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Fix scalability issue due to checkcast on context's invoke operations #12806

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merged 5 commits into from
Sep 27, 2022

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franz1981
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Motivation:

ChannelDuplexHandler can implements both ChannelOutboundHandler and ChannelInboundHandler causing a scalability issue due to checkcast due to https://bugs.openjdk.org/browse/JDK-8180450

Modifications:

Peeling-off invoke methods turning the checkcast vs interfaces into an instanceof vs ChannelDuplexHandler, saving the scalability issue to happen. Sadly, if users manually implements both ChannelOutboundHandler and ChannelInboundHandler without extending ChannelDuplexHandler the fix won't be enough.

Result:

Scalable duplex channel handler operations.

Motivation:

ChannelDuplexHandler can implements both ChannelOutboundHandler and ChannelInboundHandler
causing a scalability issue due to checkcast due to https://bugs.openjdk.org/browse/JDK-8180450

Modifications:

Peeling-off invoke methods turning the checkcast vs interfaces into an instanceof
vs ChannelDuplexHandler, saving the scalability issue to happen.
Sadly, if users manually implements both ChannelOutboundHandler and ChannelInboundHandler
without extending ChannelDuplexHandler the fix won't be enough.

Result:

Scalable duplex channel handler operations.
@franz1981
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franz1981 commented Sep 15, 2022

In theory this is already working @normanmaurer @chrisvest :
in our labs, in many tests I'm getting this level of improvement

4.5 M req/sec -> 5.8 M req/sec

And flamegraphs looks so much better

image

to

image

and the same for the outbound side too:

image

to

image

In short, no weird costs (that was costing as much has http decoding/encoding) while firing/traversing the channel pipeline
This is going to improve not just http but everyone that's using duplex channel handlers, but it has some limits, and I'm opened to suggestions here; that's why is still in draft despite being ready to be reviewed.

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Closing #12591 because this one was the proper fix and root cause.
Similar to #12708 but on checkcast bytecode

@franz1981
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FYI @doom369

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franz1981 commented Sep 15, 2022

FYI given that head/tail element of the pipeline are concrete class with high probability of being observed, it seems that adding checks vs them won't help that much because the JIT is quite capable of guarding for the "frequent" cases without making us to change any line of code, but I'm opened to change this and add explicit equality check(s) too (not using any instanceof), if it makes sense and not relies on internal JDK counters for this.

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FYI given that head/tail element of the pipeline are concrete class with high probability of being observed, it seems that adding checks vs them won't help that much because the JIT is quite capable of guarding for the "frequent" cases without making us to change any line of code, but I'm opened to change this and add explicit equality check(s) too (not using any instanceof), if it makes sense and not relies on internal JDK counters for this.

I agree

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doom369 commented Sep 15, 2022

it seems that adding checks vs them won't help that much because the JIT is quite capable of guarding for the "frequent" cases without making us to change any line of code

Agree. However, from the other side - you never know when and if a certain JIT optimization will kick in. That's, I would say, the main problem with JIT. You can't predict it and thus you can't rely on it. So the only real option is to profile under the specific conditions that fit your use case. Also, let's not forget that JIT is not free as well, especially on the server start.

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franz1981 commented Sep 15, 2022

Re the head/tail instance checks I have tried doing it manually by hitting different probabilities to match what the JIT decide for they bytecode MethodData and it wasn't bringing any visible improvement.
If I can distill a JMH bench to have fun with this we can explore that option too, but consider that's beyond the scope of this change that's merely patching the scalability issue (still not completely solved as mentioned in the commit msg).

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Restarted the build because of #12809

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@normanmaurer Running benchmarks again on this version (shouldn't be a problem TBH, but better be safe...)

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numbers on the CI are strange - I'm investigating if it's due this last commit

@franz1981 franz1981 marked this pull request as draft September 16, 2022 14:19
@chrisvest
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@franz1981 Ping me when it's ready for review again.

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@franz1981 is it also true that we don't have this issue in netty 5 anymore as there is only ChannelHandler ?

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Yep @normanmaurer it shouldn't be a problem anymore but better have a proper reproducer and verify it...
In the meantime, I am working with my team to stabilize the CI we used to detect this; do you have anything on Apple/at home suitable to try it ?

