具有多个条件的内部联接r数据表 [英] inner join with multiple conditions r data table

问题描述

我正在尝试使用具有多个相当动态条件的数据表进行内部联接。我被语法绊倒了。首先，我创建两个对象，我想使用它们进行内部联接。 x 和 x2 。

I am trying to do an inner join using data table that has multiple, fairly dynamic conditions. I am getting tripped up on the syntax. First, I create two objects, x and x2 that I want to do an inner join with.

set.seed(1)
#generate data
x = data.table(CJ(t=1:10, d=1:3,p1s=seq(1,3,by=0.1),p1sLAST=seq(1,3,by=0.1)))
x[d==1,p1sLAST:=3]
x=x[p1s<=p1sLAST]
x2 = data.table(CJ(tprime=1:10, p1sLASTprm=seq(1,3,by=0.1)))

对象：

> x
    t d p1s p1sLAST
1:  1 1 1.0     3.0
2:  1 1 1.0     3.0
3:  1 1 1.0     3.0
4:  1 1 1.0     3.0
5:  1 1 1.0     3.0
---                 
9026: 10 3 2.8     2.9
9027: 10 3 2.8     3.0
9028: 10 3 2.9     2.9
9029: 10 3 2.9     3.0
9030: 10 3 3.0     3.0


> x2
    tprime p1sLASTprm
1:      1        1.0
2:      1        1.1
3:      1        1.2
4:      1        1.3
5:      1        1.4
---                  
206:     10        2.6
207:     10        2.7
208:     10        2.8
209:     10        2.9
210:     10        3.0

现在，我想在单个内部联接中完成最后三个步骤。

Now, I want to do these last three steps in a single inner join.

joined = x[,x2[],by=names(x)]
joined=joined[p1sLASTprm==p1s & d!=3 | d==3 & p1sLASTprm==3]
joined=joined[tprime==t+1]

结果在最终输出中：

> joined
       t  d  p1s   p1sLAST  tprime    p1sLASTprm
    1: 1 1    1.0     3.0      2        1.0
    2: 1 1    1.1     3.0      2        1.1
    3: 1 1    1.2     3.0      2        1.2
    4: 1 1    1.3     3.0      2        1.3
    5: 1 1    1.4     3.0      2        1.4
    ---                                  
    4343: 9 3 2.8     2.9     10        3.0
    4344: 9 3 2.8     3.0     10        3.0
    4345: 9 3 2.9     2.9     10        3.0
    4346: 9 3 2.9     3.0     10        3.0
    4347: 9 3 3.0     3.0     10        3.0

推荐答案

我不认为单个内部联接可以完成这3个步骤，因为存在 | ，并且很可能需要结果的并集。

I do not think a single inner join can accomplish those 3 steps since there is a | and most likely a union of results will be required.

一种更有效利用内存的方法可能是：

A more memory efficient approach could be:

ux <- unique(x)[, upt := t+1]
rbindlist(list(
    ux[d!=3][x2,
        c(mget(names(ux)), mget(names(x2))),
        on=c("p1s"="p1sLASTprm", "upt"="tprime"),
        nomatch=0L],
    ux[d==3][x2[p1sLASTprm==3],
        c(mget(names(ux)), mget(names(x2))),
        on=c("upt"="tprime"),
        nomatch=0L]
))

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