bcc-funcinterval - Man Page
Time interval between the same function, tracepoint as a histogram.
funcinterval [-h] [-p PID] [-i INTERVAL] [-d DURATION] [-T] [-u] [-m] [-v] pattern
This tool times interval between the same function as a histogram.
eBPF/bcc is very suitable for platform performance tuning. By funclatency, we can profile specific functions to know how latency this function costs. However, sometimes performance drop is not about the latency of function but the interval between function calls. funcinterval is born for this purpose.
This tool uses in-kernel eBPF maps for storing timestamps and the histogram, for efficiency.
WARNING: This uses dynamic tracing of (what can be many) functions, an activity that has had issues on some kernel versions (risk of panics or freezes). Test, and know what you are doing, before use.
Since this uses BPF, only the root user can use this tool.
CONFIG_BPF and bcc.
pattern Function name. -h Print usage message.
- -p PID
Trace this process ID only.
- -i INTERVAL
Print output every interval seconds.
- -d DURATION
Total duration of trace, in seconds.
Include timestamps on output.
Output histogram in microseconds.
Output histogram in milliseconds.
Print the BPF program (for debugging purposes).
- Time the interval of do_sys_open() kernel function as a histogram:
# funcinterval do_sys_open
- Time the interval of xhci_ring_ep_doorbell(), in microseconds:
# funcinterval -u xhci_ring_ep_doorbell
- Time the interval of do_nanosleep(), in milliseconds
# funcinterval -m do_nanosleep
- Output every 5 seconds, with timestamps:
# funcinterval -mTi 5 vfs_read
- Time process 181 only:
# funcinterval -p 181 vfs_read
- Time the interval of mm_vmscan_direct_reclaim_begin tracepoint:
# funcinterval t:vmscan:mm_vmscan_direct_reclaim_begin
- Time the interval of c:malloc used by top every 3 seconds:
# funcinterval -p `pidof -s top` -i 3 c:malloc
- Time /usr/local/bin/python main function:
# funcinterval /usr/local/bin/python:main
How many calls fell into this range
An ASCII bar chart to visualize the distribution (count column)
This traces kernel functions and maintains in-kernel timestamps and a histogram, which are asynchronously copied to user-space. While this method is very efficient, the rate of kernel functions can also be very high (>1M/sec), at which point the overhead is expected to be measurable. Measure in a test environment and understand overheads before use. You can also use funccount to measure the rate of kernel functions over a short duration, to set some expectations before use.
This is from bcc.
Also look in the bcc distribution for a companion _examples.txt file containing example usage, output, and commentary for this tool.
Unstable - in development.