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<chapter>
<header>
<copyright>
<year>2007</year>
<year>2016</year>
<holder>Ericsson AB, All Rights Reserved</holder>
</copyright>
<legalnotice>
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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<title>The Seven Myths of Erlang Performance</title>
<prepared>Bjorn Gustavsson</prepared>
<docno></docno>
<date>2007-11-10</date>
<rev></rev>
<file>myths.xml</file>
</header>
<marker id="myths"></marker>
<p>Some truths seem to live on well beyond their best-before date,
perhaps because "information" spreads faster from person-to-person
than a single release note that says, for example, that body-recursive
calls have become faster.</p>
<p>This section tries to kill the old truths (or semi-truths) that have
become myths.</p>
<section>
<title>Myth: Tail-Recursive Functions are Much Faster
Than Recursive Functions</title>
<p><marker id="tail_recursive"></marker>According to the myth,
recursive functions leave references
to dead terms on the stack and the garbage collector has to copy
all those dead terms, while tail-recursive functions immediately
discard those terms.</p>
<p>That used to be true before R7B. In R7B, the compiler started
to generate code that overwrites references to terms that will never
be used with an empty list, so that the garbage collector would not
keep dead values any longer than necessary.</p>
<p>Even after that optimization, a tail-recursive function is
still most of the times faster than a body-recursive function. Why?</p>
<p>It has to do with how many words of stack that are used in each
recursive call. In most cases, a recursive function uses more words
on the stack for each recursion than the number of words a tail-recursive
would allocate on the heap. As more memory is used, the garbage
collector is invoked more frequently, and it has more work traversing
the stack.</p>
<p>In R12B and later releases, there is an optimization that
in many cases reduces the number of words used on the stack in
body-recursive calls. A body-recursive list function and a
tail-recursive function that calls <seealso
marker="stdlib:lists#reverse/1">lists:reverse/1</seealso> at
the end will use the same amount of memory.
<c>lists:map/2</c>, <c>lists:filter/2</c>, list comprehensions,
and many other recursive functions now use the same amount of space
as their tail-recursive equivalents.</p>
<p>So, which is faster?
It depends. On Solaris/Sparc, the body-recursive function seems to
be slightly faster, even for lists with a lot of elements. On the x86
architecture, tail-recursion was up to about 30% faster.</p>
<p>So, the choice is now mostly a matter of taste. If you really do need
the utmost speed, you must <em>measure</em>. You can no longer be
sure that the tail-recursive list function always is the fastest.</p>
<note><p>A tail-recursive function that does not need to reverse the
list at the end is faster than a body-recursive function,
as are tail-recursive functions that do not construct any terms at all
(for example, a function that sums all integers in a list).</p></note>
</section>
<section>
<title>Myth: Operator "++" is Always Bad</title>
<p>The <c>++</c> operator has, somewhat undeservedly, got a bad reputation.
It probably has something to do with code like the following,
which is the most inefficient way there is to reverse a list:</p>
<p><em>DO NOT</em></p>
<code type="erl">
naive_reverse([H|T]) ->
naive_reverse(T)++[H];
naive_reverse([]) ->
[].</code>
<p>As the <c>++</c> operator copies its left operand, the result
is copied repeatedly, leading to quadratic complexity.</p>
<p>But using <c>++</c> as follows is not bad:</p>
<p><em>OK</em></p>
<code type="erl">
naive_but_ok_reverse([H|T], Acc) ->
naive_but_ok_reverse(T, [H]++Acc);
naive_but_ok_reverse([], Acc) ->
Acc.</code>
<p>Each list element is copied only once.
The growing result <c>Acc</c> is the right operand
for the <c>++</c> operator, and it is <em>not</em> copied.</p>
<p>Experienced Erlang programmers would write as follows:</p>
<p><em>DO</em></p>
<code type="erl">
vanilla_reverse([H|T], Acc) ->
vanilla_reverse(T, [H|Acc]);
vanilla_reverse([], Acc) ->
Acc.</code>
<p>This is slightly more efficient because here you do not build a
list element only to copy it directly. (Or it would be more efficient
if the compiler did not automatically rewrite <c>[H]++Acc</c>
to <c>[H|Acc]</c>.)</p>
</section>
<section>
<title>Myth: Strings are Slow</title>
<p>String handling can be slow if done improperly.
In Erlang, you need to think a little more about how the strings
are used and choose an appropriate representation. If you
use regular expressions, use the
<seealso marker="stdlib:re">re</seealso> module in STDLIB
instead of the obsolete <c>regexp</c> module.</p>
</section>
<section>
<title>Myth: Repairing a Dets File is Very Slow</title>
<p>The repair time is still proportional to the number of records
in the file, but Dets repairs used to be much slower in the past.
Dets has been massively rewritten and improved.</p>
</section>
<section>
<title>Myth: BEAM is a Stack-Based Byte-Code Virtual Machine
(and Therefore Slow)</title>
<p>BEAM is a register-based virtual machine. It has 1024 virtual registers
that are used for holding temporary values and for passing arguments when
calling functions. Variables that need to survive a function call are saved
to the stack.</p>
<p>BEAM is a threaded-code interpreter. Each instruction is word pointing
directly to executable C-code, making instruction dispatching very fast.</p>
</section>
<section>
<title>Myth: Use "_" to Speed Up Your Program When a Variable
is Not Used</title>
<p>That was once true, but from R6B the BEAM compiler can see
that a variable is not used.</p>
</section>
<section>
<title>Myth: A NIF Always Speeds Up Your Program</title>
<p>Rewriting Erlang code to a NIF to make it faster should be
seen as a last resort. It is only guaranteed to be dangerous,
but not guaranteed to speed up the program.</p>
<p>Doing too much work in each NIF call will
<seealso marker="erts:erl_nif#WARNING">degrade responsiveness
of the VM</seealso>. Doing too little work may mean that
the gain of the faster processing in the NIF is eaten up by
the overhead of calling the NIF and checking the arguments.</p>
<p>Be sure to read about
<seealso marker="erts:erl_nif#lengthy_work">Long-running NIFs</seealso>
before writing a NIF.</p>
</section>
</chapter>
