Join two csv files if value is between interval in file 2 - bash

Question

I have two csv files that I need to join, F1 has milions of lines, F2 (file 1) has thousands of lines. I need to join these files, if the position in file F1 (F1.pos) is between F2.start and F2.end. Is there any way, how to do this in bash? Because I have a code in Python pandas to sqllite3 and I am looking for something quicker.
Table F1 looks like:
| name | pos |
|------ |------ |
| a | 1020 |
| b | 1200 |
| c | 1800 |
Table F2 looks like:
| interval_name | start | end |
|--------------- |------- |------ |
| int1 | 990 | 1090 |
| int2 | 1100 | 1150 |
| int3 | 500 | 2000 |
Result should look like:
| name | pos | interval_name | start | end |
|------ |------ |--------------- |------- |------ |
| a | 1020 | int1 | 990 | 1090 |
| a | 1020 | int3 | 500 | 2000 |
| b | 1200 | int1 | 990 | 1090 |
| b | 1200 | int3 | 500 | 2000 |
| c | 1800 | int3 | 500 | 2000 |

Answer 1

DISCLAIMER: Use dedicated/local tools if available, this is hacking:
There is an apparent error in your desired output: name b should not match int1.
$ tail -n+1 *.csv
==> f1.csv <==
name,pos
a,1020
b,1200
c,1800
==> f2.csv <==
interval_name,start,end
int1,990,1090
int2,1100,1150
int3,500,2000
$ awk -F, -vOFS=, '
BEGIN {
print "name,pos,interval_name,start,end"
PROCINFO["sorted_in"]="#ind_num_asc"
}
FNR==1 {next}
NR==FNR {Int[$1] = $2 "," $3; next}
{
for(i in Int) {
split(Int[i], I)
if($2 >= I[1] && $2 <= I[2]) print $0, i, Int[i]
}
}
' f2.csv f1.csv
Outputs:
name,pos,interval_name,start,end
a,1020,int1,990,1090
a,1020,int3,500,2000
b,1200,int3,500,2000
c,1800,int3,500,2000
This is not particularly efficient in any way; the only sorting used is to ensure that the Int array is parsed in the correct order, which changes if your sample data is not indicative of the actual schema. I would be very interested to know how my solution performs vs pandas.

Answer 2

Here's one in awk. It hashes the smaller file records to arrays and for each of the bigger file records it iterates thru the hashes so it is slow:
$ awk '
NR==FNR { # hash f2 records
start[NR]=$4
end[NR]=$6
data[NR]=substr($0,2)
next
}
FNR<=2 { # mind the front matter
print $0 data[FNR]
}
{ # check if in range and output
for(i in start)
if($4>start[i] && $4<end[i])
print $0 data[i]
}' f2 f1
Output:
| name | pos | interval_name | start | end |
|------ |------ |--------------- |------- |------ |
| a | 1020 | int1 | 990 | 1090 |
| a | 1020 | int3 | 500 | 2000 |
| b | 1200 | int3 | 500 | 2000 |
| c | 1800 | int3 | 500 | 2000 |

Answer 3

I doubt that a bash script would be faster than a python script. Just don't import the files into a database – write a custom join function instead!
The best way to join depends on your input data. If nearly all F1.pos are inside of nearly all intervals then a naive approach would be the fastest. The naive approach in bash would look like this:
#! /bin/bash
join --header -t, -j99 F1 F2 |
sed 's/^,//' |
awk -F, 'NR>1 && $2 >= $4 && $2 <= $5'
# NR>1 is only there to skip the column headers
However, this will be very slow if there are only a few intersections, for instance, when the average F1.pos only is in 5 intervals. In this case the following approach will be way faster. Implement it in a programing language of your choice – bash is not appropriate for this:
Sort F1 by pos in ascending order.
Sort F2 by start and then by end in ascending order.
For each sorted file, keep a pointer to a line, starting at the first line.
Repeat until F1's pointer reaches the end:
For the current F1.pos advance F2's pointer until F1.pos ≥ F2.start.
Lock F2's pointer, but continue to read lines until F1.pos ≤ F2.end. Print the read lines in the output format name,pos,interval_name,start,end.
Advance F1's pointer by one line.
Only sorting the files could be actually faster in bash. Here is a script to sort both files.
#! /bin/bash
sort -t, -n -k2 F1-without-headers > F1-sorted
sort -t, -n -k2,3 F2-without-headers > F2-sorted
Consider using LC_ALL=C, -S N% and --parallel N to speed up the sorting process.