Details
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Bug
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Status: Resolved
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Normal
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Resolution: Fixed
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None
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Normal
Description
I was trying to profile Cassandra under my workload and I kept seeing this backtrace:
epollEventLoopGroup-2-3 State: RUNNABLE CPU usage on sample: 240ms io.netty.channel.epoll.Native.epollWait0(int, long, int, int) Native.java (native) io.netty.channel.epoll.Native.epollWait(int, EpollEventArray, int) Native.java:111 io.netty.channel.epoll.EpollEventLoop.epollWait(boolean) EpollEventLoop.java:230 io.netty.channel.epoll.EpollEventLoop.run() EpollEventLoop.java:254 io.netty.util.concurrent.SingleThreadEventExecutor$5.run() SingleThreadEventExecutor.java:858 io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run() DefaultThreadFactory.java:138 java.lang.Thread.run() Thread.java:745
At fist I though that the profiler might not be able to profile native code properly, but I wen't further and I realized that most of the CPU was used by epoll_wait() calls with a timeout of zero.
Here is the output of perf on this system, which confirms that most of the overhead was with timeout == 0.
Samples: 11M of event 'syscalls:sys_enter_epoll_wait', Event count (approx.): 11594448
Overhead Trace output ◆
90.06% epfd: 0x00000047, events: 0x7f5588c0c000, maxevents: 0x00002000, timeout: 0x00000000 ▒
5.77% epfd: 0x000000b5, events: 0x7fca419ef000, maxevents: 0x00001000, timeout: 0x00000000 ▒
1.98% epfd: 0x000000b5, events: 0x7fca419ef000, maxevents: 0x00001000, timeout: 0x000003e8 ▒
0.04% epfd: 0x00000003, events: 0x2f6af77b9c00, maxevents: 0x00000020, timeout: 0x00000000 ▒
0.04% epfd: 0x0000002b, events: 0x121ebf63ac00, maxevents: 0x00000040, timeout: 0x00000000 ▒
0.03% epfd: 0x00000026, events: 0x7f51f80019c0, maxevents: 0x00000020, timeout: 0x00000000 ▒
0.02% epfd: 0x00000003, events: 0x7fe4d80019d0, maxevents: 0x00000020, timeout: 0x00000000
Running this time with perf record -ag for call traces:
# Children Self sys usr Trace output
# ........ ........ ........ ........ ....................................................................................
#
8.61% 8.61% 0.00% 8.61% epfd: 0x000000a7, events: 0x7fca452d6000, maxevents: 0x00001000, timeout: 0x00000000
|
---0x1000200af313
|
--8.61%--0x7fca6117bdac
0x7fca60459804
epoll_wait
2.98% 2.98% 0.00% 2.98% epfd: 0x000000a7, events: 0x7fca452d6000, maxevents: 0x00001000, timeout: 0x000003e8
|
---0x1000200af313
0x7fca6117b830
0x7fca60459804
epoll_wait
That looks like a lot of CPU used to wait for nothing. I'm not sure if pref reports a per-CPU percentage or a per-system percentage, but that would be still be 10% of the total CPU usage of Cassandra at the minimum.
I went further and found the code of all that: We schedule a lot of Message::Flusher with a deadline of 10 usec (5 per messages I think) but netty+epoll only support timeouts above the milliseconds and will convert everything bellow to 0.
I added some traces to netty (4.1):
diff --git a/transport-native-epoll/src/main/java/io/netty/channel/epoll/EpollEventLoop.java b/transport-native-epoll/src/main/java/io/netty/channel/epoll/EpollEventLoop.java index 909088fde..8734bbfd4 100644 --- a/transport-native-epoll/src/main/java/io/netty/channel/epoll/EpollEventLoop.java +++ b/transport-native-epoll/src/main/java/io/netty/channel/epoll/EpollEventLoop.java @@ -208,10 +208,15 @@ final class EpollEventLoop extends SingleThreadEventLoop { long currentTimeNanos = System.nanoTime(); long selectDeadLineNanos = currentTimeNanos + delayNanos(currentTimeNanos); for (;;) { - long timeoutMillis = (selectDeadLineNanos - currentTimeNanos + 500000L) / 1000000L; + long timeoutNanos = selectDeadLineNanos - currentTimeNanos + 500000L; + long timeoutMillis = timeoutNanos / 1000000L; + System.out.printf("timeoutNanos: %d, timeoutMillis: %d | deadline: %d - now: %d | hastask: %d\n", + timeoutNanos, timeoutMillis, + selectDeadLineNanos, currentTimeNanos, hasTasks() ? 1 : 0); if (timeoutMillis <= 0) { if (selectCnt == 0) { int ready = Native.epollWait(epollFd.intValue(), events, 0); + System.out.printf("ready: %d\n", ready); if (ready > 0) { return ready; }
And this gives :
timeoutNanos: 1000500000, timeoutMillis: 1000 | deadline: 2001782341816510 - now: 2001781341816510 | hastask: 0 timeoutNanos: 1000500000, timeoutMillis: 1000 | deadline: 2001782342087239 - now: 2001781342087239 | hastask: 0 timeoutNanos: 1000500000, timeoutMillis: 1000 | deadline: 2001782342166947 - now: 2001781342166947 | hastask: 0 timeoutNanos: 508459, timeoutMillis: 0 | deadline: 2001781342297987 - now: 2001781342289528 | hastask: 0 ready: 0 timeoutNanos: 508475, timeoutMillis: 0 | deadline: 2001781342357719 - now: 2001781342349244 | hastask: 0 ready: 0 timeoutNanos: 509327, timeoutMillis: 0 | deadline: 2001781342394822 - now: 2001781342385495 | hastask: 0 ready: 0 timeoutNanos: 509339, timeoutMillis: 0 | deadline: 2001781342430192 - now: 2001781342420853 | hastask: 0 ready: 0 timeoutNanos: 509510, timeoutMillis: 0 | deadline: 2001781342461588 - now: 2001781342452078 | hastask: 0 ready: 0 timeoutNanos: 509493, timeoutMillis: 0 | deadline: 2001781342495044 - now: 2001781342485551 | hastask: 0 ready: 0
The nanosecond timeout all come from eventLoop.schedule(this, 10000, TimeUnit.NANOSECONDS); in Message::Flusher.
Knowing that, I'm not sure what would be best to do, and I have a hard time understanding Message::Flusher, but to me it looks like trying to schedule less tasks would probably help and I didn't think anything obvious that could be done with netty.
Changing if (++runsWithNoWork > 5) to 2 seems to help a little bit, but that isn't really significant.
