Mongodb新增的聚合方法及其Java客户端

Aggregation Framework Reference¶

http://cn.docs.mongodb.org/manual/reference/aggregation/#aggregation-framework-reference

Java Driver and Aggregation Framework¶

http://docs.mongodb.org/ecosystem/tutorial/use-aggregation-framework-with-java-driver/

Let’s use a simple example to demonstrate how the aggregationhelper works. Suppose I am using MongoDB to store my employee’stravel expenses. I’ve created a collectionnamed expenses,which store individual expenses by employee and by department.Here’s a sample document:

{  "_id" : ObjectId("503d5024ff9038cdbfcc9da4"),
   

"employee" : 61,
   

"department" : "Sales",
   

"amount" : 77,
   

"type" : "airfare"
}

I am auditing three departments: Sales, Engineering and HumanResources. I want to calculate each department’s average spend onairfare. I’d like to use the Aggregation Framework for the audit,so I think of the operation in terms of a pipeline:

1. Operation: Match documentswhere type = "airfare";then pipe into
2. Operation: Pass onlythe department andthe amount fieldsthrough the pipeline; then pipe into
3. Operation: Average theexpense amount,grouped by department.

I will use the aggregation operators $match, $project and $group toperform each operation. Individual aggregation operations can beexpressed as JSON objects, so I can think of my pipeline in JSONas:

1. First operation:

   $match: { type: "airfare"}
   

2. Piped into:

   $project: { department: 1, amount: 1 }
   

3. Piped into:

   $group: { _id: "$department",
             average: { $avg: "$amount" } }
   

   也就是说，运行以下命令：
   

   db.expenses.aggregate({
   
   $match:{type: "airfare"}$project:{_id:0,department: 1, amount: 1}
   $group:{_id: "$department", average: { $avg: "$amount" }}
   })
   

   Java 实现：
   

   // create our pipeline operations, first with the $match DBObjectmatch=newBasicDBObject("$match",newBasicDBObject("type","airfare")); 
   

    
   // build the $projection operation DBObjectfields=newBasicDBObject("department",1);fields.put("amount",1);fields.put("_id",0);DBObjectproject=newBasicDBObject("$project",fields); 
   

   // Now the $group operationDBObjectgroupFields=newBasicDBObject("_id","$department");groupFields.put("average",newBasicDBObject("$avg","$amount"));DBObjectgroup=newBasicDBObject("$group",groupFields); 
   

   // run aggregationAggregationOutputoutput=collection.aggregate(match,project,group);
   

   
   
   Aggregations are executed as database commands in MongoDB. These commands embed the results of the aggregation task in an object that also contains additional information about how the command was executed. The return value of aggregate() is an instance of the AggregationOutput class, which provides assessors to this information.
   
   
   
   

   public Iterable<DBObject> results()
   
   
   public CommandResult getCommandResult
   
   
   public DBObject getCommand()
   

   Let’s take a look at the results of my audit:
   

   System.out.println(output.getCommandResult());
   

   {
      "serverUsed" : "/127.0.0.1:27017" ,
   
    "result" : 
   
   [
         {"_id" : "Human Resources","average": 74.91735537190083},
   
    {"_id" : "Sales" , "average" : 72.30275229357798},
   
    {"_id" : "Engineering" , "average" : 74.1}
      ],
   
    "ok" : 1.0
   }