GNU logs - #32099, boring messages

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Subject: bug#32099: New uniq option for speed
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Thank you very much for maintaining coreutils!

It seems to me that it would be hard to
underestimate how useful it is.


The main reason I'm writing is to humbly suggest
a performance improvement to the "uniq" command.

It currently requires its input to be sorted.

Sorting generally takes about O(N*log(N)) time.

However, it seems to me that sorting is
unnecessary.

You can see this is so in the following example

    $ echo -e "b\na\nb" | awk '!seen[$0]++'

It basically avoids sorting by using hashed
indexes into an associative array to find
previously seen values in about O(N) time.

I expect it would be about O(log(N)) times faster
than the sorting the uniq command currently
requires.

For big values of N, the time saved could be
substantial.


Humble suggestion.

Add an option to the "uniq" command.

Let it work quickly with unsorted data.

Maybe the new option could be something like
"-usi" for "unsorted input".

Thanks,
Kingsley

-- 
Time is the fire in which we all burn.

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To: "Kingsley G. Morse Jr." <kingsley@HIDDEN>
Subject: bug#32099: Acknowledgement (New uniq option for speed)
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Subject: bug#32099: New uniq option for speed
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Kingsley G. Morse Jr. wrote:
>      $ echo -e "b\na\nb" | awk '!seen[$0]++'
>=20
> It basically avoids sorting by using hashed
> indexes into an associative array to find
> previously seen values in about O(N) time.

No, it's still O(N log N) because hash table lookup is really O(log N), d=
espite=20
what many textbooks say. Though no doubt we could make it faster than tha=
n the=20
sorting pipeline, it wouldn't be algorithmically faster. See, for example=
:

https://lemire.me/blog/2009/08/18/do-hash-tables-work-in-constant-time/

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Subject: bug#32099: New uniq option for speed
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References: <20180708210356.c5fwiocbvdndkgxh@HIDDEN>
From: Assaf Gordon <assafgordon@HIDDEN>
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Ηello,

On 08/07/18 03:03 PM, Kingsley G. Morse Jr. wrote:
> The main reason I'm writing is to humbly suggest
> a performance improvement to the "uniq" command.
> 
> It currently requires its input to be sorted.
> 
> Sorting generally takes about O(N*log(N)) time.
> 
> However, it seems to me that sorting is
> unnecessary.
> 
> You can see this is so in the following example
> 
>      $ echo -e "b\na\nb" | awk '!seen[$0]++'

In addition to Paul's reply, here are couple of more practical issues:

1.
GNU sort has several non trivial (and not obvious) advantages:

It can sort a file larger than available memory (i.e. you
can sort a 3GB file on machine with 1GB of RAM).

It can sort using multiple threads, making sorting faster.

If you have a powerful machine (lots of ram and lots of CPUs),
you can sort entirely in memory like so:

     sort -S 10GB --parallel=10 -T /foo/bar INPUT > OUTPUT

The "-S" sets the maximum amount of memory sort is allowed to use,
The "--parallel" sets the number of parallel sorting threads,
The "-T" points to a non-existing directory - ensuring that
if sort runs out of memory (input too large) then it will fail
instead of resorting to using disk storage (and slower I/O).

There are many other combinations (e.g. "--compress-program").

A simple hash implementation will not be able to do so.


2.
Sort already supports printing only unique values with the "-u" option.
So by using the correct combination of keys (-k) and unique (-u)
you can get unique values without even invoking "uniq"
(if your concert is starting another process).

Note that uniq will compare the entire line, and sort will "unique"
only the specified "keys", but sort also has last the "--stable"
option that can affect the results.


3.
Sometimes you really just want to see the list of unique values,
and that's valid.
But often times you want to later examine or do something with the list
of unique values, and then it is common to sort it.

A hash implementation of "unique" will not print sorted items,
and then you'll likely need to pipe it to another "sort" anyhow
(perhaps with much smaller number of items, but still need sort).


4.
The Unix philosophy often says
   "Write programs that do one thing and do it well."
( https://en.wikipedia.org/wiki/Unix_philosophy )

GNU Sort does sorting very well.
Other programs that require sorted input can rely on it (e.g. join,
uniq, etc.).


5.
Using your awk example is actually a fantastic way to achieve
what you wanted - it fits perfectly in "do one thing and do it well".

Note that If you're using a recent Debian or Ubuntu machine,
they have switched the default awk implementation from GNU awk (gawk)
to "mawk". "mawk" is indeed faster in some aspects, but it seems gawk is
much faster when it comes to hashing.

Observe the following:

   $ seq 1000000 | time -p gawk '!seen[$0]++' > /dev/null
   real 0.40
   user 0.35
   sys 0.04
   $ seq 1000000 | time -p mawk '!seen[$0]++' > /dev/null
   real 10.48
   user 10.40
   sys 0.07

Using awk will also enable you to later extend your task to
achieve more. Eg. the following program:
   awk 'NR==FNR{seen[$1]++;next} seen[$1]>0' a.txt b.txt

Will only print lines from "b.txt" which have a key matching from
file "a.txt". kind of a hash-based join between two files.