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normanmaurer commented Sep 18, 2022 via email

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franz1981 commented Sep 20, 2022

In the meantime we're stabilizing the perf CI with a proper system test, I've created a microbenchmark to help reproducing this;
below some numbers from my (well-tuned, noiseless but still - SIGH - no NUMA) laptop

# JMH version: 1.33
# VM version: JDK 1.8.0_345, OpenJDK 64-Bit Server VM, 25.345-b01
# VM invoker: /usr/lib/jvm/java-1.8.0-openjdk-1.8.0.345.b01-1.fc36.x86_64/jre/bin/java
# VM options: -server -dsa -da -ea:io.netty... -XX:+HeapDumpOnOutOfMemoryError -Dio.netty.leakDetection.level=disabled -Xms768m -Xmx768m -XX:MaxDirectMemorySize=768m -XX:BiasedLockingStartupDelay=0 -Djmh.executor=CUSTOM -Djmh.executor.class=io.netty.microbench.util.AbstractMicrobenchmark$HarnessExecutor
# Blackhole mode: full + dont-inline hint (default, use -Djmh.blackhole.autoDetect=true to auto-detect)

Now:

Benchmark                                                                      Mode  Cnt         Score         Error  Units
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent           thrpt   10  51122083.557 ± 2916748.927  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent                   thrpt   10  12952652.309 ±  239318.791  ops/s

while on 4.1:

Benchmark                                                                      Mode  Cnt         Score        Error  Units
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent           thrpt   10  11502465.689 ± 293861.798  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent                   thrpt   10   5264915.927 ±  18689.621  ops/s

The parallel version is using 4 physical cores (HT is disabled to save weird CPU-bound benchmarking quirks to happen).
In this PR the scalability is perfectly linear, while on 4.1 is ~50% of the expected speedup (ie ~21 M ops/sec).

Please don't compare the same test across versions, because right now we benefit from bimorphic inlining of duplex invoke calls (for this bench), while on 4.1 we have itable_stub ones + slow patch checkcast (see #12708 for more details); in the real world channel handlers perform real work and the dispatching speedup shouldn't be that evident (although present).

Below few metrics using -prof perfc2c to compare between the 2 versions:

Now, parallel:

=================================================
    Global Shared Cache Line Event Information   
=================================================
  Total Shared Cache Lines          :         56
  Load HITs on shared lines         :       1713
  Fill Buffer Hits on shared lines  :        576
  L1D hits on shared lines          :        537
  L2D hits on shared lines          :          0
  LLC hits on shared lines          :        600
  Locked Access on shared lines     :        362
  Blocked Access on shared lines    :          0
  Store HITs on shared lines        :        333
  Store L1D hits on shared lines    :        190
  Store No available memory level   :          0
  Total Merged records              :        761

And single threaded:

=================================================
    Global Shared Cache Line Event Information   
=================================================
  Total Shared Cache Lines          :         18
  Load HITs on shared lines         :        512
  Fill Buffer Hits on shared lines  :        196
  L1D hits on shared lines          :        178
  L2D hits on shared lines          :          0
  LLC hits on shared lines          :        138
  Locked Access on shared lines     :        183
  Blocked Access on shared lines    :          0
  Store HITs on shared lines        :         62
  Store L1D hits on shared lines    :         62
  Store No available memory level   :          0
  Total Merged records              :        187

Most numbers are nearly 4 times mores as expected by the benchmark parallelism, without outliers.

while on 4.1, parallel:

=================================================
    Global Shared Cache Line Event Information   
=================================================
  Total Shared Cache Lines          :         18
  Load HITs on shared lines         :     107834
  Fill Buffer Hits on shared lines  :      50613
  L1D hits on shared lines          :       8722
  L2D hits on shared lines          :          0
  LLC hits on shared lines          :      48499
  Locked Access on shared lines     :         70
  Blocked Access on shared lines    :          0
  Store HITs on shared lines        :      10127
  Store L1D hits on shared lines    :       9524
  Store No available memory level   :          0
  Total Merged records              :      37348

And single-threaded:

=================================================
    Global Shared Cache Line Event Information   
=================================================
  Total Shared Cache Lines          :         10
  Load HITs on shared lines         :        131
  Fill Buffer Hits on shared lines  :         52
  L1D hits on shared lines          :         36
  L2D hits on shared lines          :          0
  LLC hits on shared lines          :         43
  Locked Access on shared lines     :         39
  Blocked Access on shared lines    :          0
  Store HITs on shared lines        :         20
  Store L1D hits on shared lines    :         20
  Store No available memory level   :          0
  Total Merged records              :         48

It presents a very different picture, with 4X more "hits" on shared lines, sign of some form of heavy contention.

