The sched provider makes available probes related to CPU scheduling. Because CPUs are the one resource that all threads must consume, the sched provider is useful for understanding systemic behavior. For example, you can use the sched provider to understand when and why threads sleep, run, change priority, or wake other threads.
The sched probes are described in the following table.
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The argument types for the sched probes are listed in the following table; the arguments are described in Figure 55, Table 55, List of sched Probes.
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Many sched probes have arguments consisting of a pointer to an lwpsinfo_t and a pointer to a psinfo_t, indicating a thread and the process containing the thread, respectively. These structures are described in detail in lwpsinfo_t and psinfo_t, respectively. For more information, see Figure 56, Table 56, List of sched Probe Arguments.
The cpuinfo_t structure defines a CPU. Arguments to both the enqueue and dequeue probes include a pointer to a cpuinfo_t. Additionally, the cpuinfo_t corresponding to the current CPU is pointed to by the curcpu variable. The definition of the cpuinfo_t structure is as follows:
typedef struct cpuinfo {
processorid_t cpu_id; /* CPU identifier */
psetid_t cpu_pset; /* processor set identifier */
chipid_t cpu_chip; /* chip identifier */
lgrp_id_t cpu_lgrp; /* locality group identifer */
processor_info_t cpu_info; /* CPU information */
} cpuinfo_t;
The cpu_id member is the processor identifier, as returned by psrinfo and p_online. For more information, see psrinfo(1M) and p_online(2) man pages.
The cpu_pset member is the processor set that contains the CPU, if any. See psrset(1M) for more details on processor sets.
The cpu_chip member is the identifier of the physical chip. Physical chips may contain several CPUs. For more information, see the psrinfo(1M) man page.
The cpu_lgrp member is the identifier of the latency group associated with the CPU. See liblgrp(3LIB) for details on latency groups.
The cpu_info member is the processor_info_t structure associated with the CPU, as returned by processor_info. For more information, see the processor_info(2) man page.
This section describes sched provider examples.
One common question you might want answered is which CPUs are running threads and for how long. You can use the on-cpu and off-cpu probes to easily answer this question on a system-wide basis as shown in the following example:
sched:::on-cpu
{
self->ts = timestamp;
}
sched:::off-cpu
/self->ts/
{
@[cpu] = quantize(timestamp - self->ts);
self->ts = 0;
}
Running the preceding script results in output similar to the following example:
# 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
The preceding output shows that on CPU 1 threads tend to run for less than 100 microseconds at a stretch, or for approximately 10 milliseconds. A noticeable gap between the two clusters of data is shown in the histogram. You also might be interested in knowing which CPUs are running a particular process. You can use the on-cpu and off-cpu probes for answering this question as well. The following script displays which CPUs run a specified application over a period of ten seconds:
#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 over %d seconds:\n\n",
(timestamp - start) / 1000000000);
printf("CPU microseconds\n--- ------------\n");
normalize(@, 1000);
printa("%3d %@d\n", @);
}
Running the preceding script on a large mail server and specifying the IMAP daemon results in output similar to the following example:
# 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
Oracle Solaris takes into account the amount of time that a thread has been sleeping when selecting a CPU on which to run the thread: a thread that has been sleeping for less time tends not to migrate. You can use the off-cpu and on-cpu probes to observe this behavior:
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;
}
Running the preceding script for approximately 30 seconds results in output similar to the following example:
# 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
The example output shows that there are many more occurrences of non-migration than migration. Also, when sleep times are longer, migrations are more likely. The distributions are noticeably different in the sub 100 millisecond range, but look very similar as the sleep times get longer. This result would seem to indicate that sleep time is not factored into the scheduling decision once a certain threshold is exceeded.