6.
Lastly, if you still want a program that uses hashing to discard
duplicates in a file, may I humbly suggest GNU datamash:
    https://www.gnu.org/software/datamash/
(disclaimer: I'm datamash's developer).

It can easily remove duplicates, and it uses the same hashing code
that other coreutils program use. Example:

   $ printf "%s\n" a a b a b c b | datamash rmdup 1
   a
   b
   c

Datamash has several additional useful features,
for example it can remove duplicates from a specific column but still 
print the entire matching line:

   $ printf "FOO %s %s\n" a 1 a 2 b 3 a 4 b 5 c 6 b 7 \
         | datamash -W rmdup 2
   FOO a 1
   FOO b 3
   FOO c 6



Hope this helps,
regards,
  - assaf

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Subject: bug#32099: Benchmarks: Hashing ~70% faster (Was: New uniq option for speed)
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Hi Assaf,

I like datamash.

And I like avoiding a pipe with sort's "-u"
option.

And I like your benchmarks.

Mine are humbly attached.

They compare sorting to hashing.

At the moment, hashing seems to me to be about 70%
faster.

And to scale better.

I'd still like uniq to be faster and free from
sort.

Feel free to let me know if I screwed up.

Thanks,
Kingsley

On 07/09/2018 14:53, Assaf Gordon wrote:
> Ηello,
> 
> On 08/07/18 03:03 PM, Kingsley G. Morse Jr. wrote:
> > The main reason I'm writing is to humbly suggest
> > a performance improvement to the "uniq" command.
> > 
> > It currently requires its input to be sorted.
> > 
> > Sorting generally takes about O(N*log(N)) time.
> > 
> > However, it seems to me that sorting is
> > unnecessary.
> > 
> > You can see this is so in the following example
> > 
> >      $ echo -e "b\na\nb" | awk '!seen[$0]++'
> 
> In addition to Paul's reply, here are couple of more practical issues:
> 
> 1.
> GNU sort has several non trivial (and not obvious) advantages:
> 
> It can sort a file larger than available memory (i.e. you
> can sort a 3GB file on machine with 1GB of RAM).
> 
> It can sort using multiple threads, making sorting faster.
> 
> If you have a powerful machine (lots of ram and lots of CPUs),
> you can sort entirely in memory like so:
> 
>     sort -S 10GB --parallel=10 -T /foo/bar INPUT > OUTPUT
> 
> The "-S" sets the maximum amount of memory sort is allowed to use,
> The "--parallel" sets the number of parallel sorting threads,
> The "-T" points to a non-existing directory - ensuring that
> if sort runs out of memory (input too large) then it will fail
> instead of resorting to using disk storage (and slower I/O).
> 
> There are many other combinations (e.g. "--compress-program").
> 
> A simple hash implementation will not be able to do so.
> 
> 
> 2.
> Sort already supports printing only unique values with the "-u" option.
> So by using the correct combination of keys (-k) and unique (-u)
> you can get unique values without even invoking "uniq"
> (if your concert is starting another process).
> 
> Note that uniq will compare the entire line, and sort will "unique"
> only the specified "keys", but sort also has last the "--stable"
> option that can affect the results.
> 
> 
> 3.
> Sometimes you really just want to see the list of unique values,
> and that's valid.
> But often times you want to later examine or do something with the list
> of unique values, and then it is common to sort it.
> 
> A hash implementation of "unique" will not print sorted items,
> and then you'll likely need to pipe it to another "sort" anyhow
> (perhaps with much smaller number of items, but still need sort).
> 
> 
> 4.
> The Unix philosophy often says
>   "Write programs that do one thing and do it well."
> ( https://en.wikipedia.org/wiki/Unix_philosophy )
> 
> GNU Sort does sorting very well.
> Other programs that require sorted input can rely on it (e.g. join,
> uniq, etc.).
> 
> 
> 5.
> Using your awk example is actually a fantastic way to achieve
> what you wanted - it fits perfectly in "do one thing and do it well".
> 
> Note that If you're using a recent Debian or Ubuntu machine,
> they have switched the default awk implementation from GNU awk (gawk)
> to "mawk". "mawk" is indeed faster in some aspects, but it seems gawk is
> much faster when it comes to hashing.
> 
> Observe the following:
> 
>   $ seq 1000000 | time -p gawk '!seen[$0]++' > /dev/null
>   real 0.40
>   user 0.35
>   sys 0.04
>   $ seq 1000000 | time -p mawk '!seen[$0]++' > /dev/null
>   real 10.48
>   user 10.40
>   sys 0.07
> 
> Using awk will also enable you to later extend your task to
> achieve more. Eg. the following program:
>   awk 'NR==FNR{seen[$1]++;next} seen[$1]>0' a.txt b.txt
> 
> Will only print lines from "b.txt" which have a key matching from
> file "a.txt". kind of a hash-based join between two files.
> 
> 
> 6.
> Lastly, if you still want a program that uses hashing to discard
> duplicates in a file, may I humbly suggest GNU datamash:
>    https://www.gnu.org/software/datamash/
> (disclaimer: I'm datamash's developer).
> 
> It can easily remove duplicates, and it uses the same hashing code
> that other coreutils program use. Example:
> 
>   $ printf "%s\n" a a b a b c b | datamash rmdup 1
>   a
>   b
>   c
> 
> Datamash has several additional useful features,
> for example it can remove duplicates from a specific column but still print
> the entire matching line:
> 
>   $ printf "FOO %s %s\n" a 1 a 2 b 3 a 4 b 5 c 6 b 7 \
>         | datamash -W rmdup 2
>   FOO a 1
>   FOO b 3
>   FOO c 6
> 
> 
> 
> Hope this helps,
> regards,
>  - assaf
> 

