对文档 entryStat 进行统计
按照 shareTpye 筛选后的数据
通过key 进行 mapreduce
类似 sql 的

select id ，count（1）
from entryStat
where shareType = #{shareType }
groupby id

代码如下

    public List<EntryStatMrResult> listEntryStat(int shareType){
        Query query = new Query(Criteria.where("shareType").is(shareType));
        MapReduceResults<EntryStatMrResult> mapReduceResults =  mongoTemplate.mapReduce(
                query,
                "entryStat",
                "classpath:map.js",
                "classpath:reduce.js",
                EntryStatMrResult.class);
        return Lists.newArrayList( mapReduceResults.iterator());
    }

文档的数据类型是

@Getter
@Setter
public class EntryStat implements Serializable {

    @Id
    public String id;

    public String userId;

    public String userName;

    public Integer shareType ;

    public Date createTime;

    public Date updateTime;
}

返回类型

@Data
public class EntryStatMrResult {

    private String  id;

    private Integer value;

}

map.js

function map() {
    emit(this.userId,1);
}

reduce.js

function reduce(key, values2) {
    var sum = 0;
    for (var i = 0; i < values2.length; i++)
        sum += values2[i];
    return sum;
}

mongo 依赖

        <!--mongodb依赖-->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-data-mongodb</artifactId>
        </dependency>
        <dependency>
            <groupId>org.mongodb</groupId>
            <artifactId>mongo-java-driver</artifactId>
        </dependency>

参考文档
https://docs.spring.io/spring-data/mongodb/docs/current/reference/html/
https://docs.mongodb.com/manual/tutorial/map-reduce-examples/