The final example using off-cpu and on-cpu shows how to use these probes along with the pr_stype field to determine why threads sleep and for how long:
sched:::off-cpu
/curlwpsinfo->pr_state == SSLEEP/
{
/*
* In sleeping state. Track the 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;
}
Running the preceding script for several seconds results in output similar to the following example:
# 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
When a CPU becomes idle, the dispatcher looks for work enqueued on other non-idle CPUs. The following example uses the dequeue probe to understand how often applications are transferred and by which CPU:
#pragma D option quiet
sched:::dequeue
/args[2]->cpu_id != -1 && cpu != args[2]->cpu_id &&
(curlwpsinfo->pr_flag & PR_IDLE)/
{
@[stringof(args[1]->pr_fname), args[2]->cpu_id] =
lquantize(cpu, 0, 100);
}
END
{
printa("%s stolen from CPU %d by:\n%@d\n", @);
}
The tail of the output from running the preceding script on a four CPU system results in output similar to the following example:
# dtrace -s ./whosteal.d
^C
...
nscd stolen from CPU 1 by:
value -------------- Distribution ------------ count
1 | 0
2 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 28
3 | 0
snmpd stolen from CPU 1 by:
value -------------- Distribution ------------ count
< 0 | 0
0 |@ 1
1 | 0
2 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 31
3 |@@ 2
4 | 0
sched stolen from CPU 1 by:
value -------------- Distribution ------------ count
< 0 | 0
0 |@@ 3
1 | 0
2 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 36
3 |@@@@ 5
4 | 0
Instead of knowing which CPUs took which work, you might want to know the CPUs on which processes and threads are waiting to run. You can use the enqueue and dequeue probes together to answer this question:
sched:::enqueue
{
a[args[0]->pr_lwpid, args[1]->pr_pid, args[2]->cpu_id] =
timestamp;
}
sched:::dequeue
/a[args[0]->pr_lwpid, args[1]->pr_pid, args[2]->cpu_id]/
{
@[args[2]->cpu_id] = quantize(timestamp -
a[args[0]->pr_lwpid, args[1]->pr_pid, args[2]->cpu_id]);
a[args[0]->pr_lwpid, args[1]->pr_pid, args[2]->cpu_id] = 0;
}
Running the preceding script for several seconds results in output similar to the following example:
# dtrace -s ./qtime.d
dtrace: script './qtime.d' matched 5 probes
^C
1
value ------------- Distribution ------------- count
1024 | 0
2048 | 10
4096 |@@@@@@@@@@@@@@@@@@@@@@@@@@ 4316
8192 |@@@@@@@ 1115
16384 |@@@ 549
32768 |@@ 337
65536 |@@ 330
131072 | 13
262144 | 6
524288 | 4
1048576 | 2
2097152 | 1
4194304 | 0
0
value ------------- Distribution ------------- count
1024 | 0
2048 | 22
4096 |@@@@@@@@@@@@@@@@ 2747
8192 |@@@@@@@ 1205
16384 |@@@@@@@@@@@@ 1942
32768 |@@@ 469
65536 |@@ 304
131072 | 28
262144 | 16
524288 | 5
1048576 | 1
2097152 | 2
4194304 | 1
8388608 | 0
Instead of looking at wait times, you might want to examine the length of the run queue over time. Using the enqueue and dequeue probes, you can set up an associative array to track the queue length:
sched:::enqueue
{
this->len = qlen[args[2]->cpu_id]++;
@[args[2]->cpu_id] = lquantize(this->len, 0, 100);
}
sched:::dequeue
/qlen[args[2]->cpu_id]/
{
qlen[args[2]->cpu_id]--;
}
Running the preceding script for approximately 30 seconds on a largely idle uniprocessor system results in output similar to the following example:
# dtrace -s ./qlen.d
dtrace: script './qlen.d' matched 5 probes
^C
0
value -------------- Distribution ------------ count
< 0 | 0
0 |@@@@@@@@@@@@@@@@@@@@@@@@@ 110626
1 |@@@@@@@@@ 41142
2 |@@ 12655
3 |@ 5074
4 | 1722
5 | 701
6 | 302
7 | 63
8 | 23
9 | 12
10 | 24
11 | 58
12 | 14
13 | 3
14 | 0
The output is roughly what you would expect for an idle system: the majority of the time that a runnable thread is enqueued, the run queue was very short, three or fewer threads in length. However, given that the system was largely idle, the exceptional data points at the bottom of the table might be unexpected. For example, why was the run queue as long as 13 runnable threads? To explore this question, you could write a D script that displays the contents of the run queue when the length of the run queue is long. This problem is complicated because D enablings cannot iterate over data structures, and therefore cannot simply iterate over the entire run queue. Even if D enablings could do so, you should avoid dependencies on the kernel's internal data structures.
