提取構面計數和數據時的mongodb性能問題

Question

我是使用MongoDB的新手。
我收集了以下文件：

{
    "_id" : ObjectId("58204f60536d1a27736d512b"),
    "last_name" : "Vinaykumar",
    "university_name" : "Osmania University",
    "job_483" : 1,
    "xiith_mark" : 0,
    "id" : "3305775",
    "first_name" : "V",
    "course_name" : "Diploma",
    "institute_name_string" : "Govt.Polytechnic,Kothagudem",
    "profile_percentage" : 60,
    "xiith_mark_type" : "Percentage",
    "xth_mark_type" : "Percentage",
    "date_of_birth" : "11-March-1995",
    "xth_mark" : 0,
    "last_login" : 1379565790,
    "percentage" : 76,
    "job_details" : [
    {
        "status" : NumberLong(0),
        "applied_date" : NumberLong(1476703354),
        "contact_viwed_status" : 0,
        "label_name" : [ ],
        "questionnaire_status" : 0,
        "batch_id" : null,
        "owner_type" : "searches",
        "call_letter" : null,
        "owner_id" : NumberLong(465)
    },
    {
        "status" : NumberLong(0),
        "applied_date" : NumberLong(1477051963),
        "contact_viwed_status" : 0,
        "label_name" : [ ],
        "questionnaire_status" : 0,
        "batch_id" : null,
        "owner_type" : "searches",
        "call_letter" : null,
        "owner_id" : NumberLong(482)
    },
    {
        "status" : NumberLong(0),
        "applied_date" : NumberLong(1477052973),
        "contact_viwed_status" : 0,
        "label_name" : [ ],
        "questionnaire_status" : 0,
        "batch_id" : null,
        "owner_type" : "searches",
        "call_letter" : null,
        "owner_id" : NumberLong(483)
   }
   ],
   "branch_name" : "Electrical & Electronics",
   "candidate_state_name" : "Andhra Pradesh",
   "candidate_city_name_string" : "Andhra Pradesh-other",
   "10" : 10,
   "12" : 12,
   "gender" : "Male",
   "fw_id" : "FW15651132",
   "cgpa" : 0,
   "picture_path" : "",
   "hq_passout_year" : 2013
}

我需要從數據庫中獲取包含facet count的數據。
需要以下方面的構面計數

• job_details.status，job_details.label_name，job_details.contact_viwed_status，候選人城市名稱字符串，
  course_name，hq_passout_year，branch_name，候選人_sublocation_name_string，技能

並且總匹配數和數據有限制

我對每個方面進行了單獨的查詢，對總數進行了一個查詢，對數據進行了一個查詢
總計9 + 1 + 1 = 11個查詢

查詢的是

job_details.status和job_details.label_name和job_details.contact_viwed_status的方面查詢都像這樣

db.Response.aggregate([
    {"$match":{"$and":[{"job_details.owner_id" : 428},    
    {"job_details.owner_type" : 'searches'}]}}, 
    {"$unwind": "$job_details" }, 
    {"$group": {"_id":"$job_details.status","count": {"$sum": 1 }} }
    ])

其他6個方面的查詢是這樣的

db.Response.aggregate([ {"$and":[{"job_details.owner_id" : 428},{"job_details.owner_type" : 'searches'}]},
                {"$group": {"_id":"$candidate_city_name_string","count": {"$sum": 1 }}}] )  

查詢收集數據

 db.Response.aggregate([
              {"$and":[{"job_details.owner_id" : 428}{"job_details.owner_type" : 'searches'}]},
              {"$limit":25},``
              { "$skip":0} ,
              {"$unwind":"$job_details"}])

查詢收集總數

db.Response.find({"$and":[{"job_details.owner_id" : 428},{"job_details.owner_type" : 'searches'}]}).count()

總共3 + 9 + 1 + 1 = 11條查詢因此性能非常低。 可以使這11個查詢變為單個查詢，或者如何提高性能。
請幫忙。

Answer 1

db.Response.aggregate([
{"$match":{"$and":[{"job_details.owner_id" : 482},{"job_details.owner_type" : 'searches'}]}}, 
{$facet: {
    "status": [ 
                    {"$unwind": "$job_details" }, 
                    {"$group": {"_id":"$job_details.status","count": {"$sum": 1 }} }
                 ],
    "label_name": [ 
                    {"$unwind": "$job_details" }, 
                    {"$unwind": "$job_details.label_name" }, 
                    {"$group": {"_id":"$job_details.label_name","count": {"$sum": 1 }} }
                  ] ,
    "contact_viwed_status": [ 
                    {"$unwind": "$job_details" }, 
                    {"$group": {"_id":"$job_details.contact_viwed_status","count": {"$sum": 1 }} }
                  ],
    "questionnaire_status": [ 
                    {"$unwind": "$job_details" }, 
                    {"$group": {"_id":"$job_details.questionnaire_status","count": {"$sum": 1 }} }
                  ],
    "candidate_city_name_string": [ 
                        {"$group": {"_id":"$candidate_city_name_string","count": {"$sum": 1 }}}
                      ],
    "course_name": [ 
                        {"$group": {"_id":"$course_name","count": {"$sum": 1 }}}
                      ],
    "hq_passout_year": [ 
                        {"$group": {"_id":"$hq_passout_year","count": {"$sum": 1 }}}
                      ],
    "branch_name": [ 
                        {"$group": {"_id":"$branch_name","count": {"$sum": 1 }}}
                      ],
    "candidate_sublocation_name_string": [ 
                        {"$group": {"_id":"$candidate_sublocation_name_string","count": {"$sum": 1 }}}
                      ],
    "skill": [ 
                        {"$group": {"_id":"$skill","count": {"$sum": 1 }}}
                      ],
    "doc": [
                    {"$limit":25},
                    {"$skip":0},
                    {"$unwind":"$job_details"}],
    "total_count":[
                    {"$group":{"_id": "null", "count":{"$sum":1}}}]
        }}])