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Java: I want to adjust the size of a thread pool. How can I detect either CMS collection starts, or other system-wide factors affecting available CPU?

(The specifics for this question are for a mod for Minecraft. In general, the question deals with resizing a threadpool based on system load and CPU availability).
I am coming from an Objective C background, and Apple's libdispatch (Grand Central Dispatch) for thread scheduling.
The immediate concern I have is trying to reduce the size of the threadpool when a CMS tenured collection is running. The program in question (Minecraft) only works well with CMS collections. A much less immediate, but still "of interest", is reducing the threadpool size when other programs are demanding significant CPU (specifically, either a screen recorder, or a twitch stream).
In Java, I have just found out about (deep breath):
Executors, which provide access to thread pools (both fixed size, and adjustable size), with cached thread existence (to avoid the overhead of constantly re-creating new threads, or to avoid the worry of coding threads to pause and resume based on workload),
Executor (no s), which is the generic interface for saying "Now it is time to execute this runnable()",
ExecutorService, which manages the threadpools according to Executor,
ThreadPoolExecutor, which is what actually manages the thread pool, and has the ability to say "This is the maximum number of threads to use".
Under normal operation, about 5 times a second, there will be 50 high priority, and 400 low priority operations submitted to the thread pool per user on the server. This is for high-powered machines.
What I want to do is:
Work with less-powerful machines. So, if a computer only has 2 cores, and the main program (two primary threads, plus some minor assistant threads) is already maxing out the CPU, these background tasks will be competing with the main program and the garbage collector. In this case, I don't want to reduce the number of background threads (it will probably stay at 2), but I do want to reduce how much work I schedule. So this is just "How do I detect when the work-load is going up". I suspect that this is just a case of watching the size of the work queue I use when Executors.newCachedThreadPool()
But the first problem: I can't find anything to return the size of the work queue! ThreadPoolExecutor() can return the queue, and I can ask that for a size, but newCachedThreadPool() only returns an ExecutorService, which doesn't let me query for size (or rather, I don't see how to).
If I have "enough cores", I want to tell the pool to use more threads. Ideally, enough to keep CPU usage near max. Most of the tasks that I want to run are CPU bound (disk I/O will be the exception, not the rule; concurrency blocking will also be rare). But I don't want to heavily over-schedule threads. How do I determine "enough threads" without going way over the available cores?
If, for example, screen recording (or streaming) activates, CPU core usage by other programs will go up, and then I want to reduce the number of threads; as the number of threads go down, and queue backlog goes up, I can reduce the amount of tasks I add to the queue. But I have no idea how to detect this.

I think that the best advice I / we can give is to not try to "micro-manage" the number of threads in the thread pools. Set it to sensible size that is proportional to the number of physical cores ... and leave it. By all means provide some static tuning parameters (e.g. in config files), but don't to make the system tune itself dynamically. (IMO, the chances that dynamic tuning will work better than static are ... pretty slim.)
For "real-time" streaming, your success is going to depend on the overall load and the scheduler's ability to prioritize more than the number of threads. However it is a fact that standard Java SE on a standard OS is not suited to hard real-time, so your real-time performance is liable to deteriorate badly if you push the envelope.

What is the relationship between number of CPU cores and number of threads in an app in java?

I'm new to java multi-threaded programming. The question that has came to my mind is that how many threads can I run according to the number of my CPU cores. and if I run threads more than CPU cores will it be an overhead for the machine to run the app. for example when we have a server machine which has a server software that run 2 threads(main thread + developer thread), will it be an overhead for the server when more simultaneous clients make socket connections to the server or not?
Thanks.

The number of threads a system can execute simultaneously is (of course) identical to the number of cores in the system.
The number of threads that can exist on the system is limited by the available memory (each thread requires a stack and a structure used by the OS to manage the thread), and possibly there is a limitation how many threads the OS allows (this depends on the OS architecture, some OS' may use a fixed size table and once its full no more threads can be created).
Commonly, todays computers can handle hundreds to thousands of threads.
The reason why more threads are used than cores exist in the system is: Most threads will inevitably spend much of their time waiting for some event (example: word processor waiting for user to type on keyboard). The OS manages it that threads that wait in such a manner do not consume CPU time.

Idea behind it is don't let your CPU sleep, neither load it too much that it waste most of time in thread switching.
Its helpful to check Tuning the pool size, In IBMs paper
Idea behind is, it depends on the nature of task, if its all in-memory computation tasks you can use N+1 threads (N numbers of cores (included hyper threading)).
Or
we need to do the application profiling and find out waiting time (WT) , service time (ST) for a typical request and approximately N*(1+WT/ST) number of optimal threads we can have, considering 100% utilization of CPU.