For this type of script, you would enable the enqueue and dequeue probes and use both speculations and associative arrays. Whenever a thread is enqueued, the script increments the length of the queue and records the timestamp in an associative array keyed by the thread. You cannot use a thread-local variable in this case because a thread might be enqueued by another thread. The script then checks to see if the queue length exceeds the maximum. If it does, the script starts a new speculation, and records the timestamp and the new maximum. Then, when a thread is dequeued, the script compares the enqueue timestamp to the timestamp of the longest length: if the thread was enqueued before the timestamp of the longest length, the thread was in the queue when the longest length was recorded. In this case, the script speculatively traces the thread's information. Once the kernel dequeues the last thread that was enqueued at the timestamp of the longest length, the script commits the speculation data. This script is shown below:
#pragma D option quiet
#pragma D option nspec=4
#pragma D option specsize=100k
int maxlen;
int spec[int];
sched:::enqueue
{
this->len = ++qlen[this->cpu = args[2]->cpu_id];
in[args[0]->pr_addr] = timestamp;
}
sched:::enqueue
/this->len > maxlen && spec[this->cpu]/
{
/*
* There is already a speculation for this CPU. As a new record
* is set, discard the old one.
*/
discard(spec[this->cpu]);
}
sched:::enqueue
/this->len > maxlen/
{
/*
* You have a winner. Set the new maximum length and set the timestamp
* of the longest length.
*/
maxlen = this->len;
longtime[this->cpu] = timestamp;
/*
* Now start a new speculation, and speculatively trace the length.
*/
this->spec = spec[this->cpu] = speculation();
speculate(this->spec);
printf("Run queue of length %d:\n", this->len);
}
sched:::dequeue
/(this->in = in[args[0]->pr_addr]) &&
this->in <= longtime[this->cpu = args[2]->cpu_id]/
{
speculate(spec[this->cpu]);
printf(" %d/%d (%s)\n",
args[1]->pr_pid, args[0]->pr_lwpid,
stringof(args[1]->pr_fname));
}
sched:::dequeue
/qlen[args[2]->cpu_id]/
{
in[args[0]->pr_addr] = 0;
this->len = --qlen[args[2]->cpu_id];
}
sched:::dequeue
/this->len == 0 && spec[this->cpu]/
{
/*
* As you just processed the last thread that was enqueued at the time
* of longest length; commit the speculation, which by now contains
* each thread that was enqueued when the queue was longest.
*/
commit(spec[this->cpu]);
spec[this->cpu] = 0;
}
Running the preceding script on the same uniprocessor results in output similar to the following example:
# dtrace -s ./whoqueue.d Run queue of length 3: 0/0 (sched) 0/0 (sched) 101170/1 (dtrace) Run queue of length 4: 0/0 (sched) 100356/1 (Xsun) 100420/1 (xterm) 101170/1 (dtrace) Run queue of length 5: 0/0 (sched) 0/0 (sched) 100356/1 (Xsun) 100420/1 (xterm) 101170/1 (dtrace) Run queue of length 7: 0/0 (sched) 100221/18 (nscd) 100221/17 (nscd) 100221/16 (nscd) 100221/13 (nscd) 100221/14 (nscd) 100221/15 (nscd) Run queue of length 16: 100821/1 (xterm) 100768/1 (xterm) 100365/1 (fvwm2) 101118/1 (xterm) 100577/1 (xterm) 101170/1 (dtrace) 101020/1 (xterm) 101089/1 (xterm) 100795/1 (xterm) 100741/1 (xterm) 100710/1 (xterm) 101048/1 (xterm) 100697/1 (MozillaFirebird-) 100420/1 (xterm) 100394/1 (xterm) 100368/1 (xterm) ^C
The output reveals that the long run queues are due to many runnable xterm processes. This experiment coincided with a change in virtual desktop, and therefore the results are probably due to some sort of X event processing.
In enqueue and dequeue, the final example demonstrated that a burst in run queue length was due to runnable xterm processes. One hypothesis is that the observations resulted from a change in virtual desktop. You can use the wakeup probe to explore this hypothesis by determining who is waking the xterm processes, and when, as shown in the following example:
#pragma D option quiet
dtrace:::BEGIN
{
start = timestamp;
}
sched:::wakeup
/stringof(args[1]->pr_fname) == "xterm"/
{
@[execname] = lquantize((timestamp - start) / 1000000000, 0, 10);
}
profile:::tick-1sec
/++x == 10/
{
exit(0);
}
To investigate the hypothesis, run the preceding script, waiting roughly five seconds, and switch your virtual desktop exactly once. If the burst of runnable xterm processes is due to switching the virtual desktop, the output should show a burst of wakeup activity at the five second mark.
# dtrace -s ./xterm.d
Xsun
value -------------- Distribution ------------ count
4 | 0
5 |@ 1
6 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 32
7 | 0
The output does show that the X server is waking xterm processes, clustered around the time that you switched virtual desktops. If you wanted to understand the interaction between the X server and the xterm processes, you could aggregate on user stack traces when the X server fires the wakeup probe.
Understanding the performance of client/server systems like the X windowing system requires understanding the clients on whose behalf the server is doing work. This kind of question is difficult to answer with conventional performance analysis tools. However, if you have a model where a client sends a message to the server and sleeps pending the server's processing, you can use the wakeup probe to determine the client for whom the request is being performed, as shown in the following example:
self int last;
sched:::wakeup
/self->last && args[0]->pr_stype == SOBJ_CV/
{
@[stringof(args[1]->pr_fname)] = sum(vtimestamp - self->last);
self->last = 0;
}
sched:::wakeup
/execname == "Xsun" && self->last == 0/
{
self->last = vtimestamp;
}
Running the preceding script results in output similar to the following example:
dtrace -s ./xwork.d dtrace: script './xwork.d' matched 14 probes ^C xterm 9522510 soffice.bin 9912594 fvwm2 100423123 MozillaFirebird 312227077 acroread 345901577
This output reveals that much Xsun work is being done on behalf of the processes acroread, MozillaFirebird and, to a lesser degree, fvwm2. Notice that the script only examined wakeups from condition variable synchronization objects SOBJ_CV. As described in Figure 50, Table 50, proc pr_stype Values, condition variables are the type of synchronization object typically used to synchronize for reasons other than access to a shared data region. In the case of the X server, a client will wait for data in a pipe by sleeping on a condition variable.
You can additionally use the sleep probe along with the wakeup probe to understand which applications are blocking on which applications, and for how long, as shown in the following example:
#pragma D option quiet
sched:::sleep
/!(curlwpsinfo->pr_flag & PR_ISSYS) && curlwpsinfo->pr_stype == SOBJ_CV/
{
bedtime[curlwpsinfo->pr_addr] = timestamp;
}
sched:::wakeup
/bedtime[args[0]->pr_addr]/
{
@[stringof(args[1]->pr_fname), execname] =
quantize(timestamp - bedtime[args[0]->pr_addr]);
bedtime[args[0]->pr_addr] = 0;
}
END
{
printa("%s sleeping on %s:\n%@d\n", @);
}
The tail of the output from running the example script for several seconds on a system resembles the following example:
# dtrace -s ./whofor.d
^C
...
