系统技术非业余研究

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做了将近8年数据库后，我的工作和研究方向将会延伸到虚拟化和计算相关的云服务，希望能够和大家一起进步，Happy New Year！

预祝大家玩得开心！

作为一个优秀的工程师，你其实不缺少才华，你缺少的是神一样的队友、充满挑战的世界级技术难题，和一个可以施展自己才华的大舞台。加入阿里核心系统数据库开发团队吧，你缺的这里都有。来吧，戳这里，给我们见识你的机会：http://blog.yufeng.info/job

Erlang的调度器效率非常高，大概在128核的情况下有80%的利用率，即使是这样，由于CPU和内存体系的结构的限制，调度器的实现还是有大量的锁存在。erts的实现为了避免core scale的问题，通常不会采用锁在那里傻等，而是采用更乐观的无锁算法，这样会有不少的CPU空转现象。

那么如何评估调度器的效率呢？我们可以从系统层面，比如从top看，每个调度器线程忙不忙。但是这只是表象，调度器可能在空转等锁，最靠谱的应该是把调度器真正干活的时间累计起来，比较真实的反应它的效率。

erlang从R15以后提供了调度器的利用率调查，这个函数就是：erlang:statistics(scheduler_wall_time) 。

我们来看下它的文档：

statistics(Item :: scheduler_wall_time) ->
[{SchedulerId, ActiveTime, TotalTime}] | undefined

Types:

SchedulerId = integer() >= 1
ActiveTime = TotalTime = integer() >= 0

Returns a list of tuples with {SchedulerId, ActiveTime, TotalTime}, where SchedulerId is an integer id of the scheduler, ActiveTime is the duration the scheduler has been busy, TotalTime is the total time duration since scheduler_wall_time activation. The time unit is not defined and may be subject to change between releases, operating systems and system restarts. scheduler_wall_time should only be used to calculate relative values for scheduler-utilization. ActiveTime can never exceed TotalTime.

The definition of a busy scheduler is when it is not idle or not scheduling (selecting) a process or port, meaning; executing process code, executing linked-in-driver or NIF code, executing built-in-functions or any other runtime handling, garbage collecting or handling any other memory management. Note, a scheduler may also be busy even if the operating system has scheduled out the scheduler thread.

Returns undefined if the system flag scheduler_wall_time is turned off.

The list of scheduler information is unsorted and may appear in different order between calls.

Using scheduler_wall_time to calculate scheduler utilization.

> erlang:system_flag(scheduler_wall_time, true).
false
> Ts0 = lists:sort(erlang:statistics(scheduler_wall_time)), ok.
ok
Some time later we will take another snapshot and calculate scheduler-utilization per scheduler.

> Ts1 = lists:sort(erlang:statistics(scheduler_wall_time)), ok.
ok
> lists:map(fun({{I, A0, T0}, {I, A1, T1}}) ->
{I, (A1 – A0)/(T1 – T0)} end, lists:zip(Ts0,Ts1)).
[{1,0.9743474730177548},
{2,0.9744843782751444},
{3,0.9995902361669045},
{4,0.9738012596572161},
{5,0.9717956667018103},
{6,0.9739235846420741},
{7,0.973237033077876},
{8,0.9741297293248656}]
Using the same snapshots to calculate a total scheduler-utilization.

> {A, T} = lists:foldl(fun({{_, A0, T0}, {_, A1, T1}}, {Ai,Ti}) ->
{Ai + (A1 – A0), Ti + (T1 – T0)} end, {0, 0}, lists:zip(Ts0,Ts1)), A/T.
0.9769136803764825

其中要注意的是”scheduler_wall_time is by default disabled. Use erlang:system_flag(scheduler_wall_time, true) to enable it.”。原因是运行期需要去做统计工作会影响性能。而且函数返回的每个调度器的使用情况顺序是乱的，需要排序下。

percept2提供了个percept2_sampling来帮我们可视化这个利用率, 演示如下：

我们启动percept2_sampling收集系统一分钟的数据，然后用web界面查看：

$ erl -pa percept2/ebin
Erlang R15B03 (erts-5.9.3.1) [source] [64-bit] [smp:16:16] [async-threads:0] [hipe] [kernel-poll:false]

Eshell V5.9.3.1  (abort with ^G)
1> percept2:start_webserver(8933).
{started,"rds064076",8933}
2> percept2_sampling:start([all], 60000, ".").
<0.57.0>

它的操作界面如下：

调度器的利用率效果如图：

我们可以看到3号调度器比较忙，其他的都闲的。

祝玩得开心！

旅行开阔视野。