while loops in parallel with input from splited file - bash

Question

I am stuck on that. So I have this while-read loop within my code that is taking so long and I would like to run it in many processors. But, I'd like to split the input file and run 14 loops (because I have 14 threads), one for each splited file, in parallel. Thing is that I don't know how to tell the while loop which file to get and work with.
For example, in a regular while-read loop I would code:
while read line
do
<some code>
done < input file or variable...
But in this case I would like to split the above input file in 14 files and run 14 while loops in parallel, one for each splited file.
I tried :
split -n 14 input_file
find . -name "xa*" | \
parallel -j 14 | \
while read line
do
<lot of stuff>
done
also tried
split -n 14 input_file
function loop {
while read line
do
<lot of stuff>
done
}
export -f loop
parallel -j 14 ::: loop
But neither I was able to tell which file would be the input to the loop so parallel would understand "take each of those xa* files and place into individual loops in parallel"
An example of the input file (a list of strings)
AEYS01000010.10484.12283
CVJT01000011.50.2173
KF625180.1.1799
KT949922.1.1791
LOBZ01000025.54942.57580
EDIT
This is the code.
The output is a table (741100 lines) with some statistics regarding DNA sequences alignments already made.
The loop takes an input_file (no broken lines, varies from 500 to ~45000 lines, 800Kb) with DNA sequence acessions, reads it line-by-line and look for each correspondent full taxonomy for those acessions in a databank (~45000 lines). Then, it does a few sums/divisions. Output is a .tsv and looks like this (an example for sequence "KF625180.1.1799"):
Rate of taxonomies for this sequence in %: KF625180.1.1799 D_6__Bacillus_atrophaeus
Taxonomy %aligned number_ocurrences_in_the_alignment num_ocurrences_in_databank %alingment/databank
D_6__Bacillus_atrophaeus 50% 1 20 5%
D_6__Bacillus_amyloliquefaciens 50% 1 154 0.649351%
$ head input file
AEYS01000010.10484.12283
CVJT01000011.50.217
KF625180.1.1799
KT949922.1.1791
LOBZ01000025.54942.57580
Two additional files are also used inside the loop. They are not the loop input.
1) a file called alnout_file that only serves for finding how many hits (or alignments) a given sequence had against the databank. It was also previously made outside this loop. It can vary in the number of lines from hundreads to thousands. Only columns 1 and 2 matters here. Column1 is the name of the sequence and col2 is the name of all sequences it matched in the databnk. It looks like that:
$ head alnout_file
KF625180.1.1799 KF625180.1.1799 100.0 431 0 0 1 431 1 431 -1 0
KF625180.1.1799 KP143082.1.1457 99.3 431 1 2 1 431 1 429 -1 0
KP143082.1.1457 KF625180.1.1799 99.3 431 1 2 1 429 1 431 -1 0
2) a databank .tsv file containing ~45000 taxonomies correspondent to the DNA sequences. Each taxonomy is in one line:
$ head taxonomy.file.tsv
KP143082.1.1457 D_0__Bacteria;D_1__Firmicutes;D_2__Bacilli;D_3__Bacillales;D_4__Bacillaceae;D_5__Bacillus;D_6__Bacillus_amyloliquefaciens
KF625180.1.1799 D_0__Bacteria;D_1__Firmicutes;D_2__Bacilli;D_3__Bacillales;D_4__Bacillaceae;D_5__Bacillus;D_6__Bacillus_atrophaeus
So, given sequence KF625180.1.1799. I previously aligned it against a databank containing ~45000 other DNA sequences and got an output whis has all the accessions to sequences that it matched. What the loop does is that it finds the taxonomies for all those sequences and calculates the "statistics" I mentionded previously. Code does it for all the DNA-sequences-accesions I have.
TAXONOMY=path/taxonomy.file.tsv
while read line
do
#find hits
hits=$(grep $line alnout_file | cut -f 2)
completename=$(grep $line $TAXONOMY | sed 's/D_0.*D_4/D_4/g')
printf "\nRate of taxonomies for this sequence in %%:\t$completename\n"
printf "Taxonomy\t%aligned\tnumber_ocurrences_in_the_alignment\tnum_ocurrences_in_databank\t%alingment/databank\n"
#find hits and calculate the frequence (%) of the taxonomy in the alignment output
# ex.: Bacillus_subtilis 33
freqHits=$(grep "${hits[#]}" $TAXONOMY | \
cut -f 2 | \
awk '{a[$0]++} END {for (i in a) {print i, "\t", a[i]/NR*100, "\t", a[i]}}' | \
sed -e 's/D_0.*D_5/D_5/g' -e 's#\s\t\s#\t#g' | \
sort -k2 -hr)
# print frequence of each taxonomy in the databank
freqBank=$(while read line; do grep -c "$line" $TAXONOMY; done < <(echo "$freqHits" | cut -f 1))
#print cols with taxonomy and calculations
paste <(printf %s "$freqHits") <(printf %s "$freqBank") | awk '{print $1,"\t",$2"%","\t",$3,"\t",$4,"\t",$3/$4*100"%"}'
done < input_file
It is a lot of greps and parsing so it takes about ~12h running in one processor for doing it to all the 45000 DNA sequence accessions. The, I would like to split input_file and do it in all the processors I have (14) because it would the time spend in that.
Thank you all for being so patient with me =)

