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https://issues.apache.org/jira/browse/ARTEMIS-3289?focusedWorklogId=600213&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-600213
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ASF GitHub Bot logged work on ARTEMIS-3289:
-------------------------------------------
Author: ASF GitHub Bot
Created on: 21/May/21 07:37
Start Date: 21/May/21 07:37
Worklog Time Spent: 10m
Work Description: franz1981 commented on pull request #3572:
URL: https://github.com/apache/activemq-artemis/pull/3572#issuecomment-845731469
Found the reason of the regression: the changes for
https://issues.apache.org/jira/browse/ARTEMIS-3290 are impacting differently
from the original runs and I'm getting again some sync check for known record
ID that slow down replica append update records.
Probably worth re-thinking
https://issues.apache.org/jira/browse/ARTEMIS-3290 to save the sync call to
happen as a whole.
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Issue Time Tracking
-------------------
Worklog Id: (was: 600213)
Time Spent: 5.5h (was: 5h 20m)
> Reduce journal appender executor Thread wakeup cost
> ---------------------------------------------------
>
> Key: ARTEMIS-3289
> URL: https://issues.apache.org/jira/browse/ARTEMIS-3289
> Project: ActiveMQ Artemis
> Issue Type: Improvement
> Reporter: Francesco Nigro
> Assignee: Francesco Nigro
> Priority: Major
> Attachments: 3289_backup.html, image-2021-05-11-09-32-15-538.png,
> main_backup.html
>
> Time Spent: 5.5h
> Remaining Estimate: 0h
>
> As mentioned in https://issues.apache.org/jira/browse/ARTEMIS-2877 one of the
> major factors that contribute to reduce the scalability of a shared-nothing
> replication setup is the thread wake-up cost of the {{JournalImpl}}'s
> {{appendExecutor}} I/O threads.
> See the flamegraph below for a busy replica while appending replicated
> journal record:
> !image-2021-05-11-09-32-15-538.png|width=966,height=313!
> The violet bars represent the CPU cycles spent to awake the Journal appender
> thread(s): despite https://issues.apache.org/jira/browse/ARTEMIS-2877 allow
> backup to batch append tasks as much as possible, it seems the signaling cost
> is still too high, if compared with the rest of replica packet processing.
> Given that the append executor is an ordered executor built on top of I/O
> thread pool, see {{ActiveMQServerImpl}}:
> {code:java}
> if (serviceRegistry.getIOExecutorService() != null) {
> this.ioExecutorFactory = new
> OrderedExecutorFactory(serviceRegistry.getIOExecutorService());
> } else {
> ThreadFactory tFactory = AccessController.doPrivileged(new
> PrivilegedAction<ThreadFactory>() {
> @Override
> public ThreadFactory run() {
> return new ActiveMQThreadFactory("ActiveMQ-IO-server-" +
> this.toString(), false, ClientSessionFactoryImpl.class.getClassLoader());
> }
> });
> this.ioExecutorPool = new ThreadPoolExecutor(0, Integer.MAX_VALUE,
> 60L, TimeUnit.SECONDS, new SynchronousQueue<Runnable>(), tFactory);
> this.ioExecutorFactory = new OrderedExecutorFactory(ioExecutorPool);
> }
> {code}
> And it's using a {{SynchronousQueue}} to submit/take new wakeup tasks, it
> worths investigate if using a different thread pool, executor or a different
> "sleeping" strategy could reduce such cost under heavy load and improve
> response time with/without replication.
> Most of the problems of the existing implementation seems related to how
> ThreadPoolExecutor + SynchrnoousQueue works in tandem with ArtemisExecutor.
> This small program print, on my machine:
> {code:java}
> public static void main(String[] args) throws InterruptedException {
> ThreadPoolExecutor executor = new ThreadPoolExecutor(0,
> Integer.MAX_VALUE, 60L, TimeUnit.SECONDS, new SynchronousQueue(), new
> ThreadFactory() {
> @Override
> public Thread newThread(Runnable r) {
> Thread t = new Thread(r);
> System.err.println("created new thread: " + t);
> return t;
> }
> });
> ExecutorFactory factory = new OrderedExecutorFactory(executor);
> ArtemisExecutor artemisExecutor = factory.getExecutor();
> ConcurrentSet<Thread> executingT = new ConcurrentHashSet<>();
> for (int j = 0; j< 100;j++) {
> for (int i = 0; i < 10; i++) {
> artemisExecutor.execute(() -> {
> executingT.add(Thread.currentThread());
> try {
> TimeUnit.MILLISECONDS.sleep(10);
> } catch (InterruptedException e) {
> e.printStackTrace();
> }
> });
> }
> Thread.sleep(100*10);
> }
> executor.shutdown();
> executor.awaitTermination(70, TimeUnit.SECONDS);
> System.out.println("Executing threads: " + executingT);
> }
> {code}
> {code:bash}
> created new thread: Thread[Thread-1,5,main]
> created new thread: Thread[Thread-2,5,main]
> created new thread: Thread[Thread-3,5,main]
> created new thread: Thread[Thread-4,5,main]
> created new thread: Thread[Thread-5,5,main]
> created new thread: Thread[Thread-6,5,main]
> created new thread: Thread[Thread-7,5,main]
> created new thread: Thread[Thread-8,5,main]
> created new thread: Thread[Thread-9,5,main]
> created new thread: Thread[Thread-10,5,main]
> Executing threads: [Thread[Thread-5,5,], Thread[Thread-10,5,],
> Thread[Thread-8,5,], Thread[Thread-3,5,], Thread[Thread-2,5,],
> Thread[Thread-1,5,], Thread[Thread-9,5,], Thread[Thread-6,5,],
> Thread[Thread-4,5,]]
> {code}
>
> Meaning that bursts of short running tasks can still create many different
> threads (and they won't use'em all too - see {{Thread[Thread-7,5,main]}})
> introducing the cost to create and awake them.
> There are cases (like the message journal) where keep reusing the same thread
> is highly beneficial and the "special" exclusive executor seems a good choice
> to express the single-threaded affinity of the appending tasks.
>
>
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