Using -prof perfnorm show indeed that loading Klass::secondary_super_cache field at

0x00007f1065356eee: mov    0x18(%rsi),%r10

is indeed getting some huge cost (although reported one instruction later due to skidding).

C2, level 4, io.netty.microbench.channel.DefaultChannelPipelineDuplexHandlerBenchmark$2::channelReadComplete, version 877 (483 bytes)


  0.11%   ↘     0x00007f1065356edc: mov    0x8(%r11),%r10d
                0x00007f1065356ee0: movabs $0x0,%rsi
  0.01%         0x00007f1065356eea: lea    (%rsi,%r10,8),%rsi
  0.03%         0x00007f1065356eee: mov    0x18(%rsi),%r10
 12.80%         0x00007f1065356ef2: movabs $0x1001331b8,%rax  ;   {metadata('io/netty/channel/ChannelInboundHandler')}
  0.01%         0x00007f1065356efc: cmp    %rax,%r10
0x00007f1065356eff: jne    0x00007f1065356f24  ;*checkcast
                                                  ; - io.netty.channel.AbstractChannelHandlerContext::invokeChannelReadComplete@11 (line 410)
                                                  ; - io.netty.channel.AbstractChannelHandlerContext::invokeChannelReadComplete@15 (line 397)
                                                  ; - io.netty.channel.AbstractChannelHandlerContext::fireChannelReadComplete@6 (line 390)
                                                  ; - io.netty.microbench.channel.DefaultChannelPipelineDuplexHandlerBenchmark$2::channelReadComplete@1 (line 50)
  0.38%    │ ↗  0x00007f1065356f01: mov    %r11,%rsi
  0.05%    │ │  0x00007f1065356f04: mov    0x8(%rsp),%rdx
  0.38%    │ │  0x00007f1065356f09: movabs $0xffffffffffffffff,%rax
           │ │  0x00007f1065356f13: callq  0x00007f1065046020  ; OopMap{[0]=Oop [8]=Oop off=440}
           │ │                                                ;*invokeinterface channelReadComplete
           │ │                                                ; - io.netty.channel.AbstractChannelHandlerContext::invokeChannelReadComplete@15 (line 410)
           │ │                                                ; - io.netty.channel.AbstractChannelHandlerContext::invokeChannelReadComplete@15 (line 397)
           │ │                                                ; - io.netty.channel.AbstractChannelHandlerContext::fireChannelReadComplete@6 (line 390)
           │ │                                                ; - io.netty.microbench.channel.DefaultChannelPipelineDuplexHandlerBenchmark$2::channelReadComplete@1 (line 50)
           │ │                                                ;   {virtual_call}
           │ │  0x00007f1065356f18: add    $0x30,%rsp
  0.03%    │ │  0x00007f1065356f1c: pop    %rbp
  0.14%    │ │  0x00007f1065356f1d: test   %eax,0x17afc0dd(%rip)        # 0x00007f107ce53000
           │ │                                                ;   {poll_return}
  0.01%    │ │  0x00007f1065356f23: retq   
  0.10%    ↘ │  0x00007f1065356f24: push   %rax
  0.02%      │  0x00007f1065356f25: mov    %rax,%rax
0x00007f1065356f28: mov    0x20(%rsi),%rdi
  0.34%      │  0x00007f1065356f2c: mov    (%rdi),%ecx
  0.35%      │  0x00007f1065356f2e: add    $0x8,%rdi
  0.01%      │  0x00007f1065356f32: test   %rax,%rax
  0.37%      │  0x00007f1065356f35: repnz scas %es:(%rdi),%rax
  2.73%      │  0x00007f1065356f38: pop    %rax
  0.72%     ╭│  0x00007f1065356f39: jne    0x00007f1065356f43
            ││  0x00007f1065356f3f: mov    %rax,0x18(%rsi)
  0.19%     ↘╰  0x00007f1065356f43: je     0x00007f1065356f01

And similarly here:

  C2, level 4, io.netty.channel.AbstractChannelHandlerContext::invokeFlush, version 870 (245 bytes) 
  