-- 
Time is the fire in which we all burn.


--qzkemyanjw2idojc
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--qzkemyanjw2idojc
Content-Type: text/plain; charset=us-ascii
Content-Description: benchmarking script
Content-Disposition: attachment; filename=uniq_demo

# Tweaking these...
max_lines_of_data=100000                # The total number of lines of data to search for unique values in. Bigger values have lomger run times.
max_line_length=10                      # How many bytes are in each line that may be unique. Smaller values create fewer unique lines.

# leads to...
interval_between_lines_of_data=$(( $max_lines_of_data / 5 ))

# Report heading.
echo lines,percent unique,algorithm,time

# Benchmark with increasing lines of data...
for data_lines in $( seq 1 $interval_between_lines_of_data $max_lines_of_data ) ; do

    # Benchmark with increasing line length..
    for line_length in $( seq $max_line_length ) ; do

        # Generate a certain number of lines of random data of a certain length
        tr -cd '[[:alnum:]]' < /dev/urandom | fold -bw "$line_length" | head -n "$data_lines" > /tmp/data

        # Calculate the percentage of lines that are unique.
        number_of_unique_lines="$( sort -u /tmp/data | wc -l )"
        percent_unique="$( calc -dp "$number_of_unique_lines/$data_lines" )"

        # Benchmark sort with its unique option.
        /usr/bin/time -o /tmp/sort_time -f %e sort -u /tmp/data > /dev/null 
        echo "$data_lines,$percent_unique,sort,$( cat /tmp/sort_time )"

        # Benchmark awk hashing.
        /usr/bin/time -o /tmp/hash_time -f %e awk '!seen[$0]++' /tmp/data  > /dev/null
        echo "$data_lines,$percent_unique,hash,$( cat /tmp/hash_time )"

    done
done

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Subject: bug#32099: Benchmarks: Hashing ~70% faster (Was: New uniq option for speed)
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tag 32099 notabug
severity 32099 wishlist
close 32099
stop

Hello Kingsley,

On 09/07/18 10:29 PM, Kingsley G. Morse Jr. wrote:
> And I like your benchmarks.
> 
> Mine are humbly attached.
> 
> They compare sorting to hashing.
> 
> At the moment, hashing seems to me to be about 70%
> faster.
> 
> And to scale better.
> 
> I'd still like uniq to be faster and free from
> sort.

Thank you for taking the time to create and provide these,
including the scripts to reproduce it.

I've marked this item as "closed / wishlist" - but only because it
is technically not a bug report. Discussion is welcomed to continue
by replying to this thread.

Being "faster" alone is important but not the only criteria (as
mentioned in the previous email's examples).

Your measurements are a good start towards stronger support to
hash-based uniq implementation (a working patch, btw, would be even
stronger).

I would suggest several improvements to the measurements, to ensure
relevant information is conveyed:

1.
Specify exactly which versions of awk/sort you are using
(e.g. which versions, whether from your distribution or compiled from 
source, if compiled than which compiler / optimization flags).
What CPUs is being used, how much memory does the computer have, etc.

2.
I would suggest adding "sort | uniq" to the charts, because that is the
real base-line you are trying to improve.
I would also consider adding "datamash rmdup" to the charts, because its
hash-based implementation could serve as a ball-park indication of how
a naive hash implementation would work in uniq.

3.
You input is very small (up to 90K lines of 10 characters each) - that
does not seem to stress-test any significant parts of the algorithms
(and for a typical user, waiting 0.05 seconds vs 0.15 seconds does not
matter).

I would recommend much larger input files, with much longer lines -
trying to simulate various real-world scenarios.

Here's a project of someone who tried to compare various hashing
functions: https://github.com/jhunt/hash/
Under the "corpus" directory you'll find few demo data files.
Even the largest one (qnames) is only 84MB - not very big.

Perhaps consider duplicating the content few times, then test it:
   for i in $(seq 1 5);do cat qnames; done > input

To get even closer to real-world input, try several input files
with different ratios of duplicated lines (your script create completely
random data - not very similar to real-world input files).

For example, what happens with many lines share similar sub-strings?
depending on the hashing implementation, this could lead to lower 
performance.

