Question

如何通过计算多行获得结果表？

Name     Type     Value
------------------------------
Name1    Plus     5000
Name1    Minus    1000
Name2    Plus     3000
Name2    Minus    2000

所需结果：

Name     Value(Plus-Minus) 
------------------------------
Name1    4000
Name2    1000

Answer 1

使用条件聚合，并为每个名称记录组取所有“正”值的差减去所有“负”值。

SELECT
    Name,
    SUM(CASE WHEN Type = 'Plus' THEN [Value] ELSE 0 END) -
    SUM(CASE WHEN Type = 'Minus' THEN [Value] ELSE 0 END) AS diff
FROM yourTable
GROUP BY
    Name;

Answer 2

您可以使用条件聚合：

> suppressMessages(suppressWarnings(library(CVXR)))
> set.seed(10)
> n <- 10
> SAMPLES <- 100
> mu <- matrix(abs(rnorm(n)), nrow = n)
> Sigma <- matrix(rnorm(n^2), nrow = n, ncol = n)
> Sigma <- t(Sigma) %*% Sigma
> w <- Variable(n)
> ret <- t(mu) %*% w
> risk <- quad_form(w, Sigma)
> constraints <- list(w >= 0, sum(w) == 1,ret==mean(mu))
> prob <- Problem(Minimize(risk), constraints)
> result <- solve(prob,solver='MOSEK', verbose=TRUE)
Problem
  Name                   :                 
  Objective sense        : min             
  Type                   : CONIC (conic optimization problem)
  Constraints            : 24              
  Cones                  : 1               
  Scalar variables       : 23              
  Matrix variables       : 0               
  Integer variables      : 0               

Optimizer started.
Presolve started.
Linear dependency checker started.
Linear dependency checker terminated.
Eliminator - tries                  : 0                 time                   : 0.00            
Lin. dep.  - tries                  : 1                 time                   : 0.00            
Lin. dep.  - number                 : 0               
Presolve terminated. Time: 0.00    
Problem
  Name                   :                 
  Objective sense        : min             
  Type                   : CONIC (conic optimization problem)
  Constraints            : 24              
  Cones                  : 1               
  Scalar variables       : 23              
  Matrix variables       : 0               
  Integer variables      : 0               

Optimizer  - threads                : 8               
Optimizer  - solved problem         : the primal      
Optimizer  - Constraints            : 13
Optimizer  - Cones                  : 1
Optimizer  - Scalar variables       : 22                conic                  : 12              
Optimizer  - Semi-definite variables: 0                 scalarized             : 0               
Factor     - setup time             : 0.00              dense det. time        : 0.00            
Factor     - ML order time          : 0.00              GP order time          : 0.00            
Factor     - nonzeros before factor : 89                after factor           : 91              
Factor     - dense dim.             : 0                 flops                  : 2.54e+03        
ITE PFEAS    DFEAS    GFEAS    PRSTATUS   POBJ              DOBJ              MU       TIME  
0   1.0e+00  6.9e+00  1.0e+00  0.00e+00   2.756709152e+01   2.756709152e+01   1.0e+00  0.00  
1   2.7e-01  1.8e+00  2.2e-01  -6.02e-01  -9.936262607e+00  4.762263760e+00   2.7e-01  0.00  
2   9.9e-02  6.8e-01  4.3e-01  1.23e+00   9.201188225e-01   -6.807855573e-01  9.9e-02  0.00  
3   3.6e-02  2.5e-01  4.4e-01  1.97e+00   -1.264256365e-01  -5.225584219e-01  3.6e-02  0.00  
4   9.2e-03  6.3e-02  1.8e-01  2.33e+00   2.868592743e-01   2.542157558e-01   9.2e-03  0.00  
5   2.0e-03  1.4e-02  8.8e-02  1.17e+00   2.840102253e-01   2.769232377e-01   2.0e-03  0.00  
6   3.7e-04  2.5e-03  3.9e-02  1.04e+00   2.879204145e-01   2.866174921e-01   3.7e-04  0.00  
7   6.3e-05  4.3e-04  1.6e-02  1.02e+00   2.901039465e-01   2.898751147e-01   6.3e-05  0.00  
8   1.3e-05  8.8e-05  7.4e-03  1.00e+00   2.902381000e-01   2.901914751e-01   1.3e-05  0.00  
9   3.6e-06  2.5e-05  4.0e-03  1.00e+00   2.902501323e-01   2.902366424e-01   3.6e-06  0.00  
10  1.1e-06  7.4e-06  2.2e-03  1.00e+00   2.902666158e-01   2.902625442e-01   1.1e-06  0.00  
11  3.6e-07  2.5e-06  1.3e-03  1.00e+00   2.902689540e-01   2.902675850e-01   3.6e-07  0.00  
12  5.7e-08  3.9e-07  5.1e-04  1.00e+00   2.902716546e-01   2.902714343e-01   5.7e-08  0.00  
13  6.6e-09  4.6e-08  1.7e-04  1.00e+00   2.902720234e-01   2.902719974e-01   6.6e-09  0.00  
Optimizer terminated. Time: 0.00    


Interior-point solution summary
  Problem status  : PRIMAL_AND_DUAL_FEASIBLE
  Solution status : OPTIMAL
  Primal.  obj: 2.9027202344e-01    nrm: 1e+00    Viol.  con: 6e-09    var: 0e+00    cones: 0e+00  
  Dual.    obj: 2.9027199740e-01    nrm: 1e+01    Viol.  con: 0e+00    var: 8e-08    cones: 0e+00  
> result$value
[1] 0.290272
>

SQL：计算多行结果

2 个答案: