R data.table add new column with query for each row - r

Question

I have 2 R data.tables in R like so:
first_table
id | first | trunc | val1
=========================
1 | Bob | Smith | 10
2 | Sue | Goldm | 20
3 | Sue | Wollw | 30
4 | Bob | Bellb | 40
second_table
id | first | last | val2
==============================
1 | Bob | Smith | A
2 | Bob | Smith | B
3 | Sue | Goldman | A
4 | Sue | Goldman | B
5 | Sue | Wollworth | A
6 | Sue | Wollworth | B
7 | Bob | Bellbottom | A
8 | Bob | Bellbottom | B
As you can see, the last names in the first table are truncated. Also, the combination of first and last name is unique in the first table, but not in the second. I want to "join" on the combination of first name and last name under the incredibly naive assumptions that
first,last uniquely defines a person
that truncation of the last name does not introduce ambiguity.
The result should look like this:
id | first | trunc | last | val1
=======================================
1 | Bob | Smith | Smith | 10
2 | Sue | Goldm | Goldman | 20
3 | Sue | Wollw | Wollworth | 30
4 | Bob | Bellb | Bellbottom | 40
Basically, for each row in table_1, I need to find a row that back fills the last name.
For Each Row in first_table:
Find the first row in second_table with:
matching first_name & trunc is a substring of last
And then join on that row
Is there an easy vectorized way to accomplish this with data.table?

Answer 1

One approach is to join on first, then filter based on the substring-match
first_table[
unique(second_table[, .(first, last)])
, on = "first"
, nomatch = 0
][
substr(last, 1, nchar(trunc)) == trunc
]
# id first trunc val1 last
# 1: 1 Bob Smith 10 Smith
# 2: 2 Sue Goldm 20 Goldman
# 3: 3 Sue Wollw 30 Wollworth
# 4: 4 Bob Bellb 40 Bellbottom
Or, do the truncation on the second_table to match the first, then join on both columns
first_table[
unique(second_table[, .(first, last, trunc = substr(last, 1, 5))])
, on = c("first", "trunc")
, nomatch = 0
]
## yields the same answer