4.
It would be beneficial to see what's the memory requirements and limits
of a hash-based implementation. Currently, because 'sort' is not limited
by available RAM, there is no memory limit (though resorting to disk I/O
might make everything slow).
For example, is it possible to hash an 800M file on a machine with only 
1GB of RAM ? and without additional code, hashing files larger than 
available memory is simply not possible - a very big disadvantage.

5.
To compare "sort' fairly against other options,
I would add to the measurements using "--parallel 1" and later 
"--parallel N" (N being the number of cpu/cores you have).
Does that improve performance?

The "awk" (or datamash) programs do not have a built-in memory limit,
while sort does. It would be useful to specify a large amount of
memory for sort (using "-S") to ensure sort did not revert to disk I/O.

6.
The reported time in your script is the elapsed time (aka "wall time").
A more relevant option would be "user time" + "kernel time"
(optiosn %S and %U in "time -f") - the wall time can be affected by
factors that don't immediately relate to hashing/sorting performance.

7.
In your script you are providing a file-based input,
it might be useful to clear the kernel's cache before each run
to ensure these do not affect the results (especially when dealing with 
large files).
See: 
https://www.tecmint.com/clear-ram-memory-cache-buffer-and-swap-space-on-linux/




To conclude,
There is definitely merit in trying to optimize uniq's performance,
but it must be weighed against other factors (e.g. the ability to 'uniq'
a file larger than available memory, and the ease of using existing 
programs to achieve the same effect).

IMHO it is not a top-priority, so I don't want to give the impression
that if an amazing speed improvement is presented, uniq will be swiftly
rewritten.

But of course, a working patch and strong pro arguments would go a long
way towards incorporating this feature.

regards,
  - assaf

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Subject: bug#32099: datamash wins! (Was: New uniq option for speed)
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--3auohxm5ypw3cvru
Content-Type: text/plain; charset=us-ascii
Content-Disposition: inline

Hey Assaf,

Thank you very much for taking the time to share
your thoughts.

People like you, willing to improve free software
and help the common good, restore my faith in
humanity.


I followed much of your advice.

I ran more benchmarks: 

gawk, mawk, sort -u, sort | uniq and ... datamash rmdup!

Plus, I benchmarked them against a bigger file.

~1 GB!

Plus, plus, I measured how much memory they used!


The result?

Hashing algorithms always won.

I expected it.

When I benchmarked data compression apps, one
named "rzip" that searched its cache of unique
values with hashing was much faster.

    https://www.linuxjournal.com/article/8051


But, to be fair, I was surprised by how little
memory datamash seemed to use.

Maybe I screwed up.

I checked max resident set size of the process
during its lifetime with /usr/bin/time's "%M"
specifier.


Plus, plus, plus, I created a composite
performance criteria of 

    elapsed time * memory used

(It's in the attached spread sheet.)

That winner at ~1 GB?

datamash!

No matter whether the keys were unique or
duplicated, "datamash rmdup 1" won!

New files are attached.


Humble suggestion:

Don't worry about running out of memory.

Hashing could be added to the "uniq" command as...
(wait for it...) an option.

So you could always omit it and use sort.


For yours truly, the big gain is actually being
able to ditch sort.

Less is more.

It's a UNIX thing.


So it is said.

So it is done.

Sorting is great, but

less is number one!

~K

PS: Congratulations on datamash performing so
    well.

