Mongodb spring的整合开发 权限认证 mongotemplate的group mapReduce开发

　　【开发过程的随笔总结，欢迎您的点评，可以做到更加严谨】

　　前段时间因为写一个业务，对mysql的插入量非常大，在idea开发环境，使得idea一直爆出outofmemry提示，并导致old 区一直涨。使用Mongodb 作为存储后，不仅插入速度大大提升，idea会卡死的顽疾也解决了。　

　　Mongodb 能够非常简单的整合进项目

　　1 添加相应database的权限用户

　　2 mongoFactory构造mogotemplate链接对象

　　3 进行mongo的增删改查操作

• Mongo 的用户管理（授权操作需要有用户）

　　请参考下面mongo的用户管理　

　　mongo用户管理　

　　http://www.cnblogs.com/billerbird/p/5648428.html

　　下面是我的整合过程

• Mongo 与Spring的集成 配置文件bean.xml

<!-- mongodb -->
<bean id="mongodb" class="org.springframework.data.mongodb.core.MongoFactoryBean">
<property name="host" value="${mongodb.host}" />
<property name="port" value="${mongodb.port}" />
</bean>
<bean id="credentials" class="org.springframework.data.authentication.UserCredentials">
<constructor-arg name="username" value="${mongodb.username}"/>
<constructor-arg name="password" value="${mongodb.password}"/>
</bean>
<bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
<constructor-arg name="mongo" ref="mongodb" />
<constructor-arg name="databaseName" value="${mongodb.databaseName}" />
<constructor-arg name="userCredentials" ref="credentials" />
</bean>

• mongotemplate的增删该查过程

• mongotemplate 增

@Autowired
private MongoTemplate mongoTemplate;

public void saveBatch(List<APIRequest> apiRequests) {
        mongoTemplate.insert(apiRequests, APIConstant.API_REQUEST_COLLECTION);
    }

 

• mongotemplate  查

@Autowired
private MongoTemplate mongoTemplate;

    public List<APIRequest> getPricingRequest(String startDate, String endDate, String partnerId) {
        Date start = DateUtil.parse(startDate,"yyyy-MM-dd");
        Date end = DateUtil.parse(endDate,"yyyy-MM-dd");
        Query query = query(where("partnerId").is(partnerId))
                .addCriteria(where("requestType").is("precisePricing"))
                .addCriteria(where("requestDate").gt(start).lte(end));
        List<APIRequest> apiRequests = mongoTemplate.find(query, APIRequest.class, APIConstant.API_REQUEST_COLLECTION);
        System.out.println("MongoDB的数据" + apiRequests.size());
        return apiRequests;
    }

 

• mongotemplate  分页

@Autowired
private MongoTemplate mongoTemplate;

    /**分页查询 shopping数据**/
    public List<APIRequest> getAllAPIRequest(String startDate, String endDate, String partnerId, Integer skip, Integer limit) {
        Date start = DateUtil.parse(startDate,"yyyy-MM-dd");
        Date end = DateUtil.parse(endDate,"yyyy-MM-dd");
        Query query = query(where("partnerId").is(partnerId))
                .addCriteria(where("requestType").is("shopping"))
                .addCriteria(where("requestDate").gt(start).lte(end)).skip(skip).limit(limit);
        List<APIRequest> apiRequests = mongoTemplate.find(query, APIRequest.class, APIConstant.API_REQUEST_COLLECTION);
        System.out.println("MongoDB的数据" + apiRequests.size());
        return apiRequests;
    }

• mongotemplate  group

@Autowired
private MongoTemplate mongoTemplate;

    /**group 查询不能超过20000**/
    public List<APIRequest> getAllAPIRequestByGroup(String startDate, String endDate, String partnerId) {
        Date start = DateUtil.parse(startDate,"yyyy-MM-dd");
        Date end = DateUtil.parse(endDate,"yyyy-MM-dd");
        String keys = "origin;destination;journeyType";
        GroupBy groupBy = GroupBy.key(keys.split(";")).initialDocument("{requestCount:0}").reduceFunction("function(curr, result){result.requestCount+=curr.requestCount;}");

        Criteria criteria = where("partnerId").is(partnerId).and("requestType").is("shopping").and("requestDate").gt(start).lte(end);

        GroupByResults<APIRequest> rst = mongoTemplate.group(criteria,APIConstant.API_REQUEST_COLLECTION,groupBy, APIRequest.class);

        System.out.println("have result");

        return null;
    }

 

• mongotemplate  mapReduce

@Autowired
private MongoTemplate mongoTemplate;

    /**map reduce**/
    public List<APIRequest> getShoppingByMapReduce(String startDate, String endDate, String partnerId) {
        Date start = DateUtil.parse(startDate,"yyyy-MM-dd");
        Date end = DateUtil.parse(endDate,"yyyy-MM-dd");
        String keys = "origin;destination;journeyType";
        GroupBy groupBy = GroupBy.key(keys.split(";")).initialDocument("{requestCount:0}").reduceFunction("function(curr, result){result.requestCount+=curr.requestCount;}");

        String mapFuntion = "function() { 
" +
                "emit(
" +
                "{"origin":this.origin,"destination":this.destination,"journeyType":this.journeyType},
" +
                " this.requestCount); 
" +
                "}";
        String reductFunction = "function(key, values) { 
" +
                "   return Array.sum(values);
" +
                "}";
        Criteria criteria = where("partnerId").is(partnerId).and("requestType").is("shopping").and("requestDate").gt(start).lte(end);
        Query query = new Query(criteria);
        MapReduceOptions mrO=new MapReduceOptions();
        mrO.outputCollection("map_reduce_result");
        MapReduceResults<APIRequest> mapReduce = mongoTemplate.mapReduce(query,APIConstant.API_REQUEST_COLLECTION,mapFuntion,reductFunction,mrO,APIRequest.class);

        List<DBObject>  person_results = mongoTemplate.execute("map_reduce_result",new CollectionCallback<List<DBObject> >() {
            public List<DBObject> doInCollection(DBCollection collection)
                    throws MongoException, DataAccessException {
                DBCursor dbCursor=collection.find();
                return dbCursor.toArray();
            }
        });

        List<APIRequest> apiRequests = new ArrayList<>();
        for (DBObject dbObject : person_results) {
            APIRequest apiRequest = new APIRequest();
            apiRequest.setRequestCount(((Double)dbObject.get("value")).intValue());
            apiRequest.setOrigin((String) ((DBObject)dbObject.get("_id")).get("origin"));
            apiRequest.setDestination((String) ((DBObject)dbObject.get("_id")).get("destination"));
            apiRequest.setJourneyType((String) ((DBObject)dbObject.get("_id")).get("journeyType"));

            apiRequests.add(apiRequest);
        }
        System.out.println("map reduce的结果："+person_results.size() +"  转换后的结果："+apiRequests.size());

        return apiRequests;
    }

 

• mongotemplate  aggregate

aggregate 欢迎您贴代码

结束