That depends on what the threads are doing. The CPU is only able to do X things at once, where X is the number of cores it has. That means X threads at most can be active at any one time - however the other threads can wait their turn and the CPU will process them at appropriate moments.
You should also consider that a lot of the time threads are waiting for a response, or waiting for data to load, or a network message to arrive, etc so are not actually trying to do anything. These idle/waiting threads have very little load on the system.

Don't worry about getting a higher number of threads than CPU cores; that is actually not in your hands, but in OS'.
Assuming the JVM maps your java threads over OS threads (which is fairly normal these days), it depends on the thread management your OS does. There you rely on how smart the kernel implementation is to get performance out of your cores.
What you must keep in mind is that your design must be sustainable. For example, application servers are built on a threadpool full of worker threads. Those threads are awaken in order to serve requests. Do you want a thread for each request? Then you will surely have a problem - requests can arrive in the thousands to the server, and that could be a problem for the kernel to manage. Actually the threadpool size should be limited (between 1 and X and easily changed even in real time), threads should get work from a concurrent queue (java gives you some excellent classes for that) and each one attend requests sequentially.
I hope that being of help

Having less threads than CPUs can mean you are not using all the CPUs in your system. Having more threads might improve throughput if CPU is your bottleneck.
Having more threads than CPU does introduce an overhead and if CPU is your bottleneck this can hurt performance. However, if network IO, is your bottleneck, this overhead is a price worth paying as it usually allows you to handle many more connections. e.g. You can have 1000 TCP connections with their own threads.

There doesn't have to be any relation. A computer can have any number of cores; a process can have any number of threads.
There are several different reasons that processes utilize threading, including:
Programming abstraction. Dividing up work and assigning each division to a unit of execution (a thread) is a natural approach to many problems. Programming patterns that utilize this approach include the reactor, thread-per-connection, and thread pool patterns. Some, however, view threads as an anti-pattern. The inimitable Alan Cox summed this up well with the quote, "threads are for people who can't program state machines."
Blocking I/O. Without threads, blocking I/O halts the whole process. This can be detrimental to both throughput and latency. In a multithreaded process, individual threads may block, waiting on I/O, while other threads make forward progress. Blocking I/O via threads is thus an alternative to asynchronous & non-blocking I/O.
Memory savings. Threads provide an efficient way to share memory yet utilize multiple units of execution. In this manner they are an alternative to multiple processes.
Parallelism. In machines with multiple processors, threads provide an efficient way to achieve true parallelism. As each thread receives its own virtualized processor and is an independently schedulable entity, multiple threads may run on multiple processors at the same time, improving a system's throughput. To the extent that threads are used to achieve parallelism—that is, there are no more threads than processors—the "threads are for people who can't program state machines" quote does not apply.
The first three bullets utilize threads with no relationship to cores. If you are using threads as a programming abstraction to handle UI elements, for example, you'll have one thread per UI element (or whatever) regardless of whether you have 1 core or 12. Similarly, if you were using threads to perform blocking I/O, you'd scale your thread count with your I/O capacity, not your processing power.
The fourth bullet, however, does relate threads to cores. If the goal of threading is parallelism, then the number of threads should scale linearly with the number of cores. For example, if you double the number of cores in a system, then you would double the number of threads in your application. This is true for cores in the logical sense—that is, including SMT.
When threading is used to achieve parallelism—and this is both a common and the best use of threading—you will often have, say, one or two threads per core. Oftentimes, applications are written so as to dynamically size thread pools off the number of available cores. A single thread per core is ideal, but applications often use a larger multiplier, such as two threads per core, due to bugs and inefficiencies in their code, such as operations that block when none should.

Best performance will be when number of cores(NOC) equals number of thread (NOT), because if NOT > NOC then processor should switch context or OS will try to do that work, which is expensive enough opperation. But you have to understand that it impossible to have NOC = NOT on Web Servers because you can't predict how much clients will be at the same time. Take a look on load balancing concept to solve this issue in best way.

Why increasing number of threads is useless?

I've been looking for the way to increase the speed of processing messages received from rabbitmq queue. The only way I've found is make more than one threads doing the same - receiving and processing. And this gave me some profit. After I created 4 threads the speed quadrupled. As I have 8-core processor I've decided to increase the number of threads to 8. But this gives no performance increasing. YourKit shows that only 50% of CPU is used. Somebody can say that my app is lightweight and so it is so, but I can say that it can't do more work than it does regardless I produce much more what to do. Why this doesn't work?

There are many different issues that can constrain the maximum speed of some application on a given system. For example, it can be limited by memory bandwidth, by Amdahl's Law effects (time needed for non-parallel code, including synchronized blocks), I/O bandwidth, and cache space.
If you want further improvement you need to do some measurements and profiling to find where the time is going, and then work on that.