xterm sleeping on Xsun:
value -------------- Distribution ------------ count
131072 | 0
262144 | 12
524288 | 2
1048576 | 0
2097152 | 5
4194304 |@@@ 45
8388608 | 1
16777216 | 9
33554432 |@@@@@ 83
67108864 |@@@@@@@@@@@ 164
134217728 |@@@@@@@@@@ 147
268435456 |@@@@ 56
536870912 |@ 17
1073741824 | 9
2147483648 | 1
4294967296 | 3
8589934592 | 1
17179869184 | 0
fvwm2 sleeping on Xsun:
value -------------- Distribution ------------ count
32768 | 0
65536 |@@@@@@@@@@@@@@@@@@@@@@ 67
131072 |@@@@@ 16
262144 |@@ 6
524288 |@ 3
1048576 |@@@@@ 15
2097152 | 0
4194304 | 0
8388608 | 1
16777216 | 0
33554432 | 0
67108864 | 1
134217728 | 0
268435456 | 0
536870912 | 1
1073741824 | 1
2147483648 | 2
4294967296 | 2
8589934592 | 2
17179869184 | 0
34359738368 | 2
68719476736 | 0
syslogd sleeping on syslogd:
value -------------- Distribution ------------ count
17179869184 | 0
34359738368 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 3
68719476736 | 0
MozillaFirebird sleeping on MozillaFirebird:
value -------------- Distribution ------------ count
65536 | 0
131072 | 3
262144 |@@ 14
524288 | 0
1048576 |@@@ 18
2097152 | 0
4194304 | 0
8388608 | 1
16777216 | 0
33554432 | 1
67108864 | 3
134217728 |@ 7
268435456 |@@@@@@@@@@ 53
536870912 |@@@@@@@@@@@@@@ 78
1073741824 |@@@@ 25
2147483648 | 0
4294967296 | 0
8589934592 |@ 7
17179869184 | 0
You might want to understand how and why MozillaFirebird is blocking on itself. You could modify the preceding script as shown in the following example to answer this question:
#pragma D option quiet
sched:::sleep
/execname == "MozillaFirebird" && curlwpsinfo->pr_stype == SOBJ_CV/
{
bedtime[curlwpsinfo->pr_addr] = timestamp;
}
sched:::wakeup
/execname == "MozillaFirebird" && bedtime[args[0]->pr_addr]/
{
@[args[1]->pr_pid, args[0]->pr_lwpid, pid, curlwpsinfo->pr_lwpid] =
quantize(timestamp - bedtime[args[0]->pr_addr]);
bedtime[args[0]->pr_addr] = 0;
}
sched:::wakeup
/bedtime[args[0]->pr_addr]/
{
bedtime[args[0]->pr_addr] = 0;
}
END
{
printa("%d/%d sleeping on %d/%d:\n%@d\n", @);
}
Running the modified script for several seconds results in output similar to the following example:
# dtrace -s ./firebird.d
^C
100459/1 sleeping on 100459/13:
value -------------- Distribution ------------ count
262144 | 0
524288 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 1
1048576 | 0
100459/13 sleeping on 100459/1:
value -------------- Distribution ------------ count
16777216 | 0
33554432 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 1
67108864 | 0
100459/1 sleeping on 100459/2:
value -------------- Distribution ------------ count
16384 | 0
32768 |@@@@ 5
65536 |@ 2
131072 |@@@@@ 6
262144 | 1
524288 |@ 2
1048576 | 0
2097152 |@@ 3
4194304 |@@@@ 5
8388608 |@@@@@@@@ 9
16777216 |@@@@@ 6
33554432 |@@ 3
67108864 | 0
100459/1 sleeping on 100459/5:
value -------------- Distribution ------------ count
16384 | 0
32768 |@@@@@ 12
65536 |@@ 5
131072 |@@@@@@ 15
262144 | 1
524288 | 1
1048576 | 2
2097152 |@ 4
4194304 |@@@@@ 13
8388608 |@@@ 8
16777216 |@@@@@ 13
33554432 |@@ 6
67108864 |@@ 5
134217728 |@ 4
268435456 | 0
536870912 | 1
1073741824 | 0
100459/2 sleeping on 100459/1:
