Processes

20012021 Ericsson AB. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Processes Bjorn Gustavsson 2007-11-21 processes.xmlsrc

Creating an Erlang Process

An Erlang process is lightweight compared to threads and processes in operating systems.

A newly spawned Erlang process uses 326 words of memory. The size can be found as follows:

Erlang/OTP 24 [erts-12.0] [64-bit] [smp:8:8] [ds:8:8:10] [async-threads:1] [jit]

Eshell V5.6  (abort with ^G)
1> Fun = fun() -> receive after infinity -> ok end end.
#Fun<...>
2> {_,Bytes} = process_info(spawn(Fun), memory).
{memory,1232}
3> Bytes div erlang:system_info(wordsize).
309

The size includes 233 words for the heap area (which includes the stack). The garbage collector increases the heap as needed.

The main (outer) loop for a process must be tail-recursive. Otherwise, the stack grows until the process terminates.

DO NOT


loop() ->
  receive
     {sys, Msg} ->
         handle_sys_msg(Msg),
         loop();
     {From, Msg} ->
          Reply = handle_msg(Msg),
          From ! Reply,
          loop()
  end,
  io:format("Message is processed~n", []).

The call to io:format/2 will never be executed, but a return address will still be pushed to the stack each time loop/0 is called recursively. The correct tail-recursive version of the function looks as follows:


   loop() ->
      receive
         {sys, Msg} ->
            handle_sys_msg(Msg),
            loop();
         {From, Msg} ->
            Reply = handle_msg(Msg),
            From ! Reply,
            loop()
    end.

Initial Heap Size

The default initial heap size of 233 words is quite conservative to support Erlang systems with hundreds of thousands or even millions of processes. The garbage collector grows and shrinks the heap as needed.

In a system that use comparatively few processes, performance might be improved by increasing the minimum heap size using either the +h option for erl or on a process-per-process basis using the min_heap_size option for spawn_opt/4.

The gain is twofold:

Although the garbage collector grows the heap, it grows it step-by-step, which is more costly than directly establishing a larger heap when the process is spawned. The garbage collector can also shrink the heap if it is much larger than the amount of data stored on it; setting the minimum heap size prevents that.

The emulator probably uses more memory, and because garbage collections occur less frequently, huge binaries can be kept much longer.

In systems with many processes, computation tasks that run for a short time can be spawned off into a new process with a higher minimum heap size. When the process is done, it sends the result of the computation to another process and terminates. If the minimum heap size is calculated properly, the process might not have to do any garbage collections at all. This optimization is not to be attempted without proper measurements.

Sending Messages

All data in messages sent between Erlang processes is copied, except for refc binaries and literals on the same Erlang node.

When a message is sent to a process on another Erlang node, it is first encoded to the Erlang External Format before being sent through a TCP/IP socket. The receiving Erlang node decodes the message and distributes it to the correct process.

Receiving messages

The cost of receiving messages depends on how complicated the receive expression is. A simple expression that matches any message is very cheap because it retrieves the first message in the message queue:

 handle_msg(Message)
end.]]>

However, this is not always convenient: we can receive a message that we do not know how to handle at this point, so it is common to only match the messages we expect:

 handle_msg(Message)
end.]]>

While this is convenient it means that the entire message queue must be searched until it finds a matching message. This is very expensive for processes with long message queues, so we have added an optimization for the common case of sending a request and waiting for a response shortly after:


        erlang:demonitor(MRef, [flush]),
        handle_reply(Reply);
    {'DOWN', MRef, _, _, Reason} ->
        handle_error(Reason)
end.]]>

Since the compiler knows that the reference created by monitor/2 cannot exist before the call (since it is a globally unique identifier), and that the receive only matches messages that contain said reference, it will tell the emulator to search only the messages that arrived after the call to monitor/2.

The above is a simple example where one is but guaranteed that the optimization will take, but what about more complicated code?

Option recv_opt_info

Use the recv_opt_info option to have the compiler print information about receive optimizations. It can be given either to the compiler or erlc:

or passed through an environment variable:

Notice that recv_opt_info is not meant to be a permanent option added to your Makefiles, because all messages that it generates cannot be eliminated. Therefore, passing the option through the environment is in most cases the most practical approach.

The warnings look as follows:

To make it clearer exactly what code the warnings refer to, the warnings in the following examples are inserted as comments after the clause they refer to, for example:


%% efficiency_guide.erl:194: Warning: INFO: not a selective receive, this is always fast
receive
    Message -> handle_msg(Message)
end.