On 07/10/2018 12:21, Assaf Gordon wrote:
> tag 32099 notabug
> severity 32099 wishlist
> close 32099
> stop
> 
> Hello Kingsley,
> 
> On 09/07/18 10:29 PM, Kingsley G. Morse Jr. wrote:
> > And I like your benchmarks.
> > 
> > Mine are humbly attached.
> > 
> > They compare sorting to hashing.
> > 
> > At the moment, hashing seems to me to be about 70%
> > faster.
> > 
> > And to scale better.
> > 
> > I'd still like uniq to be faster and free from
> > sort.
> 
> Thank you for taking the time to create and provide these,
> including the scripts to reproduce it.
> 
> I've marked this item as "closed / wishlist" - but only because it
> is technically not a bug report. Discussion is welcomed to continue
> by replying to this thread.
> 
> Being "faster" alone is important but not the only criteria (as
> mentioned in the previous email's examples).
> 
> Your measurements are a good start towards stronger support to
> hash-based uniq implementation (a working patch, btw, would be even
> stronger).
> 
> I would suggest several improvements to the measurements, to ensure
> relevant information is conveyed:
> 
> 1.
> Specify exactly which versions of awk/sort you are using
> (e.g. which versions, whether from your distribution or compiled from
> source, if compiled than which compiler / optimization flags).
> What CPUs is being used, how much memory does the computer have, etc.
> 
> 2.
> I would suggest adding "sort | uniq" to the charts, because that is the
> real base-line you are trying to improve.
> I would also consider adding "datamash rmdup" to the charts, because its
> hash-based implementation could serve as a ball-park indication of how
> a naive hash implementation would work in uniq.
> 
> 3.
> You input is very small (up to 90K lines of 10 characters each) - that
> does not seem to stress-test any significant parts of the algorithms
> (and for a typical user, waiting 0.05 seconds vs 0.15 seconds does not
> matter).
> 
> I would recommend much larger input files, with much longer lines -
> trying to simulate various real-world scenarios.
> 
> Here's a project of someone who tried to compare various hashing
> functions: https://github.com/jhunt/hash/
> Under the "corpus" directory you'll find few demo data files.
> Even the largest one (qnames) is only 84MB - not very big.
> 
> Perhaps consider duplicating the content few times, then test it:
>   for i in $(seq 1 5);do cat qnames; done > input
> 
> To get even closer to real-world input, try several input files
> with different ratios of duplicated lines (your script create completely
> random data - not very similar to real-world input files).
> 
> For example, what happens with many lines share similar sub-strings?
> depending on the hashing implementation, this could lead to lower
> performance.
> 
> 4.
> It would be beneficial to see what's the memory requirements and limits
> of a hash-based implementation. Currently, because 'sort' is not limited
> by available RAM, there is no memory limit (though resorting to disk I/O
> might make everything slow).
> For example, is it possible to hash an 800M file on a machine with only 1GB
> of RAM ? and without additional code, hashing files larger than available
> memory is simply not possible - a very big disadvantage.
> 
> 5.
> To compare "sort' fairly against other options,
> I would add to the measurements using "--parallel 1" and later "--parallel
> N" (N being the number of cpu/cores you have).
> Does that improve performance?
> 
> The "awk" (or datamash) programs do not have a built-in memory limit,
> while sort does. It would be useful to specify a large amount of
> memory for sort (using "-S") to ensure sort did not revert to disk I/O.
> 
> 6.
> The reported time in your script is the elapsed time (aka "wall time").
> A more relevant option would be "user time" + "kernel time"
> (optiosn %S and %U in "time -f") - the wall time can be affected by
> factors that don't immediately relate to hashing/sorting performance.
> 
> 7.
> In your script you are providing a file-based input,
> it might be useful to clear the kernel's cache before each run
> to ensure these do not affect the results (especially when dealing with
> large files).
> See: https://www.tecmint.com/clear-ram-memory-cache-buffer-and-swap-space-on-linux/
> 
> 
> 
> 
> To conclude,
> There is definitely merit in trying to optimize uniq's performance,
> but it must be weighed against other factors (e.g. the ability to 'uniq'
> a file larger than available memory, and the ease of using existing programs
> to achieve the same effect).
> 
> IMHO it is not a top-priority, so I don't want to give the impression
> that if an amazing speed improvement is presented, uniq will be swiftly
> rewritten.
> 
> But of course, a working patch and strong pro arguments would go a long
> way towards incorporating this feature.
> 
> regards,
>  - assaf
> 
> 
> 

-- 
Time is the fire in which we all burn.


--3auohxm5ypw3cvru
Content-Type: text/plain; charset=us-ascii
Content-Description: updated benchmarking script
Content-Disposition: attachment; filename=uniq_demo

# Report heading.
echo 'lines,line length,percent unique,algorithm,time(sec),memory(K)'

# Benchmark with increasing lines of data...
for data_lines in 1 10 100 1000 10000 100000 1000000 ; do

    # Benchmark with increasing line length..
    for line_length in 1 10 100 1000 ; do

        # Synchronize cached writes to persistent storage
        sync
        
        # Generate a certain number of lines of random data of a certain length
        tr -cd '[[:alnum:]]' < /dev/urandom | fold -bw "$line_length" | head -n "$data_lines" > /tmp/data

        # Calculate the percentage of lines that are unique.
        number_of_unique_lines="$( sort -u /tmp/data | wc -l )"
        percent_unique="$( calc -dp "$number_of_unique_lines/$data_lines" )"

        # Benchmark sort with its unique option.
        /usr/bin/time -o /tmp/sort_time -f %e,%M sort -u /tmp/data > /dev/null 
        echo "$data_lines,$line_length,$percent_unique,sort,$( cat /tmp/sort_time )"

        # Benchmark gawk hashing.
        /usr/bin/time -o /tmp/gawk_time -f %e,%M gawk '!seen[$0]++' /tmp/data  > /dev/null
        echo "$data_lines,$line_length,$percent_unique,gawk,$( cat /tmp/gawk_time )"

        # Benchmark mawk hashing.
        /usr/bin/time -o /tmp/mawk_time -f %e,%M mawk '!seen[$0]++' /tmp/data  > /dev/null
        echo "$data_lines,$line_length,$percent_unique,mawk,$( cat /tmp/mawk_time )"

        # Benchmark datamash.
        /usr/bin/time -o /tmp/datamash_time -f %e,%M cat /tmp/data | datamash rmdup 1 > /dev/null
        echo "$data_lines,$line_length,$percent_unique,datamash,$( cat /tmp/datamash_time )"

