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Flame Graph profiler for Erlang
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README.md

eflame

Flame Graphs for Erlang. Uses erlang:trace/3 API.

screenshot

eflame2: Experimental variations of Vlad Ki's original eflame

Vlad Ki wrote (and is still maintaining) the original eflame source. Its API focuses on ease-of-use for profiling a single function call in a single process.

Scott Lystig Fritchie uses Vlad's work as a base for several experiments.

  1. Generate flame graph data for multi-process systems, e.g. the Riak database. Such flame graphs can give analysis on a process-by-process basis.

  2. Generate flame graph data based on experimental Erlang VM (virtual machine) tracing changes. When using a custom-patched Erlang VM, each function trace event requires much less CPU to generate stack trace information.

  3. Generate flame graph data based on an experimental Erlang VM change to support time-sampling, e.g. stack traces that are generated every 100 milliseconds. Time sampling, which is the base technique for tools such as gprof and by DTrace stack() and ustack(), have very low overhead when compared to the Erlang VM's function call tracing. (This method also requires a custom-patched Erlang VM.)

Example usage

Let's assume that we wish to trace all processes (including all processes that may be spawn()ed in the future inside of Riak for 10 seconds. The Riak server is under only a moderate workload, but this method can easily create 1 GByte or more of trace data, beware!

Step 0: Compile eflame and copy BEAM files to the target system.

Compile the source with:

erlc -o ebin src/*erl

Next, copy eflame.beam and eflame2.beam to someplace accessible on the target Riak machine, such as /tmp. Then run this command (and all of the following commands in this example) on the Riak console:

code:add_pathz("/tmp").

Step 0: Whenever you need a quick reference guide

Run the function eflame2:help() for a quick reference guide, whenever you need it.

Step 1: Start a workload, then start eflame2 tracing.

Get your workload running. In this example, we're using Riak. The workload could be a basho_bench test or something much simpler. Riak has got a large amount of background activity, so we want to make it pretty obvious that some work is being performed.

Whatever the workload is that you wish to profile, start it. Then, while the load is still running, use this command to capture 10 seconds of activity by all processes:

spawn(fun() ->
   io:format("Tracing started...\n"),
   eflame2:write_trace(global_calls_plus_new_procs, "/tmp/ef.test.0", all, 10*1000),
   io:format("Tracing finished!\n")
end).

For this example, we're going to do something very simple for our workload.

{ok, C} = riak:local_client().
[C:get(<<"test bucket">>, <<Key:32>>) || Key <- lists:seq(1, 25)].

We recommend that you choose a different output file for each test run; the 2nd argument names the output file.

The 3rd argument specifies which Erlang processes to trace. Valid PidSpec types for this argument are:

'all' | 'existing' | 'new' | pid() | [pid()]

Step 2: Format the binary trace data into text call stack output.

Run this:

eflame2:format_trace("/tmp/ef.test.0", "/tmp/ef.test.0.out").

This function can take several seconds to finish processing a 30 MByte input file, so please be patient. The output will look something like the following -- please wait until you see the "finished" message!

Hello, world, I'm <0.1771.0> and I'm running....
<0.1333.0> <0.180.0> <0.181.0> <0.182.0> <0.183.0> <0.184.0> <0.185.0> <0.186.0> <0.187.0> <0.188.0> <0.189.0> <0.190.0> <0.191.0> <0.192.0> <0.193.0> <0.194.0> <0.195.0> <0.177.0> <0.1509.0> <0.1510.0> <0.178.0> <0.373.0> <0.1511.0> <0.375.0> <0.1512.0> <0.377.0> <0.1513.0> <0.1514.0> <0.380.0> <0.1515.0> <0.382.0> <0.1516.0> <0.225.0> <0.243.0> <0.259.0> <0.254.0> <0.247.0> <0.242.0> <0.258.0> <0.246.0> <0.245.0> <0.244.0> <0.256.0> <0.257.0> <0.270.0> <0.265.0> <0.269.0> <0.271.0> <0.253.0> <0.240.0> <0.241.0> <0.263.0> <0.268.0> <0.264.0> <0.251.0> <0.266.0> <0.252.0> <0.239.0> <0.255.0> <0.267.0> <0.92.0> <0.91.0> <0.1517.0> <0.352.0> <0.351.0> <0.145.0> <0.1518.0> <0.1520.0> <0.1519.0> <0.385.0> <0.103.0> <0.104.0> <0.1521.0> <0.102.0>

Writing to /tmp/ef.test.0.out for 76 processes... finished           

The output file, the 2nd argument, will look something like this:

(0.1515.0);riak_core_stat_calc_proc:'-do_calc_stat/1-fun-0-'/2;folsom_metrics:get_metric_value/1 28
(0.1515.0);riak_core_stat_q:calc_stat/1 36
(0.1515.0);riak_core_stat_calc_proc:'-do_calc_stat/1-fun-0-'/2 20
(0.1515.0);erlang:apply/2 16
(0.251.0);proc_lib:init_p_do_apply/3;gen_server:loop/6;gen_server:loop/6;gen_server:loop/6;SLEEP 0
(0.251.0);proc_lib:init_p_do_apply/3;gen_server:loop/6;gen_server:loop/6 48
(0.251.0);proc_lib:init_p_do_apply/3;gen_server:loop/6;gen_server:loop/6;SLEEP 1201677
(0.251.0);proc_lib:init_p_do_apply/3;gen_server:handle_common_reply/6 35
(0.251.0);proc_lib:init_p_do_apply/3;gen_server:handle_msg/5 38

Each trace sample is a single text line. Each line is a collection of items separated by a semicolon: the first item is the Erlang PID that generated the trace event, and all other items are the Erlang function names on the call stack at that time.