value -------------- Distribution ------------ count
16384 | 0
32768 |@@@@@@@@@@@@@@ 11
65536 | 0
131072 |@@ 2
262144 | 0
524288 | 0
1048576 |@@@@ 3
2097152 |@ 1
4194304 |@@ 2
8388608 |@@ 2
16777216 |@ 1
33554432 |@@@@@@ 5
67108864 | 0
134217728 | 0
268435456 | 0
536870912 |@ 1
1073741824 |@ 1
2147483648 |@ 1
4294967296 | 0
100459/5 sleeping on 100459/1:
value -------------- Distribution ------------ count
16384 | 0
32768 | 1
65536 | 2
131072 | 4
262144 | 7
524288 | 1
1048576 | 5
2097152 | 10
4194304 |@@@@@@ 77
8388608 |@@@@@@@@@@@@@@@@@@@@@@@ 270
16777216 |@@@ 43
33554432 |@ 20
67108864 |@ 14
134217728 | 5
268435456 | 2
536870912 | 1
1073741824 | 0
You can also use the sleep and wakeup probes to understand the performance of door servers such as the name service cache daemon, as shown in the following example:
sched:::sleep
/curlwpsinfo->pr_stype == SOBJ_SHUTTLE/
{
bedtime[curlwpsinfo->pr_addr] = timestamp;
}
sched:::wakeup
/execname == "nscd" && bedtime[args[0]->pr_addr]/
{
@[stringof(curpsinfo->pr_fname), stringof(args[1]->pr_fname)] =
quantize(timestamp - bedtime[args[0]->pr_addr]);
bedtime[args[0]->pr_addr] = 0;
}
sched:::wakeup
/bedtime[args[0]->pr_addr]/
{
bedtime[args[0]->pr_addr] = 0;
}
The tail of the output from running the preceding script on a large mail server resembles the following example:
imapd
value -------------- Distribution ------------ count
16384 | 0
32768 | 2
65536 |@@@@@@@@@@@@@@@@@ 57
131072 |@@@@@@@@@@@ 37
262144 | 3
524288 |@@@ 11
1048576 |@@@ 10
2097152 |@@ 9
4194304 | 1
8388608 | 0
mountd
value -------------- Distribution ------------ count
65536 | 0
131072 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 49
262144 |@@@ 6
524288 | 1
1048576 | 0
2097152 | 0
4194304 |@@@@ 7
8388608 |@ 3
16777216 | 0
sendmail
value -------------- Distribution ------------ count
16384 | 0
32768 |@ 18
65536 |@@@@@@@@@@@@@@@@@ 205
131072 |@@@@@@@@@@@@@ 154
262144 |@ 23
524288 | 5
1048576 |@@@@ 50
2097152 | 7
4194304 | 5
8388608 | 2
16777216 | 0
automountd
value -------------- Distribution ------------ count
32768 | 0
65536 |@@@@@@@@@@ 22
131072 |@@@@@@@@@@@@@@@@@@@@@@@ 51
262144 |@@ 6
524288 | 1
1048576 | 0
2097152 | 2
4194304 | 2
8388608 | 1
16777216 | 1
33554432 | 1
67108864 | 0
134217728 | 0
268435456 | 1
536870912 | 0
You might be interested in the unusual data points for automountd or the persistent data point at over one millisecond for sendmail. You can add additional predicates to the preceding script to hone in on the causes of any exceptional or anomalous.
Because Oracle Solaris is a preemptive system, higher priority threads preempt lower priority ones. Preemption can induce a significant latency bubble in the lower priority thread, so you might want to know which threads are being preempted by which other threads. The following example shows how to use the preempt and remain-cpu probes to display this information:
#pragma D option quiet
sched:::preempt
{
self->preempt = 1;
}
sched:::remain-cpu
/self->preempt/
{
self->preempt = 0;
}
sched:::off-cpu
/self->preempt/
{
/*
* If you want to preempt yourself, see who you ended up giving
* the CPU to.
