nano | 🧬 Nano is a zero-config , no skeleton , minimal Hyperf | Router library

The solution was to change imx7d-pico-pi-m4.dtb to imx7d-pico-pi-qca-m4.dtb in the Yocto/Hardknott/technexion configuration file called pico-imx7.conf(described in the post)

JIT compilation in HotSpot JVM is 1) based on runtime profile data; 2) uses speculative optimizations.

Once the method is compiled at the maximum optimization level, HotSpot stops profiling this code, so it is never recompiled afterwards, no matter how long the code runs. (The exception is when the method needs to be deoptimized or unloaded, but it's not your case).

In the first case (SELECT_QUICK == true), the condition remaining > fBuffer1.length - fIdx is never met, and HotSpot JVM is aware of that from profiling data collected at lower tiers. So it speculatively hoists the check out of the loop, and compiles the loop body with the assumption that array index is always within bounds. After the optimization, the loop is compiled like this (in pseudocode):

The Java memory model is sequential consistency in the absence of data races (which your program doesn't have). This is very strong; it says that all reads and writes in your program form a total order, which is consistent with program order. So you can imagine that reads and writes from different threads simply get interleaved, or shuffled together, in some fashion - without changing the relative ordering of actions made from the same thread as each other.

But for this purpose, every action is a separate element in this order. So just by the mere fact that aBoolean.get() and aBoolean.compareAndSet() are two actions and not one action, it is possible for any number of other actions by other threads to take place in between them.

It doesn't matter whether those actions are part of a single statement, or different statements; or what kind of expression they appear in; or what operators (if any) are between them; or what computations the thread itself may or may not be doing around them. There is no way in which two actions can be "so close together" that nothing else can happen in between, short of replacing them by a single action defined to be atomic by the language.

At the level of the machine, a very simple way this can happen is that, since aBoolean.get() and aBoolean.compareAndSet() are almost certainly two different machine instructions, an interrupt may arrive in between them. This interrupt could cause the thread to be delayed for any amount of time, during which other threads could do anything they wish. So it is entirely possible that threads #1 and #2 are both interrupted in between their get() and compareAndSet(), and that thread #3 executes its set in the meantime.

Caution: Reasoning about how a particular machine might work is often useful for understanding why undesired behavior is possible, as in the previous paragraph. But it is not a substitute for reasoning about the formal memory model, and should not be used to try to argue that a program must have its desired behavior. Even if a particular machine you have in mind would do the right thing for your code, or you can't think of a way in which a plausible machine would fail, that does not prove that your program is correct.

So trying to say "oh, the machine will do a lock cmpxchg and so blah blah blah and everything works" isn't wise; some other machine you haven't thought of might work in a totally different fashion, that still complies with the abstract Java memory model but otherwise violates your x86-based expectations. In fact, x86 is a particularly poor example for this: for historical reasons, it provides a rather strong set of instruction-level memory ordering guarantees that many other "weakly ordered" architectures do not, and so there may be many things that Java abstractly allows but that x86 in practice won't do.

It looks like you are not specifying a key when you are sending your kafka message. By default Kafka sends a null key and your config says to use the kafka key as the aerospike key. In order to send a kafka key you need to set parse.key to true and specify what your separator will be (in the kafka producer).

see step 8 here

https://kafka-tutorials.confluent.io/kafka-console-consumer-producer-basics/kafka.html

I worked it out; the issue was that I didn't realise that when you install Passenger as a dynamic module, you still need to do the same config as with a regular install. In particular, in your nginx.conf, you need to add this to the http block:

I don't have Get-CimInstance available for testing but it should be as easy as this:

I solved it mounting GCS bucket in Cloud Run and read/write of object with the following changes:

• Dockerfile:

Sometimes this kind of issues are caused by another credential configuration.

Environment variables credential configuration takes prority over credentials config file. So in case there are present the environment variables "AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY" or "AWS_SESSION_TOKEN" these could generate issues if it were missconfigured or have been expired.

Try checking the env vars associated to AWS Credentials and removing them using the 'unset' command in linux.

Additionally, to remove env vars permanently you need to remove the lines related on configuration files like:

• /etc/environment
• /etc/profile
• ~/.profile
• ~/.bashrc

Reference:

Configuration settings and precedence