on-cpu 和 off-cpu
可能遇到的一个常见问题是哪些 CPU 在运行线程，将运行多久。此问题可以通过使用 on-cpu 和 off-cpu 探测器在系统范围内轻松回答，如下例所示：
sched:::on-cpu
{
self->ts = timestamp;
}
sched:::off-cpu
/self->ts/
{
@[cpu] = quantize(timestamp - self->ts);
self->ts = 0;
}
运行上面的脚本将会生成与以下示例类似的输出：
# dtrace -s ./where.d
dtrace: script './where.d' matched 5 probes
^C
0
value ------------- Distribution ------------- count
2048 | 0
4096 |@@ 37
8192 |@@@@@@@@@@@@@ 212
16384 |@ 30
32768 | 10
65536 |@ 17
131072 | 12
262144 | 9
524288 | 6
1048576 | 5
2097152 | 1
4194304 | 3
8388608 |@@@@ 75
16777216 |@@@@@@@@@@@@ 201
33554432 | 6
67108864 | 0
1
value ------------- Distribution ------------- count
2048 | 0
4096 |@ 6
8192 |@@@@ 23
16384 |@@@ 18
32768 |@@@@ 22
65536 |@@@@ 22
131072 |@ 7
262144 | 5
524288 | 2
1048576 | 3
2097152 |@ 9
4194304 | 4
8388608 |@@@ 18
16777216 |@@@ 19
33554432 |@@@ 16
67108864 |@@@@ 21
134217728 |@@ 14
268435456 | 0
|
以上输出显示，在 CPU 1 中，线程运行的时间小于 100 微秒，或者约 10 毫秒。两组数据之间的显著差异显示在直方图中。或许您还想了解哪些 CPU 在运行某个特定进程。同样可以使用 on-cpu 和 off-cpu 探测器来回答此问题。以下脚本显示哪些 CPU 运行指定的应用程序超过 10 秒：
#pragma D option quiet
dtrace:::BEGIN
{
start = timestamp;
}
sched:::on-cpu
/execname == $$1/
{
self->ts = timestamp;
}
sched:::off-cpu
/self->ts/
{
@[cpu] = sum(timestamp - self->ts);
self->ts = 0;
}
profile:::tick-1sec
/++x == 10/
{
exit(0);
}
dtrace:::END
{
printf("CPU distribution of imapd over %d seconds:\n\n",
(timestamp - start) / 1000000000);
printf("CPU microseconds\n--- ------------\n");
normalize(@, 1000);
printa("%3d %@d\n", @);
}
在大型邮件服务器上运行以上脚本并指定 IMAP（Internet Message Access Protocol，Internet 消息访问协议）守护进程将生成与以下示例类似的输出：
# dtrace -s ./whererun.d imapd CPU distribution of imapd over 10 seconds: CPU microseconds --- ------------ 15 10102 12 16377 21 25317 19 25504 17 35653 13 41539 14 46669 20 57753 22 70088 16 115860 23 127775 18 160517 |
Solaris 在选择要运行线程的 CPU 时会考虑线程已休眠的时间：休眠时间不足的线程往往不会迁移。可使用 off-cpu 和 on-cpu 探测器来观察此行为：
sched:::off-cpu
/curlwpsinfo->pr_state == SSLEEP/
{
self->cpu = cpu;
self->ts = timestamp;
}
sched:::on-cpu
/self->ts/
{
@[self->cpu == cpu ?
"sleep time, no CPU migration" : "sleep time, CPU migration"] =
lquantize((timestamp - self->ts) / 1000000, 0, 500, 25);
self->ts = 0;
self->cpu = 0;
}
运行以上脚本约 30 秒将会生成与以下示例类似的输出：
# dtrace -s ./howlong.d
dtrace: script './howlong.d' matched 5 probes
^C
sleep time, CPU migration
value -------------- Distribution ------------ count
< 0 | 0
0 |@@@@@@@ 6838
25 |@@@@@ 4714
50 |@@@ 3108
75 |@ 1304
100 |@ 1557
125 |@ 1425
150 | 894
175 |@ 1526
200 |@@ 2010
225 |@@ 1933
250 |@@ 1982
275 |@@ 2051
300 |@@ 2021
325 |@ 1708
350 |@ 1113
375 | 502
400 | 220
425 | 106
450 | 54
475 | 40
>= 500 |@ 1716
sleep time, no CPU migration
value -------------- Distribution ------------ count
< 0 | 0
0 |@@@@@@@@@@@@ 58413
25 |@@@ 14793
50 |@@ 10050
75 | 3858
100 |@ 6242
125 |@ 6555
150 | 3980
175 |@ 5987
200 |@ 9024
225 |@ 9070
250 |@@ 10745
275 |@@ 11898
300 |@@ 11704
325 |@@ 10846
350 |@ 6962
375 | 3292
400 | 1713
425 | 585
450 | 201
475 | 96
>= 500 | 3946
|
示例输出显示非迁移的出现次数大大超过迁移的出现次数。而且，休眠时间越长，发生迁移的可能性越大。100 毫秒子范围中的分布明显不同，但因为休眠时间变长，所以看起来很相似。此结果指示，一但超出特定阈值，在做出调度决策时就不会考虑休眠时间。
使用 off-cpu 和 on-cpu 的最后示例说明如何使用这些探测器和 pr_stype 字段来确定线程休眠的原因和时间：
sched:::off-cpu
/curlwpsinfo->pr_state == SSLEEP/
{
/*
* We're sleeping. Track our sobj type.
