MongoDB Aggregation Operations (group, aggregate, MapReduce operations)

#MongoDb Aggregation method group Aggrate mapreduce#1. Group (shard not supported, distributed calculation)*Grammatical Structure<pre>Db.collection.group ({key:{category:1},//Classification according to categorycond:{shop_price:{$gt: 20}},//a product with an additional condition of more than 20Reducefunction(Curr, result) {//Curr identifies a row of records, the result of a custom variable,}, Initial:{total:0},//initialize variables, variables defined here can be obtained in the reduce method, Result.totalFinalizefunction(Result) {//after the final grouping, a result is obtained and the result is processed        }    }); </pre> *working with Max<pre>Db.collection.group ({key:{category:1}, # Classification according to category cond:{}, # Additional conditional commodity borrow a commodity greater than 20 reduce:function(Curr, result) {# Curr identifies a row of records, a result-custom variable,if(Curr >result.total) $result. Total=Curr.shop_price; }, Initial:{total:0}, # Initialize variables, variables defined here can be obtained in the reduce method, Result.total Finalize:function(Result) {# After the last grouping, a result is obtained, then the result is processed}}); </pre> *Handling Avg<pre>Db.collection.group ({key:{category:1}, # classify cond:{shop_price:{$GT according to Category:20}}, # Additional conditional commodity borrow a commodity greater than 20 reduce:function(Curr, result) {# Curr identifies a row of records, a result-custom variable, Result.count+ = 1; Result.total+=parsefloat (Curr.shop_price); }, Initial:{total:0,count:0,avg:0}, # Initialize variables, variables defined here can be obtained in the reduce method, Result.total Finalize:function(Result) {# After the last grouping, a result is obtained and the result is processed result.avg= Result.total/Result.count;    }            }); </pre>2. Aggregate*Grammatical Structure<pre>db.collection.aggregate ([{}, {}, .......,]); </pre> *$group a select in SQL. According to the CAT_ID and color classification of the goods, and then find out the inventory quantity of the classified goods<pre>[{$group: {_id:{cat_id:"$cat _id", Color: "$color"}, total:{$sum: "$goods _number"}}}            ]        </pre> *$project like a select in SQL, take out the cat_id,goods_name of the commodity table and do not go out of the _id field<pre>[{$project: {_id:0, Cat_id:1, goods_name:1}}        ]        </pre> *$match match criteria to take out a product with a category ID of 3 or a price greater than 200 yuan<pre>[{$math: {$or: [{cat_id:3}, {price:{$GT: 200}}]}}        ]        </pre> *$unwind the Split field, (the field must be an array, otherwise an error)<pre>Data model:shoes {_id:1, feature:["man", "big", "Black", "cheap"]} Command:db.shoes.aggregate ([{$unwind:"$feature"}]) Output: {_id:1,feature: "Man"} {_id:1,feature: "Big"} {_id:1,feature: "Black"} {_id:1,feature: "Cheap"}        </pre> * $redact [Edit condition] (http://docs.mongodb.org/manual/reference/operator/aggregation/redact/#pipe. _s_redact)*only 30 records are $limit restricted conditions<pre>[{$limit:30}        ]        </pre> * $sort sorted according to commodity inventory positive order, 1/positive sequence -1/Reverse<pre>[{$sort: {goods_number:1,}} ]        </pre> * $geoNear [distance calculation] (http://docs.mongodb.org/manual/reference/operator/aggregation/geonear/#pipe. _s_geonear)*Skip 20 lines $skip Skip Rows<pre>[{$skip:20}        ]        </pre> *$out Output The matching results to another collection, take the item with a price greater than 3000 out of the Cat_id,goods_name,goods_number field, do not go out of the _id field, and then sort by the cat_id,color of the item, and the result skips a row. Take only 30 hang records and push the results into the result set<pre>[{$math: {goods_price:{$gte:3000}}}, {$project: {cat_id:1,goods_name:1, Goods_number:1, _id:0}}, {$group: {_id:{cat_id:"$cat _id", Color: "$color"}, total:{$sum: "$goods _number"}}}, {$skip:1}, {$limit:30}, {$out:"Result"}        ]        </pre>3. MapReduce Method*Grammatical Structure<pre>Db.collection.mapReduce (function() {Emit ( This. cat_id, This. Goods_number); }, //Map Method                function(key,value) {returnarray.sum (value); }, //Reduce Method{query:{goods_id:{$gt:30}}, out:"Mapreduceresultset"                }            ); </pre> * [More Information] (http://docs.mongodb.org/manual/core/map-reduce/)

MongoDB Aggregation Operations (group, aggregate, MapReduce operations)