组合多个模糊连接

Question

使用R编程语言，我有以下两个表（在我的实际问题中，所有日期都以“因子”类型给我）：

table_1 = data.frame(id1 = c("123 A", "123BB", "12 5", "12--5"), id2 = c("11", "12", "14", "13"),
date_1 = c("2010-01-31","2010-01-31", "2015-01-31", "2018-01-31" ))

table_1$id1 = as.factor(table_1$id1)
table_1$id2 = as.factor(table_1$id2)
table_1$date_1 = as.factor(table_1$date_1)

table_2 = data.frame(id1 = c("0123", "1233", "125  .", "125_"), id2 = c("111", "112", "14", "113"),
date_2 = c("2009-01-31","2010-01-31", "2010-01-31", "2010-01-31" ),
date_3 = c("2011-01-31","2010-01-31", "2020-01-31", "2020-01-31" ))


table_2$id1 = as.factor(table_2$id1)
table_2$id2 = as.factor(table_2$id2)
table_2$date_2 = as.factor(table_2$date_2)
table_2$date_3 = as.factor(table_2$date_3)

如果条件 1 或条件 2 为真，我正在尝试执行“内部联接”：

Condition_1

if table_1$id "模糊相等" table_2$id AND
if table_1$date BETWEEN(table_2$date_2,table_2$date_3)

Condition_2

if table_1$id2 "模糊相等" table_2$id2

现在，我知道如何分两部分进行操作：

library(dplyr)
library(fuzzyjoin)

part_1 =  stringdist_inner_join(table_1, table_2, by = "id1", max_dist = 2) %>%
  filter(date_1 >= date_2, date_1 <= date_3) 

part_2 =  stringdist_inner_join(table_1, table_2, by = "id2", max_dist = 2) 

combine = rbind(part_1, part_2)

final = combine[!duplicated(combine[c(1,2,3,4,5,6,7)]),]

我的问题

是否有“更好”的方式运行将此连接在一起，而不是分成两个单独的部分？
看来“part_1”中的SQL查询是先对所有条记录进行模糊连接，然后只保留满足日期标准的相关记录，即 filter(date_1 >= date_2, date_1 <= date_3) 。这似乎是一种低效的做事方式 - 或者这是完成此任务的唯一可能方式，因为默认情况下模糊连接必须在所有行上运行以查看是否满足“id”条件，并且只有这样才能满足“日期”条件？

Answer 1

如果我们想在循环中执行此操作，请循环遍历变量部分，即 by

library(purrr)
library(fuzzyjoin)
library(dplyr)
final2 <- map_dfr(c("id1", "id2"),  ~
       stringdist_inner_join(table_1, table_2, by = .x, max_dist = 2)) %>%
       distinct %>%
       arrange(across(everything()))

-正在检查

> all.equal(final %>% 
         arrange(across(everything())), final2)
[1] TRUE

组合多个模糊连接

Combining Multiple Fuzzy Joins

sql

r

data-manipulation

dplyr