Answer 1

You are looking for --pipe. In this case you can even use the optimized --pipepart (version >20160621):
export TAXONOMY=path/taxonomy.file.tsv
doit() {
while read line
do
#find hits
hits=$(grep $line alnout_file | cut -f 2)
completename=$(grep $line $TAXONOMY | sed 's/D_0.*D_4/D_4/g')
printf "\nRate of taxonomies for this sequence in %%:\t$completename\n"
printf "Taxonomy\t%aligned\tnumber_ocurrences_in_the_alignment\tnum_ocurrences_in_databank\t%alingment/databank\n"
#find hits and calculate the frequence (%) of the taxonomy in the alignment output
# ex.: Bacillus_subtilis 33
freqHits=$(grep "${hits[#]}" $TAXONOMY | \
cut -f 2 | \
awk '{a[$0]++} END {for (i in a) {print i, "\t", a[i]/NR*100, "\t", a[i]}}' | \
sed -e 's/D_0.*D_5/D_5/g' -e 's#\s\t\s#\t#g' | \
sort -k2 -hr)
# print frequence of each taxonomy in the databank
freqBank=$(while read line; do grep -c "$line" $TAXONOMY; done < <(echo "$freqHits" | cut -f 1))
#print cols with taxonomy and calculations
paste <(printf %s "$freqHits") <(printf %s "$freqBank") | awk '{print $1,"\t",$2"%","\t",$3,"\t",$4,"\t",$3/$4*100"%"}'
done
}
export -f doit
parallel -a input_file --pipepart doit
This will chop input_file into 10*ncpu blocks (where ncpu is the number of CPU threads), pass each block to doit, run ncpu jobs in parallel.
That said I think your real problem is spawning too many programs: If you rewrite doit in Perl or Python I will expect you will see a major speedup.

Answer 2

As an alternative I threw together a quick test.
#! /bin/env bash
mkfifo PIPELINE # create a single queue
cat "$1" > PIPELINE & # supply it with records
{ declare -i cnt=0 max=14
while (( ++cnt <= max )) # spawn loop creates worker jobs
do printf -v fn "%02d" $cnt
while read -r line # each work loop reads common stdin...
do echo "$fn:[$line]"
sleep 1
done >$fn.log 2>&1 & # these run in background in parallel
done # this one exits
} < PIPELINE # *all* read from the same queue
wait
cat [0-9][0-9].log
Doesn't need split, but does need a mkfifo.
Obviously, change the code inside the internal loop.

