Fuzzy Joins through sqlQuery() commands

Using the R programming language, I have the following query I would like to run:

library(RODBC)
library(sqldf)

con = odbcConnect("some name", uid = "some id", pwd = "abc")

sample_query = sqlQuery(con, "select distinct * from table_a a 
inner join table_b b
on (a.date_1 between b.date_2 and b.date_3 and a.id1 = b.id1) or a.id2 = b.id2)

view(sample_query)

My Question: Is it possible to "pass" non-SQL statements through sqlQuery(), such as functions from the "dplyr" and "fuzzyjoin" libraries in R? For example:

library(fuzzyjoin)
library(dplyr)

sample_query = sqlQuery( stringdist_inner_join(table_1, table_2, by = "id2", max_dist = 2) %>%
  filter(date_1 >= date_2, date_1 <= date_3) )

view(sample_query)

Or will this just result in the above query being run "locally" (i.e. take much longer)? E.g.:

sample_query =  stringdist_inner_join(table_1, table_2, by = "id2", max_dist = 2) %>%
  filter(date_1 >= date_2, date_1 <= date_3) 

Thanks!

Note: Reproducible Example

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)
  
    
    

Not exactly, everything executed on the sql server side has to be sql (unless you have R functions defined in the sql server itself), you can use the package dbplyr which translates several dplyr commands into sql under the hood but not all commands have a translation.

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