0x00007f1065359963: mov    0x8(%r10),%r11d
  0.02%     0x00007f1065359967: movabs $0x0,%rsi
            0x00007f1065359971: lea    (%rsi,%r11,8),%rsi
  0.09%     0x00007f1065359975: mov    0x18(%rsi),%r11
 12.50%     0x00007f1065359979: cmp    %rax,%r11
            0x00007f106535997c: jne    0x00007f1065359cbd  ;*checkcast
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush0@4 (line 750)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush@8 (line 742)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::flush@22 (line 728)
                                                          ; - io.netty.microbench.channel.DefaultChannelPipelineDuplexHandlerBenchmark$3::flush@1 (line 63)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush0@-1 (line 750)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush@8 (line 742)
  0.44%     0x00007f1065359982: mov    0x8(%r10),%ecx
  0.55%     0x00007f1065359986: cmp    $0x2002cac3,%ecx   ;   {metadata('io/netty/microbench/channel/DefaultChannelPipelineDuplexHandlerBenchmark$3')}
            0x00007f106535998c: je     0x00007f1065359a81
  0.15%     0x00007f1065359992: cmp    $0x2002678f,%ecx   ;   {metadata('io/netty/channel/DefaultChannelPipeline$HeadContext')}
            0x00007f1065359998: jne    0x00007f106535a07d  ;*invokeinterface flush
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush0@8 (line 750)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush@8 (line 742)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::flush@22 (line 728)
                                                          ; - io.netty.microbench.channel.DefaultChannelPipelineDuplexHandlerBenchmark$3::flush@1 (line 63)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush0@-1 (line 750)
                                                          ; - io.netty.channel.AbstractChannelHandlerContext::invokeFlush@8 (line 742)

the same costs are not present in the new version (nor the same instructions, because, as said earlier no slow path is required at all).

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@chrisvest Don't think the failures to be related to this, I've just added a microbench :(

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@franz1981 once happy please merge away :)

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Run micros to check if the new changes introduce some slowdown if compared to the original code, it seems not (that's a bit weird TBH); still investigating why

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franz1981 commented Sep 26, 2022

I've modified the benchmark to add the non-duplex use case too, to evaluate the impact of the changes in a pipeline without duplex handlers and

this PR:

Benchmark                                                            (duplex)   Mode  Cnt         Score         Error  Units
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent      true  thrpt   10  49167774.688 ± 9011369.821  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent     false  thrpt   10  15178977.152 ±  177359.042  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent              true  thrpt   10  12486509.977 ± 1266693.174  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent             false  thrpt   10   6821677.651 ±   35249.835  ops/s

while on 4.1:

Benchmark                                                            (duplex)   Mode  Cnt         Score        Error  Units
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent      true  thrpt   10  11350799.728 ± 340965.400  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent     false  thrpt   10  15069688.346 ± 817875.159  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent              true  thrpt   10   5239643.540 ± 107509.862  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent             false  thrpt   10   6989526.337 ± 468902.190  ops/s

duplex = true case is getting the expected scalability improvement, as shown earlier, but I see something strange (not a regression, actually, but a weird behaviour) for the duplex = false one instead. Investigating

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franz1981 commented Sep 26, 2022

@normanmaurer @chrisvest I'm happy I've parked this till now: by accident (adding the duplex = false benchmark case)
i've discovered probably another scalability issue (!):

1 thread:

=================================================
    Global Shared Cache Line Event Information   
=================================================
  Total Shared Cache Lines          :         14
  Load HITs on shared lines         :        213
  Fill Buffer Hits on shared lines  :         77
  L1D hits on shared lines          :         83
  L2D hits on shared lines          :          0
  LLC hits on shared lines          :         53
  Locked Access on shared lines     :         88
  Blocked Access on shared lines    :          0
  Store HITs on shared lines        :         25
  Store L1D hits on shared lines    :         25
  Store No available memory level   :          0
  Total Merged records              :         68

4 threads:

=================================================
  
    Global Shared Cache Line Event Information   
=================================================
  Total Shared Cache Lines          :         27
  Load HITs on shared lines         :      93735
  Fill Buffer Hits on shared lines  :      62446
  L1D hits on shared lines          :      19229
  L2D hits on shared lines          :          1
  LLC hits on shared lines          :      12059
  Locked Access on shared lines     :         77
  Blocked Access on shared lines    :          0
  Store HITs on shared lines        :      10304
  Store L1D hits on shared lines    :       9087
  Store No available memory level   :          0
  Total Merged records              :      20216

And this is not using any duplex handler.
I hope this to be a benchmark only issue, investigating...will update the PR

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franz1981 commented Sep 26, 2022

Argh :( found it, @doom369 was right

    final class HeadContext extends AbstractChannelHandlerContext
            implements ChannelOutboundHandler, ChannelInboundHandler {

and indeed my fix isn't able to cover with this yet, see myself in this same PR

Sadly, if users manually implements both ChannelOutboundHandler and ChannelInboundHandler without extending ChannelDuplexHandler the fix won't be enough.