*/
self->sobj = curlwpsinfo->pr_stype;
self->bedtime = timestamp;
}
sched:::off-cpu
/curlwpsinfo->pr_state == SRUN/
{
self->bedtime = timestamp;
}
sched:::on-cpu
/self->bedtime && !self->sobj/
{
@["preempted"] = quantize(timestamp - self->bedtime);
self->bedtime = 0;
}
sched:::on-cpu
/self->sobj/
{
@[self->sobj == SOBJ_MUTEX ? "kernel-level lock" :
self->sobj == SOBJ_RWLOCK ? "rwlock" :
self->sobj == SOBJ_CV ? "condition variable" :
self->sobj == SOBJ_SEMA ? "semaphore" :
self->sobj == SOBJ_USER ? "user-level lock" :
self->sobj == SOBJ_USER_PI ? "user-level prio-inheriting lock" :
self->sobj == SOBJ_SHUTTLE ? "shuttle" : "unknown"] =
quantize(timestamp - self->bedtime);
self->sobj = 0;
self->bedtime = 0;
}
运行以上脚本若干秒将会生成与以下示例类似的输出：
# dtrace -s ./whatfor.d
dtrace: script './whatfor.d' matched 12 probes
^C
kernel-level lock
value -------------- Distribution ------------ count
16384 | 0
32768 |@@@@@@@@ 3
65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 11
131072 |@@ 1
262144 | 0
preempted
value -------------- Distribution ------------ count
16384 | 0
32768 | 4
65536 |@@@@@@@@ 408
131072 |@@@@@@@@@@@@@@@@@@@@@@ 1031
262144 |@@@ 156
524288 |@@ 116
1048576 |@ 51
2097152 | 42
4194304 | 16
8388608 | 15
16777216 | 4
33554432 | 8
67108864 | 0
semaphore
value -------------- Distribution ------------ count
32768 | 0
65536 |@@ 61
131072 |@@@@@@@@@@@@@@@@@@@@@@@@ 553
262144 |@@ 63
524288 |@ 36
1048576 | 7
2097152 | 22
4194304 |@ 44
8388608 |@@@ 84
16777216 |@ 36
33554432 | 3
67108864 | 6
134217728 | 0
268435456 | 0
536870912 | 0
1073741824 | 0
2147483648 | 0
4294967296 | 0
8589934592 | 0
17179869184 | 1
34359738368 | 0
shuttle
value -------------- Distribution ------------ count
32768 | 0
65536 |@@@@@ 2
131072 |@@@@@@@@@@@@@@@@ 6
262144 |@@@@@ 2
524288 | 0
1048576 | 0
2097152 | 0
4194304 |@@@@@ 2
8388608 | 0
16777216 | 0
33554432 | 0
67108864 | 0
134217728 | 0
268435456 | 0
536870912 | 0
1073741824 | 0
2147483648 | 0
4294967296 |@@@@@ 2
8589934592 | 0
17179869184 |@@ 1
34359738368 | 0
condition variable
value -------------- Distribution ------------ count
32768 | 0
65536 | 122
131072 |@@@@@ 1579
262144 |@ 340
524288 | 268
1048576 |@@@ 1028
2097152 |@@@ 1007
4194304 |@@@ 1176
8388608 |@@@@ 1257
16777216 |@@@@@@@@@@@@@@ 4385
33554432 | 295
67108864 | 157
134217728 | 96
268435456 | 48
536870912 | 144
1073741824 | 10
2147483648 | 22
4294967296 | 18
8589934592 | 5
17179869184 | 6
34359738368 | 4
68719476736 | 0
|
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