prev.errorcount++; }}, "condition": {"date": "2015-10-29", "Cityid": {$in: ["110000", "330100"]}}});

Reference article: http://www.open-open.com/lib/view/open1392709240428.html http://docs.mongoing.com/manual-zh/core/ Single-purpose-aggregation.html http://docs.mongoing.com/manual-zh/reference/sql-aggregation-comparison.html