Step 3 (optional): Massage the call stack output into something more convenient

Perhaps you are only interested in a single process's activity. If that's true, then don't use the all PidSpec in step #1: specify the single pid directly in the call to eflame2:write_trace().

However, if you don't know exactly what process that you're interested in, the all PidSpec can be very useful. The all PidSpec can generate a huge amount of data and create a very cluttered flame graph.

The SVG output is "click and zoom'able" when viewed inside of a Web browser such as Firefox or Safari. When you click on any flame graph box (which represents an Erlang process or an Erlang function inside of a call stack), all other call stacks will be excluded. Use the "Reset Zoom" button in the upper left corner to reset the zoome state.

Once you've identified a specific PID to examine more closely, you can use a command like this to filter out all other PIDs:

egrep "0\.251\.0.;" /tmp/ef.test.0.out > /tmp/ef.test.0.out.only-0.329.0

... and then use the filtered file in step #4 below. The result will be

Step 4: Convert text call stack output to SVG.

cat /tmp/ef.test.0.out | ./flamegraph.riak-color.pl > output.svg

Then open the output.svg file using an SVG-aware application, e.g. Firefox.

NOTE: The output of eflame2 does not require processing by the stack_to_flame.sh script.

Step 5: Variations of step #4

Only pids <0.1102.0> and <0.1104.0> ... note that the "<>" characters in the PID do not appear in the output:

egrep '0\.1102\.0|0\.1104\.0' /tmp/ef.test.0.out | \
   ./flamegraph.riak-color.pl > output.svg

Only pids <0.1102.0> and <0.1104.0> and also removing sleep time:

egrep '0\.1102\.0|0\.1104\.0' /tmp/ef.test.0.out | \
   grep -v 'SLEEP ' | \
   ./flamegraph.riak-color.pl > output.svg

Other examples are available in the 'More Examples' section below.

Step 6: Follow the tutorial in README-Riak-Example.md

For additional reading, see the Riak-centric tutorial in README-Riak-Example.md.




Vlad's original README text (from here to end of file)

Usage example: https://github.com/proger/active/commit/81e7e40c9dc5a4666742636ea4c5dfafc41508a5

> eflame:apply(normal_with_children, "stacks.out", my_module, awesome_calculation, []).
> eflame:apply(my_module, awesome_calculation, []). % same as above
> eflame:apply(fun my_module:awesome_calculation/0, []). % same as above
> eflame:apply(fun awesome_calculation/0, []). % same as above, when called in my_module.erl
> eflame:apply(normal, "stacks.out", my_module, awesome_calculation, []). % won't trace children
$ stack_to_flame.sh < stacks.out > flame.svg
$ open flame.svg

Notes

  • as stacks are collected through tracing, blocking calls are noticed and are drawn in blue

  • unlike the reference implementation, flamegraph.pl does not sort the input to preserve the order of calls (since this is possible due to current method of collecting stacks)

$ grep 0.90.0 stacks.out | deps/eflame/flamegraph.pl > flame.svg

# this invocation draws a separate flame graph for each traced process
$ for pid in $(cat stacks.out | awk -F';' '{print $1}' | uniq | tr -d '<>'); do
    grep $pid stacks.out | deps/eflame/flamegraph.pl --title="$pid" > flame_$pid.svg;
done

# you may also use stacks_to_flames.sh (uses zsh)
$ deps/eflame/stacks_to_flames.sh stacks.out

More examples

Of course you can also apply a bazillion of transformations to get a more understandable stack, for example:

$ grep 0.90.0 stacks.out | sort | uniq -c | sort -n -k1 | sort -k2 | awk '{print $2, "", $1}' > stacks.90
$ perl -pi -e 's#eflame:apply/5;rebar_core:process_commands/2;##' stacks.90
$ perl -pi -e 's#rebar_core:execute/.;##g' stacks.90
$ perl -pi -e 's#rebar_core:process_dir.?/.;##g' stacks.90
$ perl -pi -e 's#rebar_core:process_each/.;##g' stacks.90
$ perl -pi -e 's#rebar_core:run_modules\w*/.;##g' stacks.90
$ perl -pi -e 's#lists:\w+/.;##g' stacks.90
$ perl -pi -e 's#/\d+;#;#g' stacks.90
$ perl -pi -e 's#io_lib_pretty:[^;]+;##g' stacks.90
$ cat stacks.90 | sort -k1 | deps/eflame/flamegraph.pl --width=1430 > flame.svg

The following picture is a cleaned flame graph for a run of rebar compile (using active) on a project with 15 dependencies where all files are already compiled:

rebar compile cleaned flame graph

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