        # Benchmark a pipe of sort and unique.
        /usr/bin/time -o /tmp/sort_and_uniq_time -f %e,%M sort /tmp/data | uniq > /dev/null
        echo "$data_lines,$line_length,$percent_unique,sort and uniq,$( cat /tmp/sort_and_uniq_time )"

    done
done

--3auohxm5ypw3cvru
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--3auohxm5ypw3cvru
Content-Type: text/plain; charset=us-ascii
Content-Description: new benchmark results
Content-Disposition: attachment; filename="uniq_demo.log.2"

lines,line length,percent unique,algorithm,time(sec),memory(K)
1,1,1,sort,0.00,1848
1,1,1,gawk,0.00,3424
1,1,1,mawk,0.00,1780
1,1,1,datamash,0.00,1580
1,1,1,sort and uniq,0.00,1828
1,10,1,sort,0.00,1916
1,10,1,gawk,0.00,3352
1,10,1,mawk,0.00,1832
1,10,1,datamash,0.00,1560
1,10,1,sort and uniq,0.00,1828
1,100,1,sort,0.00,1940
1,100,1,gawk,0.00,3324
1,100,1,mawk,0.00,1680
1,100,1,datamash,0.00,1564
1,100,1,sort and uniq,0.00,1904
1,1000,1,sort,0.00,1788
1,1000,1,gawk,0.00,3312
1,1000,1,mawk,0.00,1740
1,1000,1,datamash,0.00,1704
1,1000,1,sort and uniq,0.00,1916
10,1,0.9,sort,0.00,1780
10,1,0.9,gawk,0.00,3412
10,1,0.9,mawk,0.00,1628
10,1,0.9,datamash,0.00,1584
10,1,0.9,sort and uniq,0.00,1840
10,10,1,sort,0.00,1864
10,10,1,gawk,0.00,3444
10,10,1,mawk,0.00,1792
10,10,1,datamash,0.00,1616
10,10,1,sort and uniq,0.00,1928
10,100,1,sort,0.00,1792
10,100,1,gawk,0.00,3252
10,100,1,mawk,0.00,1784
10,100,1,datamash,0.00,1620
10,100,1,sort and uniq,0.00,1964
10,1000,1,sort,0.00,1972
10,1000,1,gawk,0.00,3248
10,1000,1,mawk,0.00,1772
10,1000,1,datamash,0.00,1640
10,1000,1,sort and uniq,0.00,1948
100,1,0.49,sort,0.00,1920
100,1,0.49,gawk,0.00,3516
100,1,0.49,mawk,0.00,1636
100,1,0.49,datamash,0.00,1616
100,1,0.49,sort and uniq,0.00,1828
100,10,1,sort,0.00,1968
100,10,1,gawk,0.00,3548
100,10,1,mawk,0.00,1696
100,10,1,datamash,0.00,1668
100,10,1,sort and uniq,0.00,1924
100,100,1,sort,0.00,1916
100,100,1,gawk,0.00,3536
100,100,1,mawk,0.00,1776
100,100,1,datamash,0.00,1632
100,100,1,sort and uniq,0.00,1928
100,1000,1,sort,0.00,1868
100,1000,1,gawk,0.00,3544
100,1000,1,mawk,0.00,1852
100,1000,1,datamash,0.00,1664
100,1000,1,sort and uniq,0.00,1784
1000,1,0.064,sort,0.00,1796
1000,1,0.064,gawk,0.00,3464
1000,1,0.064,mawk,0.00,1688
1000,1,0.064,datamash,0.00,1564
1000,1,0.064,sort and uniq,0.00,1920
1000,10,1,sort,0.00,1876
1000,10,1,gawk,0.00,3476
1000,10,1,mawk,0.00,1816
1000,10,1,datamash,0.00,1708
1000,10,1,sort and uniq,0.00,1804
1000,100,1,sort,0.00,2020
1000,100,1,gawk,0.00,3488
1000,100,1,mawk,0.00,1984
1000,100,1,datamash,0.00,1644
1000,100,1,sort and uniq,0.00,1948
1000,1000,1,sort,0.00,2724
1000,1000,1,gawk,0.00,4620
1000,1000,1,mawk,0.00,2876
1000,1000,1,datamash,0.01,1568
1000,1000,1,sort and uniq,0.01,2836
10000,1,0.0064,sort,0.01,1880
10000,1,0.0064,gawk,0.00,3564
10000,1,0.0064,mawk,0.00,1628
10000,1,0.0064,datamash,0.00,1616
10000,1,0.0064,sort and uniq,0.01,1876
10000,10,1,sort,0.03,1944
10000,10,1,gawk,0.02,4904
10000,10,1,mawk,0.00,2484
10000,10,1,datamash,0.01,1664
10000,10,1,sort and uniq,0.02,1884
10000,100,1,sort,0.02,3076
10000,100,1,gawk,0.01,5636
10000,100,1,mawk,0.00,3352
10000,100,1,datamash,0.02,1564
10000,100,1,sort and uniq,0.03,3036
10000,1000,1,sort,0.05,11644
10000,1000,1,gawk,0.06,14328
10000,1000,1,mawk,0.03,12232
10000,1000,1,datamash,0.09,1728
10000,1000,1,sort and uniq,0.10,11772
100000,1,0.00064,sort,0.20,4252
100000,1,0.00064,gawk,0.04,3332
100000,1,0.00064,mawk,0.01,1756
100000,1,0.00064,datamash,0.01,1728
100000,1,0.00064,sort and uniq,0.21,4252
100000,10,1,sort,0.29,5192
100000,10,1,gawk,0.14,17040
100000,10,1,mawk,0.13,8284
100000,10,1,datamash,0.04,1520
100000,10,1,sort and uniq,0.27,5188
100000,100,1,sort,0.34,13904
100000,100,1,gawk,0.18,26404
100000,100,1,mawk,0.15,17348
100000,100,1,datamash,0.10,1708
100000,100,1,sort and uniq,0.34,13836
100000,1000,1,sort,0.58,101788
100000,1000,1,gawk,0.62,113672
100000,1000,1,mawk,0.42,105888
100000,1000,1,datamash,0.73,1564
100000,1000,1,sort and uniq,0.84,101720
1000000,1,0.000064,sort,1.29,34940
1000000,1,0.000064,gawk,0.44,3304
1000000,1,0.000064,mawk,0.15,1752
1000000,1,0.000064,datamash,0.10,1568
1000000,1,0.000064,sort and uniq,1.33,35088
1000000,10,1,sort,2.66,43728
1000000,10,1,gawk,1.65,138700
1000000,10,1,mawk,1.79,65772
1000000,10,1,datamash,0.44,1620
1000000,10,1,sort and uniq,2.37,44008
1000000,100,1,sort,2.91,131600
1000000,100,1,gawk,2.10,232412
1000000,100,1,mawk,2.32,157876
1000000,100,1,datamash,1.23,1704
1000000,100,1,sort and uniq,3.64,131592
1000000,1000,1,sort,5.36,1010664
1000000,1000,1,gawk,6.53,1107508
1000000,1000,1,mawk,5.23,1042296
1000000,1000,1,datamash,7.79,1620
1000000,1000,1,sort and uniq,7.76,1010804