*/
@[stringof(args[1]->pr_fname), args[0]->pr_pri, execname,
curlwpsinfo->pr_pri] = count();
self->preempt = 0;
}
END
{
printf("%30s %3s %30s %3s %5s\n", "PREEMPTOR", "PRI",
"PREEMPTED", "PRI", "#");
printa("%30s %3d %30s %3d %5@d\n", @);
}
Running the preceding script for several seconds on a system results in output similar to the following example:
# dtrace -s ./whopreempt.d
^C
PREEMPTOR PRI PREEMPTED PRI #
sched 60 Xsun 53 1
xterm 59 Xsun 53 1
MozillaFirebird 57 Xsun 53 1
mpstat 100 fvwm2 59 1
sched 99 MozillaFirebird 57 1
sched 60 dtrace 30 1
mpstat 100 Xsun 59 2
sched 60 Xsun 54 2
sched 99 sched 60 2
fvwm2 59 Xsun 44 2
sched 99 Xsun 44 2
sched 60 xterm 59 2
sched 99 Xsun 53 2
sched 99 Xsun 54 3
sched 60 fvwm2 59 3
sched 60 Xsun 59 3
sched 99 Xsun 59 4
fvwm2 59 Xsun 54 8
fvwm2 59 Xsun 53 9
Xsun 59 MozillaFirebird 57 10
sched 60 MozillaFirebird 57 14
MozillaFirebird 57 Xsun 44 16
MozillaFirebird 57 Xsun 54 18
Preemption is based on priorities, so you might want to observe changes in priority over time. The following example uses the change-pri probe to display this information:
sched:::change-pri
{
@[stringof(args[0]->pr_clname)] =
lquantize(args[2] - args[0]->pr_pri, -50, 50, 5);
}
The example script captures the degree to which priority is raised or lowered, and aggregates by scheduling class. Running the preceding script results in output similar to the following example:
# dtrace -s ./pri.d
dtrace: script './pri.d' matched 10 probes
^C
IA
value -------------- Distribution ------------ count
< -50 | 20
-50 |@ 38
-45 | 4
-40 | 13
-35 | 12
-30 | 18
-25 | 18
-20 | 23
-15 | 6
-10 |@@@@@@@@ 201
-5 |@@@@@@ 160
0 |@@@@@ 138
5 |@ 47
10 |@@ 66
15 |@ 36
20 |@ 26
25 |@ 28
30 | 18
35 | 22
40 | 8
45 | 11
>= 50 |@ 34
TS
value -------------- Distribution ------------ count
-15 | 0
-10 |@ 1
-5 |@@@@@@@@@@@@ 7
0 |@@@@@@@@@@@@@@@@@@@@ 12
5 | 0
10 |@@@@@ 3
15 | 0
The output shows the priority manipulation of the Interactive (IA) scheduling class. Instead of seeing priority manipulation, you might want to see the priority values of a particular process and thread over time. The following script uses the change-pri probe to display this information:
#pragma D option quiet
BEGIN
{
start = timestamp;
}
sched:::change-pri
/args[1]->pr_pid == $1 && args[0]->pr_lwpid == $2/
{
printf("%d %d\n", timestamp - start, args[2]);
}
tick-1sec
/++n == 5/
{
exit(0);
}
To see the change in priorities over time, type the following command in one window:
$ echo $$ 139208 $ while true ; do let i=0 ; done
In another window, run the script and redirect the output to a file:
# dtrace -s ./pritime.d 139208 1 > /tmp/pritime.out
You can use the file /tmp/pritime.out that is generated in the preceding example as input to plotting software to graphically display priority over time. gnuplot is a freely available plotting package that is included in the Oracle Solaris Freeware Companion CD. By default, gnuplot is installed in /opt/sfw/bin.
Oracle Solaris uses tick-based CPU accounting, in which a system clock interrupt fires at a fixed interval and attributes CPU utilization to the threads and processes running at the time of the tick. The following example shows how to use the tick probe to observe this attribution:
# dtrace -n sched:::tick'{@[stringof(args[1]->pr_fname)] = count()}'
^C
arch 1
sh 1
sed 1
echo 1
ls 1
FvwmAuto 1
pwd 1
awk 2
basename 2
expr 2
resize 2
tput 2
uname 2
fsflush 2
dirname 4
vim 9
fvwm2 10
ksh 19
xterm 21
Xsun 93
MozillaFirebird 260
The system clock frequency varies from operating system to operating system, but generally ranges from 25 hertz to 1024 hertz. The Oracle Solaris system clock frequency is adjustable, but defaults to 100 hertz.