Answer 3

This answers what you asked, namely how to process in parallel the 14 files you get from running split. However, I don't think it is the best way of doing whatever it is that you are trying to do - but we would need some answers from you for that.
So, let's make a million line file and split it into 14 parts:
seq 1000000 > 1M
split -n 14 1M part-
That gives me 14 files called part-aa through part-an. Now your question is how to process those 14 parts in parallel - (read the last line first):
#!/bin/bash
# This function will be called for each of the 14 files
DoOne(){
# Pick up parameters
job=$1
file=$2
# Count lines in specified file
lines=$(wc -l < "$file")
echo "Job No: $job, file: $file, lines: $lines"
}
# Make the function above known to processes spawned by GNU Parallel
export -f DoOne
# Run 14 parallel instances of "DoOne" passing job number and filename to each
parallel -k -j 14 DoOne {#} {} ::: part-??
Sample Output
Job No: 1, file: part-aa, lines: 83861
Job No: 2, file: part-ab, lines: 72600
Job No: 3, file: part-ac, lines: 70295
Job No: 4, file: part-ad, lines: 70295
Job No: 5, file: part-ae, lines: 70294
Job No: 6, file: part-af, lines: 70295
Job No: 7, file: part-ag, lines: 70295
Job No: 8, file: part-ah, lines: 70294
Job No: 9, file: part-ai, lines: 70295
Job No: 10, file: part-aj, lines: 70295
Job No: 11, file: part-ak, lines: 70295
Job No: 12, file: part-al, lines: 70294
Job No: 13, file: part-am, lines: 70295
Job No: 14, file: part-an, lines: 70297
You would omit the -k argument to GNU Parallel normally - I only added it so the output comes in order.

Answer 4

I think that using a bunch of grep and awk commands is the wrong approach here - you would be miles better off using Perl, or awk. As you have not provided any sample files I generated some using this code:
#!/bin/bash
for a in {A..Z} {0..9} ; do
for b in {A..Z} {0..9} ; do
for c in {A..Z} {0..9} ; do
echo "${a}${b}${c}"
done
done
done > a
# Now make file "b" which has the same stuff but shuffled into a different order
gshuf < a > b
Note that there are 26 letters in the alphabet, so if I add the digits 0..9 to the letters of the alphabet, I get 36 alphanumeric digits and if I nest 3 loops of that I get 36^3 or 46,656 lines which matches your file sizes roughly. File a now looks like this:
AAA
AAB
AAC
AAD
AAE
AAF
File b looks like this:
UKM
L50
AOC
79U
K6S
6PO
12I
XEV
WJN
Now I want to loop through a finding the corresponding line in b. First, I use your approach:
time while read thing ; do grep $thing b > /dev/null ; done < a
That takes 9 mins 35 seconds.
If I now exit grep on the first match, on average I will find it in the middle, which means the time will be halved since I won't continue to needlessly read b after I find what I want.
time while read thing ; do grep -m1 $thing b > /dev/null ; done < a
That improves the time down to 4 mins 30 seconds.
If I now use awk to read the contents of b into an associative array (a.k.a. hash) and then read the elements of a and find them in b like this:
time awk 'FNR==NR{a[$1]=$1; next} {print a[$1]}' b a > /dev/null
That now runs in 0.07 seconds. Hopefully you get the idea of what I am driving at. I expect Perl would do this in the same time and also provide more expressive facilities for the maths in the middle of your loop too.

Answer 5

I hope this small script helps you out:
function process {
while read line; do
echo "$line"
done < $1
}
function loop {
file=$1
chunks=$2
dir=`mktemp -d`
cd $dir
split -n l/$chunks $file
for i in *; do
process "$i" &
done
rm -rf $dir
}
loop /tmp/foo 14
It runs the process loop on the specified file with the specified number of chunks (without splitting lines) in parallel (using & to put each invocation in the background). I hope it gets you started.

Answer 6

This can do the job for You, I am not familiar with parallel instead using native bash spawning processes &:
function loop () {
while IFS= read -r -d $'\n'
do
# YOUR BIG STUFF
done < "${1}"
}
arr_files=(./xa*)
for i in "${arr_files[#]}"
do loop "${i}" &
done
wait