Motivation:
We have found out that ByteBufUtil.indexOf can be inefficient for substring search on
ByteBuf, both in terms of algorithm complexity (worst case O(needle.readableBytes *
haystack.readableBytes)), and in constant factor (esp. on Composite buffers).
With implementation of more performant search algorithms we have seen improvements on
the order of magnitude.
Modifications:
This change introduces three search algorithms:
1. Knuth Morris Pratt - classical textbook algorithm, a good default choice.
2. Bit mask based algorithm - stable performance on any input, but limited to maximum
search substring (the needle) length of 64 bytes.
3. Aho–Corasick - worse performance and higher memory consumption than [1] and [2], but
it supports multiple substring (the needles) search simultaneously, by inspecting every
byte of the haystack only once.
Each algorithm processes every byte of underlying buffer only once, they are implemented
as ByteProcessor.
Result:
Efficient search algorithms with linear time complexity available in Netty (I will share
benchmark results in a comment on a PR).
Motivation:
PoolChunk.usage() method has non-trivial computations. It is used currently in hot path methods invoked when an allocation and de-allocation are happened.
The idea is to replace usage() output comparison against percent thresholds by Chunk.freeBytes plain comparison against absolute thresholds. In such way the majority of computations from the threshold conditions are moved to init logic.
Modifications:
Replace PoolChunk.usage() conditions in PoolChunkList with equivalent conditions for PoolChunk.freeBytes()
Result:
Improve performance of allocation and de-allocation of ByteBuf from normal size cache pool
Motivation:
decodeHexNibble can be a lot faster using a lookup table
Modifications:
decodeHexNibble is made faster by using a lookup table
Result:
decodeHexNibble is faster
Motivation:
Currently, characters are appended to the encoded string char-by-char even when no encoding is needed. We can instead separate out codepath that appends the entire string in one go for better `StringBuilder` allocation performance.
Modification:
Only go into char-by-char loop when finding a character that requires encoding.
Result:
The results aren't so clear with noise on my hot laptop - the biggest impact is on long strings, both to reduce resizes of the buffer and also to reduce complexity of the loop. I don't think there's a significant downside though for the cases that hit the slow path.
After
```
Benchmark Mode Cnt Score Error Units
QueryStringEncoderBenchmark.longAscii thrpt 6 1.406 ± 0.069 ops/us
QueryStringEncoderBenchmark.longAsciiFirst thrpt 6 0.046 ± 0.001 ops/us
QueryStringEncoderBenchmark.longUtf8 thrpt 6 0.046 ± 0.001 ops/us
QueryStringEncoderBenchmark.shortAscii thrpt 6 15.781 ± 0.949 ops/us
QueryStringEncoderBenchmark.shortAsciiFirst thrpt 6 3.171 ± 0.232 ops/us
QueryStringEncoderBenchmark.shortUtf8 thrpt 6 3.900 ± 0.667 ops/us
```
Before
```
Benchmark Mode Cnt Score Error Units
QueryStringEncoderBenchmark.longAscii thrpt 6 0.444 ± 0.072 ops/us
QueryStringEncoderBenchmark.longAsciiFirst thrpt 6 0.043 ± 0.002 ops/us
QueryStringEncoderBenchmark.longUtf8 thrpt 6 0.047 ± 0.001 ops/us
QueryStringEncoderBenchmark.shortAscii thrpt 6 16.503 ± 1.015 ops/us
QueryStringEncoderBenchmark.shortAsciiFirst thrpt 6 3.316 ± 0.154 ops/us
QueryStringEncoderBenchmark.shortUtf8 thrpt 6 3.776 ± 0.956 ops/us
```
Motivation:
In Java, it is almost always at least slower to use `ByteBuffer` than `byte[]` without pooling or I/O. `QueryStringDecoder` can use `byte[]` with arguably simpler code.