--3auohxm5ypw3cvru--

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Subject: bug#32099: Benchmarks: Hashing ~70% faster (Was: New uniq option for speed)
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On 07/10/2018 08:21 PM, Assaf Gordon wrote:
> I would suggest several improvements to the measurements, to ensure
> relevant information is conveyed:
> 
> 1.
> [...]

great summary.  With the risk of mentioning already said aspects:

7. Consider all the existing options, i.e. processing modes, of 'uniq' as well.
This means, it has to be considered (upfront!) whether introducing an alternate
way to do things - in this case hashing - only serves for the trivial case,
or whether this would slow down or even contradict the processing with other
options, currently:

  -c, --count           prefix lines by the number of occurrences
  -d, --repeated        only print duplicate lines, one for each group
  -D                    print all duplicate lines
      --all-repeated[=METHOD]  like -D, but allow separating groups
                                 with an empty line;
                                 METHOD={none(default),prepend,separate}
  -f, --skip-fields=N   avoid comparing the first N fields
      --group[=METHOD]  show all items, separating groups with an empty line;
                          METHOD={separate(default),prepend,append,both}
  -i, --ignore-case     ignore differences in case when comparing
  -s, --skip-chars=N    avoid comparing the first N characters
  -u, --unique          only print unique lines
  -z, --zero-terminated     line delimiter is NUL, not newline
  -w, --check-chars=N   compare no more than N characters in lines

Without deeper thinking about it, especially the combinations with
the --group, --repeated and --unique options might be problematic.

8. Standards.  POSIX says:
  http://pubs.opengroup.org/onlinepubs/9699919799/utilities/uniq.html

  The uniq utility shall read an input file comparing adjacent lines,
  and write one copy of each input line on the output. The second and
  succeeding copies of repeated adjacent input lines shall not be written.

This makes an assumption both on the input and output.

Regarding the input, this means that the processing just has to remember
the previous line in order to decide whether to print/discard it in the
output.  Therefore, arbitrary input size is fine.
Hashing most probably will have issues with arbitrary input size;
I do not talk about 1GB files, but _much_ larger files (yes, we
are in 2018 where 1GB is like nothing).

Regarding the output, this means that the output is implicitly in
sort order as well.  Like the input, uniq can discard the already
written data from memory because it is sure that uniq doesn't need
to consider it anymore.


Thus said, a successful optimization idea does not only have to show
that it is faster or needs less resources in _some_ cases, but also
must prove that it does not tear down many cases including extreme
ones.  The current implementation might be as-is for a good reason.
If it turns out that the optimization idea screws up a single
of the above use cases, then the dilemma is whether 2 implementations
are warranted to be kept (maintenance!), and whether it is possible
to detect the extreme cases early enough to switch from the default
to the other processing strategy.

https://en.wikipedia.org/wiki/Perfect_is_the_enemy_of_good
or D. Knuth:
  "premature optimization is the root of all evil
   (or at least most of it) in programming"

As Assaf said, a patch with a proof of concept would be helpful ... even
if it's just helpful to proof that the current implementation is fine.