The short (and not particularly helpful) answer is "overheads and bottlenecks".
For instance:
Creating threads in Java is relatively expensive. If the amount of work done by a thread isn't large, the overhead of creating the thread can out-weigh the benefits.
Context switching between threads is relatively expensive, especially when you take account of memory-related overheads such as cache misses, TLB misses. (These overheads actually hit when a native thread is assigned to a core. If the OS can somehow keep a native thread on a single core continuously (i.e. with no other threads on the same core), then it can use spinlocking ... and avoid the context switch. But the more Java threads you have, the less likely it is that the OS can do this.)
The threads may be spending a large proportion of their time waiting for I/O to complete. The I/O system's throughput or the speed / latency of some external service can be a bottleneck.
You may have contention over data structures; e.g. threads requiring exclusive access to safely read or update (say) a shared Map. If threads regularly need to wait for others to release locks, then you have a bottleneck.
Your computation may be dominated by the costs of "feeding" the threads. For example, if there is a single master thread that hands out "work" to worker threads, then the master thread's activities could be the bottleneck; i.e. it may not be able to provide enough work to keep the workers busy.
Since your tags imply that you are using a message queue, it is possible that that is the bottleneck, especially if the messages are big or the "work" done on each one is relatively small.
(Using a separate separate message queue service is liable to increase context switches, add I/O latency, add protocol overheads and so on. It's not an automatic route to performance improvement for small-scale systems.)
It is also possible that you have "hyperthreaded" cores not real cores, or that the operating system is stopping your JVM from using all cores.

If CPU or waiting for IO is your bottle neck, adding independent threads can make a big difference.
If you have a shared resource is a bottleneck, e.g. your L3 cache, your network adapter, your kernel, adding threads won't help because CPU is not the problem. In fact it can often make it worse by adding overhead.
my app is lightweight
In which case CPU is unlikely to be your issue and you are doing well to see a speed up with more than 1 CPU. Most likely you are speeding up CPU used by RabbitMQ. Ideally it should be more efficient and this shouldn't really help much. IMHO, more efficient messaging solutions don't gain much by multiple CPUs as they will not be bottlenecked on CPU.

One way or another, you're only using 4 cores. There's a lot that can stop stop you from doubling your performance by doubling your threads, but from your 4 thread success you've gotten past all that. I'm guessing there's a bug in your code to set off 8 threads and it's only firing up 4. (Even with hyperthreading, you're going to get some improvement. Even with every possible problem, you're going to get some improvement.) Otherwise, I'll go with T.J.Crowder and Stephen C: I don't think you really have 8 cores.
I'd try using different numbers of threads: 3, 5, 6. See what changes. I think you'll stumble on the problem soon enough.
To be fair to Java: if you write thread-safe code and avoid bottlenecks, it handles threads really well, as you've noticed going from one thread to 4. I've always found the overhead costs to be trivial.

Your application does not have linear speedup, and therefore, it does not have good scalability.
In order to keep increase the number of threads you need to ensure the data being handle is growing accordingly. For a fixed amount of data, increasing number of threads (and/or cores) will have a diminishing return at some point since the overhead of creating threads will outweight the thread's compute time.
Make sure to look up the following link:
Ahmdahl's law
Gustafson's law
Gustafson's law is a great counterpoint to Ahmdal's law so I highly recommend understanding that article.

Why does ScheduledThreadPoolExecutor only accept a fixed number of threads?

I may imagine some tasks scheduled to take a very long time and ScheduledThreadPoolExecutor would create additional threads for the other tasks that need to be run, until a maximum number of threads is reached.
But seems that I can only specify a fixed number of threads for the pool, why is that so ?

As the why, I don't know either. But I can imagine.
The amount of resources of a computer is limited. Not all resources can be handled concurrently either.
If multiple processes concurrently load files, they will be loaded slower than if they were being loaded sequentially (at least on a harddisk).
A processor also has limited support for handling multiple threads concurrently. At some point the OS or JVM will spend more time switching threads, than threads spend executing their code.
That is a good reason for the ScheduledThreadPoolExecutor to be designed the way it is. You can put any amount of jobs on the queue, but there are never executed more jobs at the same time than can be run efficiently. It's up to you to balance that, of course.
If your tasks are IO bound, I'd set the pool size small, and if they are CPU bound, a bit larger (32 or so). You can also make multiple ScheduledThreadPoolExecutors, one for IO bound tasks and one for CPU bound tasks.

