Use the GROUP BY clause in a SELECT statement to group rows together that have the same value in one or more column, or the same computed value using expressions with any functions and operators except grouping functions. When you use a GROUP BY clause, you will get a single result row for each group of rows that have the same value for the expression given in GROUP BY.
mysql>selectcount(*), channel from wlan_client where channel >15; +----------+---------+ |count(*) | channel | +----------+---------+ |165594|44| +----------+---------+ 1rowinset (0.30 sec)
group by 整数
You can also use a single integer as the grouping expression. If you use an integer n, the results will be grouped by the nth column in the select expression.
这里是另一种用法,N代表select中的第N项,如上面的select count(), channel from wlan_client group by channel就可写成select count(), channel from wlan_client group by 2
If you have the “nowait” parameter set and there are no calls in the FIFO queue, processing immediately continues past the FIFO queue. If there are one or more calls in the queue, only one call is retrieved and processing continues past the FIFO queue after that call ends.
It is generally best to do most telephony processing in the dialplan, not in your script. The FS team has put a great deal of effort into making sofia handle many edge cases of SIP processing, so trying to do all that in your script would prove hopeless. ↩︎
So, contrary to the comment there, the load is not measured every 5s (HZ=1000 in CentOS6) but every 5.001 seconds!
Now, let’s do the math. If we add one ms every five s, how long does it take to add another full five s? In other words, what is the interference period? We need to add one ms 5000x. If we add it every five s, it takes us 25000s. Which, converted to hours, is: six hours, 56 minutes and 40 seconds. So we were slightly wrong, the spikes did not occur every seven hours.
The regular high load was really caused by launching a bunch of monitoring scripts every minute and by the fact that the load measurements slowly and slightly moves with a period of almost 7 hours.
Well, yeah. It turned out that it was really happening everywhere. But to our defense, on a much, much smaller scale. Why? First, most of our machines are much more powerful, so the spike in load is not that big and it does not trigger the threshold for alerts (it is based on load_per_core value). Second, most of the machines actually do something, so you won’t notice a small spike in load occurring every ~seven hours in the plot, as the load curve is not stable anyway. And third, the majority of the hosts only have a few collectd exec plugins configured, so the number of processes executed at one moment is significantly smaller.