c# - 使用 Redis 实现排序、搜索和分页以获得最佳性能的最佳方式

问题描述

我有大约 1,00,000 个员工的大数据。我已将此数据存储到一个名为“employess”的 Redis 密钥中。现在有一个屏幕，我想在某些字段上执行搜索并对每一列进行排序以及分页。

因此，为此我创建了以下可以正常工作的代码。但平均需要大约 1.2 秒到 2 秒的时间。

我想将它减少到 200 毫秒（要求）

有人可以指导我如何实现该性能或我在以下代码中做错了什么。

我正在使用 C# 代码和 ServiceStack.Redis 客户端。如果需要，我可以自由使用任何其他 Redis 客户端。

public class Employee
    {
        public int EmployeeId { get; set; }
        public string LastName { get; set; }
        public string FirstName { get; set; }
        public DateTime DOB { get; set; }
        public char Gender { get; set; }
        public string Street { get; set; }
        public string City { get; set; }
        public string State { get; set; }
        public string Zip { get; set; }
        public string Department { get; set; }
        public string Occupation { get; set; }
        public decimal Salary { get; set; }
    }

// 处理排序、搜索、分页和从 Redis 获取数据的方法。

  private GeneralResponse<IEnumerable<Employee>> GetEmp(SearchParam filter, int initialPage, int pageSize, out int totalRecords, out int recordFilterd,
           int sortColumn, string sortDirection)
        {
            var response = new GeneralResponse<IEnumerable<Employee>>();
            totalRecords = 0;
            recordFilterd = 0;

            try
            {
                var data = Enumerable.Empty<Employee>().AsQueryable();
                try
                {
                    using (var redisClient = new RedisClient(Common.redisUrl, Common.redisPort))
                    {


                        var rdata = redisClient.Get<IEnumerable<Employee>>("employess");
                        data = rdata.AsQueryable();
                        ViewBag.source = "redis";
                    }
                }
                catch (Exception e)
                {
                    data = Common.EmployeesList.AsQueryable();
                    ViewBag.source = "Database";
                }


                totalRecords = data.Count();
                //filter 
                if (!string.IsNullOrWhiteSpace(filter.FirstName))
                {
                    data = data.Where(x =>
                        x.FirstName.ToLower().Contains(filter.FirstName.Trim().ToLower())
                    );

                }
                if (!string.IsNullOrWhiteSpace(filter.LastName))
                {
                    data = data.Where(x =>
                        x.LastName.ToLower().Contains(filter.LastName.Trim().ToLower())
                    );
                }
                if (!string.IsNullOrWhiteSpace(filter.Department))
                {
                    data = data.Where(x =>
                        x.Department.ToLower() == filter.Department.Trim().ToLower()
                    );
                }
                if (filter.FromDob != null && filter.FromDob != default(DateTime))
                {
                    data = data.Where(x => x.DOB >= filter.FromDob);
                }
                if (filter.ToDob != null && filter.ToDob != default(DateTime))
                {
                    filter.ToDob = filter.ToDob.AddHours(23).AddMinutes(59);
                    data = data.Where(x => x.DOB <= filter.ToDob);

                }
                recordFilterd = data.Count();

                //sort 
                var ascending = sortDirection == "asc";
                switch (sortColumn)
                {
                    case 0:
                        data = data.OrderBy(p => p.EmployeeId, ascending);
                        break;
                    case 1:
                        data = data.OrderBy(p => p.LastName, ascending);
                        break;
                    case 2:
                        data = data.OrderBy(p => p.FirstName, ascending);
                        break;
                    case 3:
                        data = data.OrderBy(p => p.DOB, ascending);
                        break;
                    case 4:
                        data = data.OrderBy(p => p.Gender, ascending);
                        break;
                    case 5:
                        data = data.OrderBy(p => p.Street, ascending);
                        break;
                    case 6:
                        data = data.OrderBy(p => p.City, ascending);
                        break;
                    case 7:
                        data = data.OrderBy(p => p.State, ascending);
                        break;
                    case 8:
                        data = data.OrderBy(p => p.Zip, ascending);
                        break;
                    case 9:
                        data = data.OrderBy(p => p.Department, ascending);
                        break;
                    case 10:
                        data = data.OrderBy(p => p.Occupation, ascending);
                        break;
                    case 11:
                        data = data.OrderBy(p => p.Occupation, ascending);
                        break;
                    default:
                        data = data.OrderBy(p => p.Salary, ascending);
                        break;
                }

                data = data
                    .Skip(initialPage * pageSize)
                    .Take(pageSize);

                var result = data.ToList();
                response.Data = result;

            }
            catch (Exception e)
            {
                response.Error = true;
                response.Exception = e;
            }
            return response;
        }

任何帮助或指导将不胜感激。以下是我想要达到速度的参考屏幕。

标签： c#redisservicestack.redis

c# - 使用 Redis 实现排序、搜索和分页以获得最佳性能的最佳方式

问题描述

解决方案

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