While digging further about SchecduledThreadPoolExecutor I found this link, This link explains SchecduledThreadPoolExecutor solves many problems of Timer class. And also reason for introducing SchecduledThreadPoolExecutor was to replace Timer (due to various problems with Timer).
I think Reason for fixed number of threads passed to SchecduledThreadPoolExecutor is in one of problems this class solves. i.e.
The Timer class starts only one
thread. While it is more efficient
than creating a thread per task, it is
not an optimal solution. The optimal
solution may be to use a number of
threads between one thread for all
tasks and one thread per task. In
effect, the best solution is to place
the tasks in a pool of threads. The
number of threads in the pool should
be assignable during construction to
allow the program to determine the
optimal number of threads in the pool.
So in my opinion this is where use case for SchecduledThreadPoolExecutor is coming from. In your case, You should be able to decide optimal value depending upon tasks you plan to schedule and time these tasks takes to finish. If I have 4 long running tasks which are scheduled for same time I would prefer my pool size be greater than 4 if there are other tasks to be executed during same time. I would also prefer to seperate out long running tasks in different executor as indicated in earlier answers.
Hope this helps :)

According to Java Concurrency In Practice there are the following disadvantages of unbounded thread creation:
Thread lifecyle overhead
Thread creation and teardown are not free. Thread creation takes time, and requires some processing activity by the JVM and OS.
Resource consumption
Active threads consume system resources, especially memory. When there are more runnable threads than available processors, threads sit idle. Having many idle threads can tie up a lot of memory, putting pressure on the garbage collector, and having many threads competing for the CPUs can impose other performance costs as well. If you have enough threads to keep all the CPUs busy, creating more threads won't help and may even hurt.
Stability
There is a limit on how many threads can be created. The limit varies by platform and is affected by factors including JVM invocation parameters, the requested stack size in the Thread constructor, and limits on threads placed by the underlying operating system. When you hit htis limit, the most likely result is an OutOfMemoryError. Trying to recover from such an error is very risky; it is far easier to structur your program to avoid hitting this limit.
Up to a certain point, more threads can improve throughput, but beyond that point creating more threads just slows down your application, and creating one thread too many can cause your entire application to crash horribly. The way to stay out of danger is to place some bound on how many threads your application creates, and to test your application thoroughly to ensure that, even when this bound is reached, it does not run out of resources.
Unbounded thread creation may appear to work just fine during prototyping and development, with problems surfacing only when the application is deployed and under heavy load.

Java Threads memory explosion

I am fairly new with concurrent programming and I am learning it.
I am implementing a quick sort in Java JDK 7 (Fork Join API) to sort a list of objects (100K).
While using this recursive piece of code without using concurrency,i observe no memory explosion, everything is fine.
I just added the code to use it on multi cores (by extending the class RecursiveAction) and then the memory usage jumped very high until it reached its limits. By doing some profiling i observe a high creation rate of threads and i think its expectable.
But, is a java Thread by itself much more memory demanding or am i missing something here ?
Quicksort must requires a lot of threads but not much than regular objects.
Should I stop creating RecursiveAction Threads when i meet a threshold and then just switch to a sequential piece of code (no more threads)?
Thank you very much.

Java threads usually take 256k/512k(depeding in OS, jdk versions..) of stack space alone, by default.
You're wasting huge resources and speed if you're running more threads than you have processors/cores for a CPU intensive process such as doing quicksort, so try to not run more threads than you have cores.

Yes, switching over to sequential code is a good idea when the unit of work is in the region of ca. 10,000-100,000 operations. This is just a rule of thumb. So, for quick sort, I'd drop out to sequential execution when the size to be sorted is less than say 10-20,000 elements, depending upon the complexity of the comparison operation.
What's the size of the ForkJoinPool - usually it's set to create the same number of threads as processors, so you shouldn't be seeing too many threads. If you've manually set the parallelism to be high (say, in the hundreds or thousands) then you will see high (virtual) memory use, since each thread allocates space for the stack (256K by default on 32-bit windows and linux.)

As a rule of thumb for a CPU bound computation, once your number of threads exceeds the number of available cores, adding more threads is not going to speed things up. In fact, it will probably slow you down due to the overheads of creating the threads, the resources tied down by each thread (e.g. the thread stacks), and the cost of synchronizing.
Indeed, even if you had an infinite number of cores, it would not be worth creating threads to do small tasks. Even with thread pools and other clever tricks, if the amount of work to be done in a task is too small the overheads of using a thread will exceed any savings. (It is difficult to predict exactly where that threshold is, and it certainly depends on the nature of the task as well as platform-related factors.)

I changed my code and so far I have better results. I invoke the main Thread task in the ForkJoinPool, in the Threads, I dont create more threads if there are a lot more active threads than available cores in the ForkJoinPool.
I dont do synchronism through the join() method. As a result a parent thread will die as soon as it created its offsprings. In the main function that invoked the root task. I wait for the tasks to be completed, aka no more active threads. Its seems to work fine as the memory stays normal and i gained lots of time over a the same piece of code executed sequentially.
I am going to learn more.
Thank you all !