Modification:
Replace `ByteBuffer` / `CharsetDecoder` with `byte[]` and `new String`
Result:
After
```
Benchmark Mode Cnt Score Error Units
QueryStringDecoderBenchmark.noDecoding thrpt 6 5.612 ± 2.639 ops/us
QueryStringDecoderBenchmark.onlyDecoding thrpt 6 1.393 ± 0.067 ops/us
QueryStringDecoderBenchmark.mixedDecoding thrpt 6 1.223 ± 0.048 ops/us
```
Before
```
Benchmark Mode Cnt Score Error Units
QueryStringDecoderBenchmark.noDecoding thrpt 6 6.123 ± 0.250 ops/us
QueryStringDecoderBenchmark.onlyDecoding thrpt 6 0.922 ± 0.159 ops/us
QueryStringDecoderBenchmark.mixedDecoding thrpt 6 1.032 ± 0.178 ops/us
```
I notice #6781 switched from an array to `ByteBuffer` but I can't find any motivation for that in the PR. Unit tests pass fine with an array and we get a reasonable speed bump.
Motivation
JMH 1.22 was released recently, we might as well use the latest when
running benchmarks.
Summary of changes:
https://mail.openjdk.java.net/pipermail/jmh-dev/2019-November/002879.html
Modifications
Update jmh dependencies in microbench module from version 1.21 to 1.22.
Result
Benchmarks run using latest JMH
Motivation
Currently when future tasks are scheduled via EventExecutors from a
different thread, at least two allocations are performed - the
ScheduledFutureTask wrapping the to-be-run task, and a Runnable wrapping
the action to add to the scheduled task priority queue. The latter can
be avoided by incorporating this logic into the former.
Modification
- When scheduling or cancelling a future task from outside the event
loop, enqueue the task itself rather than wrapping in a Runnable
- Have ScheduledFutureTask#run first verify the task's deadline has
passed and if not add or remove it from the scheduledTaskQueue depending
on its cancellation state
- Add new outside-event-loop benchmarks to ScheduleFutureTaskBenchmark
Result
Fewer allocations when scheduling/cancelling future tasks
Motivation
Currently a static AtomicLong is used to allocate a unique id whenever a
task is scheduled to any event loop. This could be a source of
contention if delayed tasks are scheduled at a high frequency and can be
easily avoided by having a non-volatile id counter per queue.
Modifications
- Replace static AtomicLong ScheduledFutureTask#nextTaskId with a long
field in AbstractScheduledExecutorService
- Set ScheduledFutureTask#id based on this when adding the task to the
queue (in event loop) instead of at construction time
- Add simple benchmark
Result
Less contention / cache-miss possibility when scheduling future tasks
Before:
Benchmark (num) Mode Cnt Score Error Units
scheduleLots 100000 thrpt 20 346.008 ± 21.931 ops/s
Benchmark (num) Mode Cnt Score Error Units
scheduleLots 100000 thrpt 20 654.824 ± 22.064 ops/s
Motivation:
Netty homepage(netty.io) serves both "http" and "https".
It's recommended to use https than http.
Modification:
I changed from "http://netty.io" to "https://netty.io"
Result:
No effects.
Motivation:
The previous used maxHeaderListSize was too low which resulted in exceptions during the benchmark run:
```
io.netty.handler.codec.http2.Http2Exception: Header size exceeded max allowed size (8192)
at io.netty.handler.codec.http2.Http2Exception.connectionError(Http2Exception.java:103)
at io.netty.handler.codec.http2.Http2Exception.headerListSizeError(Http2Exception.java:188)
at io.netty.handler.codec.http2.Http2CodecUtil.headerListSizeExceeded(Http2CodecUtil.java:231)
at io.netty.handler.codec.http2.HpackDecoder$Http2HeadersSink.finish(HpackDecoder.java:545)
at io.netty.handler.codec.http2.HpackDecoder.decode(HpackDecoder.java:132)
at io.netty.handler.codec.http2.HpackDecoderBenchmark.decode(HpackDecoderBenchmark.java:85)
at io.netty.handler.codec.http2.generated.HpackDecoderBenchmark_decode_jmhTest.decode_thrpt_jmhStub(HpackDecoderBenchmark_decode_jmhTest.java:120)
at io.netty.handler.codec.http2.generated.HpackDecoderBenchmark_decode_jmhTest.decode_Throughput(HpackDecoderBenchmark_decode_jmhTest.java:83)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.openjdk.jmh.runner.BenchmarkHandler$BenchmarkTask.call(BenchmarkHandler.java:453)
at org.openjdk.jmh.runner.BenchmarkHandler$BenchmarkTask.call(BenchmarkHandler.java:437)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.lang.Thread.run(Thread.java:748)
```
Also we should ensure we only use ascii for header names.
