Question

我正在使用带有Spring Data的MongoDB来创建我们的原型应用程序。保存操作非常快，但是为了列出结果，性能非常差，即使它们只有3到4个记录持续存在。另一个令人惊讶的部分是每次连续列表操作都会导致性能下降。

在这里给出一个想法是单个json，它不是世界上最大的。

    {
    "enquiryId": "574feac25215eae3e2e1434b",
    "enquiryName": "Mineral Shipment",
    "dateOfEnquiry": null,
    "requiredFrom": 1465324200000,
    "requiredTo": 1483036200000,
    "source": {
      "locationId": null,
      "area": {
        "pincode": null,
        "area": null,
        "city": {
          "cityId": null,
          "cityName": "Panjim",
          "state": {
            "stateId": null,
            "stateName": " Goa 403001",
            "country": {
              "countryId": null,
              "countryName": " India"
            }
          }
        }
      }
    },
    "destination": {
      "locationId": null,
      "area": {
        "pincode": null,
        "area": null,
        "city": {
          "cityId": null,
          "cityName": "Ludhiana",
          "state": {
            "stateId": null,
            "stateName": " Punjab 141001",
            "country": {
              "countryId": null,
              "countryName": " India"
            }
          }
        }
      }
    },
    "shipment": {
      "shipmentId": null,
      "enquiryId": null,
      "shipmentName": "Mineral Shipment",
      "valueOfGoods": null,
      "categories": [
        {
          "categoryId": null,
          "categoryName": "Hazardous,Flammable",
          "subCategories": null,
          "shipmentId": null
        }
      ],
      "modes": [
        {
          "modeId": null,
          "modeName": "WATER",
          "modeDescription": null,
          "shipmentId": null
        }
      ],
      "items": [
        {
          "itemId": null,
          "itemName": "Coal",
          "shape": null,
          "form": null,
          "dimension": null,
          "weight": null,
          "quantity": null,
          "shipmentId": null
        },
        {
          "itemId": null,
          "itemName": "Nickel",
          "shape": null,
          "form": null,
          "dimension": null,
          "weight": null,
          "quantity": null,
          "shipmentId": null
        }
      ]
    },
    "transportEnquiries": [
      {
        "transportEnquiryId": null,
        "transport": {
          "transportId": null,
          "name": "Flat Bed",
          "mode": {
            "modeId": null,
            "modeName": "WATER",
            "modeDescription": "The two world wars gave a great impetus to the development of air transport in almost all the countries of the world",
            "shipmentId": null
          },
          "type": {
            "typeId": null,
            "name": "LWH",
            "modeId": null,
            "illustrationURL": null
          },
          "desc": "Description of Flat Bed"
        }
      }
    ],
    "storageEnquiries": [],
    "packagingEnquiries": null,
    "insuranceEnquiries": null,
    "documentationEnquiry": null,
    "trackingToolRequired": null,
    "customerSupportRequired": null,
    "insuranceRequired": null,
    "storageRequired": null,
    "documentationRequired": null,
    "published": false,
    "userId": null
  }

这是Spring Service

    public class EnquiryManagementService implements IEnquiryManagementService{

    @Autowired
    private EnquiryRepository enquiryRepository;

    public Enquiry createEnquiry(Enquiry enquiry) {
        Enquiry enquiryObj = (Enquiry)enquiry;
        Enquiry e = enquiryRepository.save(enquiryObj);
        return e;
    }

    @Override
    public List<Enquiry> listEnquiry(int start) {
         long startTime = System.currentTimeMillis();
         Page<Enquiry> enquiries = enquiryRepository.findAll(new PageRequest(start,10));
         long endTime = System.currentTimeMillis();
         System.out.println("Time Taken = "+(endTime-startTime));
         return enquiries.getContent();
    }



}

以下是在不添加任何记录的情况下连续4次处理findAll（）所花费的时间的结果。系统中只有4条记录，您可以看到所用时间分别为10.7秒，25.7秒，41.9秒和58.5秒。每个请求都需要一辈子的时间才能完成。

拍摄时间= 10768
拍摄时间= 25785
拍摄时间= 41921
拍摄时间= 58530

以下是我的系统的配置 - 英特尔酷睿i3 2330M @ 2.2 GHz - 2 GB RAM - 64位Windows 7 - 我系统本地安装的MongoDB版本：3.2 - 执行此查询时CPU利用率为50％，内存为80％

理想情况下，此操作必须在不到半秒或最多一秒钟内完成。任何形式的帮助都会很棒。

MongoDB和Spring Data性能问题

0 个答案: