It's been a while since your last video! please share your knowledge again, you have a very good way of explanation. you might as well do udemy courses or create a paid courses on your youtube channel
Your explanations are amazing. I believe, you ARE the gift given me for all the efforts I made before by learning Java and Spring :D . Thank you a lot!
For people who don't have patience: The answer is: it depends on whether the task is CPU intensive or IO intesive. If it's CPU intensive, it is = number of cores, if it's IO bound, it is = depends on how much time the IO intensive task is eating on CPU. Usually much more than the number of cores.
Hi Defog Tech , thanks for the tutorials ! Could you make videos (even better if a playlist of tutorials) about advanced topics and real-life examples about Maven ? For example, releasing of projects with complex versioning, git/jenkins/artifactory integration etc... Any intermediate - advanced topics would be very much appreciated. Online tutorials nowadays about maven only cover very basic concepts and they are all the same (e.g. dependencies ... everyone knows about it).
Excellent 👌 explanation. Please do more videos on java concurrency. Also my suggestion is it would be great if you create videos which covers java concurrency book with your animation and explanation Thanks again
Done thanks CPU bound tasks (no blocking) pool size is number of cores 7:30 IO bound task diagram 11:30 Formula for number of cores wait time is how much time the thread is in wait state, and cpu time is how much time the thread spends executing For example, if the task executes for 1 second and 0.5 seconds of that is blocked on IO, then ideal thread count will be if we have 1 core 1(1+ (0.5/0.5)) = 2 threads What if the task blocks longer? Say total execution time 1 second but 0.8 blocked Ideal thread count = 1*(1+(0.8/0.2)) = 5
Thanks for the Video. Just curious about scenario for I/O tasks scenario if the I/O is non-blocking IO(In above Video it is assumed I/O is blocking I/O). It just appears in that case increasing the size of threadpool may not give any benefit as the thread will need not to wait for I/O in non-blocking scenario and can take up another task in meantime and even one thread (in single core machine scenario ) may suffice .
13:31 "L1/L2 etc need to be flushed during a thread switch", while it's architecture specific this is only needed for switching between processes, however if switching between different threads in the same process they share the same address space, so no flushing is needed (ignoring relevant fences). Also it the L2 cache is shared between multiple cores and wouldn't be flushed however the TLB and L1 potentially are.
Great explanation! What if we have multiple threadpool instead of just one single threadpool in an application, can each still have same coreThreadSize?
Sir, could you please make video about differences between embeded server and standalone server at performances aspect in Java ecosystem ? I love the learning more deep about that and how it takes benefit for microservice architecture
Hi I have been following your videos since few years now, and have started reading JCIP book for further clarity. Ny question is, Do programmers of bigdata field too need to understand concurrency?? Or is it handled by the latest frameworks like spark storm etc
For BigData processing I dont think understanding of Java concurrency is necessary. You might need to understand concurrency in general at data flow level, but not in-depth like these tutorials.
All time is IO time plus CPU time plus other thread time. The more thread you run the more time you’ll get scheduled for each threads overall. Instead of 1/1000 you’ll get 100/1100 all things else considered equal
Great explanation. I had a question - what happens if a method has both IO and CPU bound operations? Does IO bound operation take precedence over CPU bound operation?
I didnt fully understand. If method has sequential code it will be executed in that sequence irrespective of whether its IO or CPU bound. At a kernel level too, threads are given equal opportunity to run and I dont think IO vs CPU is a scheduling factor.
One of the best explanations for thread pooling I have seen so far which many have failed to do. It would be great if you can extend the discussion on how hyperthreading works along with thread pools.
I think you should appear sometimes in videos person talk to your students. It will surely help your channel. It's been a year You have not uploaded any videos. I think you have potential to become next java brains. I hope you start uploading as project reactor is maturing and I don't see anybody else who could teach devs write non blocking code. Or you can jump into gRPC. Thank you for for all these efforts. Start coming live turn on the super chats. Join button won't help it is more of commitment and you know commitments.
Hello Sir, your explanations r very pin point, please upload some Design patterns best practices and application level Exception hanndlings . SSL usage rest security like basic, oath , encryption realtime usage in microservices and normal projects
This advice is true if it assumes that there are no other threads running on the computer computer but of course there are thousands of threads running typically or at least hundred and so the more threads you allocate the more the scheduler gives time to your application. In addition to increasing the nice number / priority
Agreed. Though its more true during development and testing where you application is running with many others. For production though, even with containers typically the application has fixed set if resources assigned and the sharing is minimal
For IO bound tasks, we can have more threads in the pool for a fixed number of CPU cores. In real life scenarios, have you performed trial and error to arrive at the ideal count of threads, by observing the average wait time for such tasks?
Awesome explanation, just a view you may add memory usage of the task as an important parameter in the formula because it is one of the essential factor which restrict us in number of threads. Also you may add some explanation like what will happen if you try to start 1000 threads but fixed number of parallel threads are only 10. Mean will CPU keep them in memory or what would be the scenario. Other than this i felt its a very good explanation. :)
best explanation i have come across so far on threadpool and its dilema. I spent last one week reading windows via c trying to understand what you explained here in under 15 mins. Thanks a lot.
These really are excellent videos. I've been a software engineer for almost a decade now, and while I more or less understand concurrency theory for distributed systems (well, as much as anyone CAN understand it :) ), I will admit that I never really bothered learning much about low-to-mid-level multithreading. These videos are easy to follow, well presented, and provide a lot of "bang for your buck" time-wise.
Let's suppose I have hit the post api and saved the data in db via jpa ... Now I am using back button and resubmitting the request again 3 time and each times data is pushed in db ..and I don't want to insert resubmitted data in the table , could you please tell me how we can achieve this TIA 😊
you should use an idempotency key which is hash of the data being inserted, and set unique constraint within DB itself. this should not be handled at code level IMO
Extremely good explanation. Let's say I have 2 cores and I create a thread pool of size 2. That means I have the main thread plus 2 child threads = 3 threads total, right? Why isn't the main thread being taken into account in your calculations? Thanks
AFAIK, in webservers in addition to main-thread there are lot of other threads (eg: GC thread). Have used only request accepting/processing threads in this example to keep it simple.
I don't know if you realize it but you're content is great. I hope more poeple press the applaud button that supports you monetarily. Please continue making videos.
I have one confusion: how many types of thread are there ? I know there are threads related to cpu, then there are probably os threads, and then there are java threads. How do they relate to one another ?
Behind the scenes everything is a thread of same type. Every process, whether its OS utilities or applications or services, work using threads. I am sure there are commands for every OS which lets you find how many threads each process is using. Try that out for various types of applications. There are no threads related to CPU AFAIK.
@@DefogTech Thankyou for your reply Deepak. So when a processor says i9 8 core and 8 threads. That means they are saying 8 things can run parallelly on those 8 cores at at time ?
@@updownftw yes, correct. 1 thread per core. Note: There is a feature in both Intel and AMD CPUs called SMT which allows 2 threads per core, but even that is not technically concurrent, and its disabled generally due to recent vulnerabilities.
Hi, I am very new to the java concurrent programming. Your playlist have helped me a lot in understanding the basics. Thank you so much for giving such a simple explanation. I have a doubt regarding thread count calculation, suppose there is a system which need to get some large number of customer data of from DB/System (ie IO operation) and want to process, validate (ie CPU intense operation) data of each user and update the validation status back to DB/System (ie IO operation). How should I calculate/ design the thread count? Please correct me if I am wrong about the scenario. Thanks in advance.
Good question. It depends on how much time it takes for read IO operation to complete which will define rate of incoming tasks and how much time the CPU intensive operation takes which will define how many of these tasks can you run in parallel (at a time). So if CPU intensive task takes 10ms, then you can have max N of such tasks, where N = Number of CPU cores.
Process: A process is an instance of a computer program that is being executed. It contains the program code and its current activity. Depending on the operating system (OS), a process may be made up of multiple threads of execution that execute instructions concurrently. Process-based multitasking enables you to run the Java compiler at the same time that you are using a text editor. In employing multiple processes with a single CPU,context switching between various memory context is used. Each process has a complete set of its own variables. Thread: A thread is a basic unit of CPU utilization, consisting of a program counter, a stack, and a set of registers. A thread of execution results from a fork of a computer program into two or more concurrently running tasks. The implementation of threads and processes differs from one operating system to another, but in most cases, a thread is contained inside a process. Multiple threads can exist within the same process and share resources such as memory, while different processes do not share these resources. Example of threads in same process is automatic spell check and automatic saving of a file while writing. Threads are basically processes that run in the same memory context. Threads may share the same data while execution. Thread Diagram i.e. single thread vs multiple threads Task: A task is a set of program instructions that are loaded in memory.