Modifications:
Just use Integer.MAX_VALUE as limit
Result:
Be able to run benchmark without exceptions
Motivation:
Some methods that either override others or are implemented as part of implementation an interface did miss the `@Override` annotation
Modifications:
Add missing `@Override`s
Result:
Code cleanup
Motivation:
SpotJMHBugs reports that accumulating a value as a way of eliding dead code
elimination may be inadvisable, as discussed in
`JMHSample_34_SafeLooping::measureWrong_2`. Change the test so that it consumes
the response with `Blackhole::consume` instead.
Modifications:
- Replace addition of results with explicit `blackhole.consume()` call
Result:
Tests work as before, but with different benchmark numbers.
Motivation:
Some JMH benchmarks need additional explanations to motivate
specific code choices.
Modifications:
Introduced comment to explai why calling BlackHole::consume
in a loop is not always the right choice for some benchmark.
Result:
The relevant method shows a comment that warn about changing
the code to introduce BlackHole::consume in the loop.
Motivation:
Resolve the issue highlighted by SpotJMHBugs that the creation of the RecyclableArrayList may be elided by the JIT since the result isn't consumed or returned.
Modifications:
Return the result of `list.recycle()` so that the list isn't elided.
Result:
The JMH benchmark shows a change in performance indicating that the prior results of this may be unsound.
Motivation:
The wakeup logic in EpollEventLoop is overly complex
Modification:
* Simplify the race to wakeup the loop
* Dont let the event loop wake up itself (it's already awake!)
* Make event loop check if there are any more tasks after preparing to
sleep. There is small window where the non-eventloop writers can issue
eventfd writes here, but that is okay.
Result:
Cleaner wakeup logic.
Benchmarks:
```
BEFORE
Benchmark Mode Cnt Score Error Units
EpollSocketChannelBenchmark.executeMulti thrpt 20 408381.411 ± 2857.498 ops/s
EpollSocketChannelBenchmark.executeSingle thrpt 20 157022.360 ± 1240.573 ops/s
EpollSocketChannelBenchmark.pingPong thrpt 20 60571.704 ± 331.125 ops/s
Benchmark Mode Cnt Score Error Units
EpollSocketChannelBenchmark.executeMulti thrpt 20 440546.953 ± 1652.823 ops/s
EpollSocketChannelBenchmark.executeSingle thrpt 20 168114.751 ± 1176.609 ops/s
EpollSocketChannelBenchmark.pingPong thrpt 20 61231.878 ± 520.108 ops/s
```
Motivation
Pipeline handlers are free to "take control" of input buffers if they have singular refcount - in particular to mutate their raw data if non-readonly via discarding of read bytes, etc.
However there are various places (primarily unit tests) where a wrapped byte-array buffer is passed in and the wrapped array is assumed not to change (used after the wrapped buffer is passed to EmbeddedChannel.writeInbound()). This invalid assumption could result in unexpected errors, such as those exposed by #8931.
Modifications
Anywhere that the data passed to writeInbound() might be used again, ensure that either:
- A copy is used rather than wrapping a shared byte array, or
- The buffer is otherwise protected from modification by making it read-only
For the tests, copying is preferred since it still allows the "mutating" optimizations to be exercised.
Results
Avoid possible errors when pipeline assumes it has full control of input buffer.
Motivation:
Results are just wrong for small delays.
Modifications:
Switching to AvarageTime avoid to rely on OS nanoTime granularity.
Result:
Uncontended low delay results are not reliable
Motivation:
Invoking ChannelHandlers is not free and can result in some overhead when the ChannelPipeline becomes very long. This is especially true if most handlers will just forward the call to the next handler in the pipeline. When the user extends Channel*HandlerAdapter we can easily detect if can just skip the handler and invoke the next handler in the pipeline directly. This reduce the overhead of dispatch but also reduce the call-stack in many cases.
This backports https://github.com/netty/netty/pull/8723 and https://github.com/netty/netty/pull/8987 to 4.1
Modifications:
Detect if we can skip the handler when walking the pipeline.
Result:
Reduce overhead for long pipelines.
Benchmark (extraHandlers) Mode Cnt Score Error Units
DefaultChannelPipelineBenchmark.propagateEventOld 4 thrpt 10 267313.031 ± 9131.140 ops/s
DefaultChannelPipelineBenchmark.propagateEvent 4 thrpt 10 824825.673 ± 12727.594 ops/s