usually the JIT is capable of peeling off the call-sites but sometime, nope - as this benchmark :(
Probably worth doing something for this: will add a commit tomorrow to address it

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franz1981 commented Sep 26, 2022

New results:

Benchmark                                                            (duplex)   Mode  Cnt         Score         Error  Units
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent      true  thrpt   10  60777303.572 ± 3081644.927  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.parallelPropagateEvent     false  thrpt   10  45924754.944 ±  254106.937  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent              true  thrpt   10  13987173.667 ±   74434.157  ops/s
DefaultChannelPipelineDuplexHandlerBenchmark.propagateEvent             false  thrpt   10  11225378.518 ±  191302.919  ops/s

to be compared vs #12806 (comment).
Now the scalability is correctly preserved in both cases (duplex and not duplex, addressing separately the special head case). Not reporting perfc2c output for brevity but now there are no longer weird shared cache event multipliers.

note:
reason why duplex = false is slower is because of the number of inbound handler (> 2) that makes calls to become megamorphic (the ones not inlined) and using itable_stub to dispatch to the right concrete class.

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@normanmaurer I see that despite this fix solve most of the problems, it doesn't solve all of them, see
image

and

...  HttpClientCodecWrapper implements ChannelInboundHandler, ChannelOutboundHandler

These are handlers (and I hope the list is completed) that won't be fixed by this PR and that can have some adverse scalability effect that none noticed yet; some of these are quite used too
eg SslHandler

We have then an additional way to solve this:

  • HeadContext check has still to happen because it doesn't extend any concrete type to be used to peel it off and save checkcast with interfaces to happen
  • use the adapters eg ChannelOutboundHandlerAdapter and ChannelInboundHandlerAdapter to peel-off the call-sites instead of ChannelDuplexHandler - (note: ChannelDuplexHandler extends ChannelInboundHandlerAdapter implements ChannelOutboundHandler meaning that it will still use the secondary cache field on Klass just for ChannelOutboundHandler but not for ChannelInboundHandler - decent, but not ideal)

Just accept that these specific handlers are not good and fix them with some hack
ie extends duplex and add @Skip to the methods we don't want to propagate events?

I'm opened to suggestion here @normanmaurer

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@franz1981 I think we should merge this one first and then investigate the others.

@franz1981 franz1981 marked this pull request as ready for review September 27, 2022 09:15
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I'm still running tests with type pollution on this PR, but feel free to merge without hurrying the release, so I can still add other fixes

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@normanmaurer I would like to create an issue to track all this effort; it's useful for JDK issues as well :P

@normanmaurer normanmaurer merged commit b31e7f2 into netty:4.1 Sep 27, 2022
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@franz1981 thanks a lot for the amazing work!

@andreasdc andreasdc mentioned this pull request Oct 13, 2022
franz1981 added a commit to franz1981/netty that referenced this pull request Dec 19, 2023
…tions

Motivation:

ChannelDuplexHandler can implements both ChannelOutboundHandler and ChannelInboundHandler causing a scalability issue due to checkcast due to https://bugs.openjdk.org/browse/JDK-8180450
Not only: there are different classes eg Http2ConnectionHandler, which implement them transitively, by using one of the 2 existing adapters (ChannelInboundAdapter, ChanneOutboundAdapters).
The existing change at netty#12806 was fixing only the duplex cases, but others like the above one was still affected.

Modifications:

Replace the duplex type checks with broader inbound adapter ones, given that duplex is still based on it.
Add outbound adapters type checks in addition to duplex ones.

Result:

More scalable adapters-based channel handler operations.
normanmaurer pushed a commit that referenced this pull request Dec 19, 2023
…tions (#13741)

Motivation:

ChannelDuplexHandler can implements both ChannelOutboundHandler and
ChannelInboundHandler causing a scalability issue due to checkcast due
to https://bugs.openjdk.org/browse/JDK-8180450
Not only: there are different classes eg Http2ConnectionHandler, which
implement them transitively, by using one of the 2 existing adapters
(ChannelInboundAdapter, ChanneOutboundAdapters). The existing change at
#12806 was fixing only the duplex
cases, but others like the above one was still affected.

Modifications:

Replace the duplex type checks with broader inbound adapter ones, given
that duplex is still based on it. Add outbound adapters type checks in
addition to duplex ones.

Result:

More scalable adapters-based channel handler operations.
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