%% DO NOT, unless Tag is known to be a suitable reference: see
%% cross_function_receive/0 further down.
selective_receive(Tag, Message) ->
%% efficiency_guide.erl:200: Warning: NOT OPTIMIZED: all clauses do not match a suitable reference
receive
    {Tag, Message} -> handle_msg(Message)
end.

%% DO
optimized_receive(Process, Request) ->
%% efficiency_guide.erl:206: Warning: OPTIMIZED: reference used to mark a message queue position
    MRef = monitor(process, Process),
    Process ! {self(), MRef, Request},
    %% efficiency_guide.erl:208: Warning: OPTIMIZED: matches reference created by monitor/2 at efficiency_guide.erl:206
    receive
        {MRef, Reply} ->
        erlang:demonitor(MRef, [flush]),
        handle_reply(Reply);
    {'DOWN', MRef, _, _, Reason} ->
    handle_error(Reason)
    end.

%% DO
cross_function_receive() ->
    %% efficiency_guide.erl:218: Warning: OPTIMIZED: reference used to mark a message queue position
    Ref = make_ref(),
    %% efficiency_guide.erl:219: Warning: INFO: passing reference created by make_ref/0 at efficiency_guide.erl:218
    cross_function_receive(Ref).

cross_function_receive(Ref) ->
    %% efficiency_guide.erl:222: Warning: OPTIMIZED: all clauses match reference in function parameter 1
    receive
        {Ref, Message} -> handle_msg(Message)
    end.]]>

Literal Pool

Constant Erlang terms (hereafter called literals) are kept in literal pools; each loaded module has its own pool. The following function does not build the tuple every time it is called (only to have it discarded the next time the garbage collector was run), but the tuple is located in the module's literal pool:


    element(M, {31,28,31,30,31,30,31,31,30,31,30,31}).]]>

If a literal, or a term that contains a literal, is inserted into an Ets table, it is copied. The reason is that the module containing the literal can be unloaded in the future.

When a literal is sent to another process, it is not copied. When a module holding a literal is unloaded, the literal will be copied to the heap of all processes that hold references to that literal.

There also exists a global literal pool that is managed by the persistent_term module.

By default, 1 GB of virtual address space is reserved for all literal pools (in BEAM code and persistent terms). The amount of virtual address space reserved for literals can be changed by using the +MIscs option when starting the emulator.

Here is an example how the reserved virtual address space for literals can be raised to 2 GB (2048 MB):

    erl +MIscs 2048

Loss of Sharing

An Erlang term can have shared subterms. Here is a simple example:

Shared subterms are not preserved in the following cases:

When a term is sent to another process When a term is passed as the initial process arguments in the spawn call When a term is stored in an Ets table

That is an optimization. Most applications do not send messages with shared subterms.

The following example shows how a shared subterm can be created:

kilo_byte/1 creates a deep list. If list_to_binary/1 is called, the deep list can be converted to a binary of 1024 bytes:

1> byte_size(list_to_binary(efficiency_guide:kilo_byte())).
1024

Using the erts_debug:size/1 BIF, it can be seen that the deep list only requires 22 words of heap space:

2> erts_debug:size(efficiency_guide:kilo_byte()).
22

Using the erts_debug:flat_size/1 BIF, the size of the deep list can be calculated if sharing is ignored. It becomes the size of the list when it has been sent to another process or stored in an Ets table:

3> erts_debug:flat_size(efficiency_guide:kilo_byte()).
4094

It can be verified that sharing will be lost if the data is inserted into an Ets table:

4> T = ets:new(tab, []).
#Ref<0.1662103692.2407923716.214181>
5> ets:insert(T, {key,efficiency_guide:kilo_byte()}).
true
6> erts_debug:size(element(2, hd(ets:lookup(T, key)))).
4094
7> erts_debug:flat_size(element(2, hd(ets:lookup(T, key)))).
4094

When the data has passed through an Ets table, erts_debug:size/1 and erts_debug:flat_size/1 return the same value. Sharing has been lost.

It is possible to build an experimental variant of the runtime system that will preserve sharing when copying terms by giving the --enable-sharing-preserving option to the configure script.

SMP Emulator

The emulator takes advantage of a multi-core or multi-CPU computer by running several Erlang scheduler threads (typically, the same as the number of cores).

To gain performance from a multi-core computer, your application must have more than one runnable Erlang process most of the time. Otherwise, the Erlang emulator can still only run one Erlang process at the time.

Benchmarks that appear to be concurrent are often sequential. The estone benchmark, for example, is entirely sequential. So is the most common implementation of the "ring benchmark"; usually one process is active, while the others wait in a receive statement.