netty | netty实战示例 -

The problem is the connection with the cassandra. Make sure that you've been created the keyspace-name on cassandra. After that in your project declare a Bean Configuration with the keyspace, in my case mykeyspace. You can visit https://kayaerol84.medium.com/cassandra-cluster-management-with-docker-compose-40265d9de076 for more details about setting up the keyspace.

MSK doesn't offer Kafka Connect as a service. You'll need to install this on your own computer, or on other AWS compute resources. From there, you need to install the Camel connector plugins

Your Gradle build is targeting 1.8 (Java 8).

You need to change this (or remove it) if you are using the Java records feature released in Java 16, previewed in Java 14 and in Java 15.

By default WebClient runs with a connection pool. The default settings for the pool are 500 max connections and max 1000 pending requests. You have JMeter and try to simulate 10000 but you do not specify how you distribute the load. You may need to increase the max pending requests. Have a look at this documentation and this documentation.

If you want to configure the WebClient then you need:

ActiveMQ Artemis has no default connection limit. I just wrote a quick test based on this which uses the Paho 1.2.5 MQTT client. It spun up 500 concurrent connections using both normal TCP and WebSockets. The test finished in less than 20 seconds with no errors. I'm just running this test on my laptop.

I noticed that your journal-buffer-timeout is 700000 which seems quite high which means you have a very low write speed of 1.43 writes per millisecond (i.e. a slow disk). The journal-buffer-timeout that is calculated, for example, on my laptop is 4000 which translates into a write-speed of 250 which is significantly faster than yours. My laptop is nothing special, but it does have an SSD. That said, SSDs are pretty common. If this low write-speed is indicative of the overall performance of your VM it may simply be too weak to handle the load you want. To be clear, this value isn't related directly to MQTT connections. It's just something I noticed while reviewing your configuration that may be indirect evidence of your issue.

The journal-buffer-timeout value is calculated and configured automatically when the instance is created. You can re-calculate this value later and configure it manually using the bin/artemis perf-journal command.

Ultimately, your issue looks environmental to me. I recommend you inspect your VM and network. TCP dumps may be useful to see perhaps how/why the connection is being reset. Thread dumps from the server during the time of the trouble would also be worth inspecting.

The RoutingContext object, which is used internally by the broker, is reusable. This is done for performance reasons to prevent having to re-create the RoutingContext for every routing operation no matter what. As one might guess, routing messages is a very common operation in the broker so it pays to optimize it as much as possible. Reusing the RoutingContext means fewer objects are created and thrown away which means less garbage needs to be cleaned up which means fewer pauses and better overall performance by the broker.

The fact that the previousAddress is different here from the address where the current message is going to be routed is not a problem. It just means that the context won't be re-used for this routing operation and therefore will be cleared. As the name suggests, the beforeMessageRoute method is invoked before any routing logic is performed (e.g. clearing the RoutingContext). If you inspect the RoutingContext using afterMessageRoute then you should see that it was cleared and populated with the proper details.

Message "sending" and message "routing" (both of which have plugin hooks) are related but distinct operations. A message is "sent" in response to a client operation. Sends always result in a route. However, not all routes are the results of sends. A message can be routed due to internal broker operations which do not involve a send (e.g. moving messages around a cluster, expiring a message, cancelling an undeliverable message to a dead-letter address, using a divert, etc.).

I would caution you against inspecting internal broker state (which can be subtle and nuanced) and assuming a problem exists when everything else indicates that the broker is functioning normally. In this case you said that you were "facing routing issues" and that "some message are routed from topic.private.abc.task.V1 to topic.abc.rawmessage.V1" when, in fact, there was no routing issue and messages were not actually being routed from topic.private.abc.task.V1 to topic.abc.rawmessage.V1. From what I can see everything is in fact functioning normally.

Apache Arrow utilizes a pretty similar idea of Java off-heap storage as Apache Ignite does. For Apache Arrow it means that objects like IntVector don't actually store data in their on-heap layout. They just store a reference to a buffer containing an off-heap address of a physical representation. Technically it's a long offset pointing to a chunk of memory within JVM address space.

When you restart your JVM, address space changes. But in your Apache Ignite native persistence there's a record holding an old pointer. It leads to a SIGSEGV because it's not in the JVM address anymore (in fact it doesn't even exist after a restart).

You could use Apache Arrow serialization machinery to store data permanently in Apache Ignite or even somewhere else. But in fact after that you're going to lose Apache Arrow preciousness as a fast in-memory columnar store. It was initially designed to share off-heap data across multiple data-processing solutions.

Therefore I believe that technically it could be possible to leverage Apache Ignite binary storage format. In that case a custom BinarySerializer should be implemented. After that it would be possible to use it with the Apache Arrow vector classes.

You either need to disable the dependencyConvergence check in the POM, or you need to add an entry to the section of your POM which contains the version of error_prone_annotations that you want to use.

I was able to solve this issue. Basically all your microservices should use below configuration. Here prefer-ip-address: true and fetch-registry: true is the key here.