The tick probe only fires if the system clock detects a runnable thread. To use the tick probe to observe the system clock's frequency, you must have a thread that is always runnable. In one window, create a looping shell as shown in the following example:
$ while true ; do let i=0 ; done
n another window, run the following script:
uint64_t last[int];
sched:::tick
/last[cpu]/
{
@[cpu] = min(timestamp - last[cpu]);
}
sched:::tick
{
last[cpu] = timestamp;
}
# dtrace -s ./ticktime.d dtrace: script './ticktime.d' matched 2 probes ^C 0 9883789
The minimum interval is 9.8 millisecond, which indicates that the default clock tick frequency is 10 milliseconds (100 hertz). The observed minimum is somewhat less than 10 milliseconds due to jitter.
One deficiency of tick-based accounting is that the system clock that performs accounting is often also responsible for dispatching any time-related scheduling activity. As a result, if a thread is to perform some amount of work every clock tick, that is every 10 milliseconds, the system will either over-account for the thread or under-account for the thread, depending on whether the accounting is done before or after time-related dispatching scheduling activity. In Oracle Solaris, accounting is performed before time-related dispatching. As a result, the system will under-account for threads running at regular interval. If such threads run for less than the clock tick interval, they can effectively hide behind the clock tick. The following example shows the degree to which the system has such threads:
sched:::tick,
sched:::enqueue
{
@[probename] = lquantize((timestamp / 1000000) % 10, 0, 10);
}
The output of the example script is two distributions of the millisecond offset within a ten millisecond interval, one for the tick probe and another for enqueue:
# dtrace -s ./tick.d
dtrace: script './tick.d' matched 4 probes
^C
tick
value -------------- Distribution ------------ count
6 | 0
7 |@ 3
8 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 79
9 | 0
enqueue
value -------------- Distribution ------------ count
< 0 | 0
0 |@@ 267
1 |@@ 300
2 |@@ 259
3 |@@ 291
4 |@@@ 360
5 |@@ 305
6 |@@ 295
7 |@@@@ 522
8 |@@@@@@@@@@@@ 1315
9 |@@@ 337
The output histogram named tick shows that the clock tick is firing at an 8 millisecond offset. If scheduling were not at all associated with the clock tick, the output for enqueue would be evenly spread across the ten millisecond interval. However, the output shows a spike at the same 8 millisecond offset, indicating that at least some threads in the system are being scheduled on a time basis.
You can use cpucaps-sleep and cpucaps-wakeup probes to understand the impact CPU Caps have on specific processes and threads. The following example shows how much various processes spend on wait queues:
sched:::cpucaps-sleep
{
sleep[args[1]->pr_pid] = timestamp;
}
sched:::cpucaps-wakeup
/sleep[args[1]->pr_pid]/
{
@sleeps[args[1]->pr_fname] = quantize(timestamp - sleep[args[1]->pr_pid]);
sleep[args[1]->pr_pid] = 0;
}
Running the preceding script results in output similar to the following example:
# dtrace -s
./capswait.d
dtrace: script './capswait.d' matched 2 probes
^C
exmh
value ------------- Distribution ------------- count
8388608 | 0
16777216 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 4
33554432 | 0
scan
value ------------- Distribution ------------- count
16777216 | 0
33554432 |@@@@@@@@@@@@@@@@@@@@ 1
67108864 | 0
134217728 |@@@@@@@@@@@@@@@@@@@@ 1
268435456 | 0
firefox-bin
value ------------- Distribution ------------- count
4194304 | 0
8388608 |@@ 1
16777216 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 19
33554432 |@@@@ 2
67108864 | 0
The sched provider uses DTrace's stability mechanism to describe its stabilities, as shown in the following table. For more information about the stability mechanism, see DTrace Stability Mechanisms.
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