Have a nice day,
Berny

X-Loop: help-debbugs@HIDDEN
Subject: bug#32099: Testing with other options (Was: Benchmarks: Hashing ~70% faster )
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Hey Berny,

I like your suggestion of testing whether hashing
interferes with any other option.

I was glad to see the POSIX standard doesn't
explicitly require sorted input or output.

If someone writes the patch, I should be able to
test it, at least on up to 1 GB of input.

So,
Kingsley

On 07/12/2018 08:43, Bernhard Voelker wrote:
> On 07/10/2018 08:21 PM, Assaf Gordon wrote:
> > I would suggest several improvements to the measurements, to ensure
> > relevant information is conveyed:
> > 
> > 1.
> > [...]
> 
> great summary.  With the risk of mentioning already said aspects:
> 
> 7. Consider all the existing options, i.e. processing modes, of 'uniq' as well.
> This means, it has to be considered (upfront!) whether introducing an alternate
> way to do things - in this case hashing - only serves for the trivial case,
> or whether this would slow down or even contradict the processing with other
> options, currently:
> 
>   -c, --count           prefix lines by the number of occurrences
>   -d, --repeated        only print duplicate lines, one for each group
>   -D                    print all duplicate lines
>       --all-repeated[=METHOD]  like -D, but allow separating groups
>                                  with an empty line;
>                                  METHOD={none(default),prepend,separate}
>   -f, --skip-fields=N   avoid comparing the first N fields
>       --group[=METHOD]  show all items, separating groups with an empty line;
>                           METHOD={separate(default),prepend,append,both}
>   -i, --ignore-case     ignore differences in case when comparing
>   -s, --skip-chars=N    avoid comparing the first N characters
>   -u, --unique          only print unique lines
>   -z, --zero-terminated     line delimiter is NUL, not newline
>   -w, --check-chars=N   compare no more than N characters in lines
> 
> Without deeper thinking about it, especially the combinations with
> the --group, --repeated and --unique options might be problematic.
> 
> 8. Standards.  POSIX says:
>   http://pubs.opengroup.org/onlinepubs/9699919799/utilities/uniq.html
> 
>   The uniq utility shall read an input file comparing adjacent lines,
>   and write one copy of each input line on the output. The second and
>   succeeding copies of repeated adjacent input lines shall not be written.
> 
> This makes an assumption both on the input and output.
> 
> Regarding the input, this means that the processing just has to remember
> the previous line in order to decide whether to print/discard it in the
> output.  Therefore, arbitrary input size is fine.
> Hashing most probably will have issues with arbitrary input size;
> I do not talk about 1GB files, but _much_ larger files (yes, we
> are in 2018 where 1GB is like nothing).
> 
> Regarding the output, this means that the output is implicitly in
> sort order as well.  Like the input, uniq can discard the already
> written data from memory because it is sure that uniq doesn't need
> to consider it anymore.
> 
> 
> Thus said, a successful optimization idea does not only have to show
> that it is faster or needs less resources in _some_ cases, but also
> must prove that it does not tear down many cases including extreme
> ones.  The current implementation might be as-is for a good reason.
> If it turns out that the optimization idea screws up a single
> of the above use cases, then the dilemma is whether 2 implementations
> are warranted to be kept (maintenance!), and whether it is possible
> to detect the extreme cases early enough to switch from the default
> to the other processing strategy.
> 
> https://en.wikipedia.org/wiki/Perfect_is_the_enemy_of_good
> or D. Knuth:
>   "premature optimization is the root of all evil
>    (or at least most of it) in programming"
> 
> As Assaf said, a patch with a proof of concept would be helpful ... even
> if it's just helpful to proof that the current implementation is fine.
> 
> Have a nice day,
> Berny

-- 
Time is the fire in which we all burn.

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tags 32099 notabug
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 Content preview:  severity 32099 wishlist retitle 32099 uniq: add hash-based
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severity 32099 wishlist
retitle 32099 uniq: add hash-based implementation

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 Content preview:  severity 32099 wishlist retitle 32099 uniq: add hash-based
 implementation [...] 
 Content analysis details:   (2.0 points, 10.0 required)
 pts rule name              description
 ---- ---------------------- --------------------------------------------------
 -0.0 RCVD_IN_DNSWL_NONE     RBL: Sender listed at http://www.dnswl.org/, no
 trust [209.85.215.177 listed in list.dnswl.org]
 -0.0 SPF_PASS               SPF: sender matches SPF record
 0.0 FREEMAIL_FROM Sender email is commonly abused enduser mail provider
 (assafgordon[at]gmail.com)
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severity 32099 wishlist
retitle 32099 uniq: add hash-based implementation