diff --git a/docs/langdives/Java/ThreadPoolTuning.md b/docs/langdives/Java/ThreadPoolTuning.md index 684b0e0..e24cdcd 100644 --- a/docs/langdives/Java/ThreadPoolTuning.md +++ b/docs/langdives/Java/ThreadPoolTuning.md @@ -2,27 +2,25 @@ Thread pool configuration is critical for optimizing the performance of your applications. Poorly configured thread pools can lead to problems such as CPU starvation, thread contention, memory exhaustion, or poor resource utilization. In this Article, we’ll dive deep into CPU-bound vs I/O-bound tasks, explore how to determine optimal thread pool sizes, and discuss key considerations such as queue types and rejection policies. ---- - ## **CPU vs I/O Bound Tasks** When configuring thread pools, it is essential to classify your tasks as CPU-bound or I/O-bound, as this distinction guides the number of threads your pool should maintain. ### **CPU-Bound Tasks** -Tasks that perform intensive computations (e.g., mathematical calculations, data processing, encoding), and here limiting factor is the **CPU core availability**. So its better to avoid context switching overhead by keeping the number of threads close to the available CPU cores. +Tasks that perform intensive computations (e.g., mathematical calculations, data processing, encoding), and here limiting factor is the CPU core availability. So its better to avoid context switching overhead by keeping the number of threads close to the available CPU cores. ```java title="Optimal Thread Pool Size for CPU-Bound Tasks" int coreCount = Runtime.getRuntime().availableProcessors(); ExecutorService cpuBoundPool = Executors.newFixedThreadPool(coreCount); ``` -!!! note - If more threads than CPU cores are running, threads will compete for CPU cycles, causing **context switching**, which adds overhead. +!!! note "Choosing count for CPU Bound Tasks" + If more threads than CPU cores are running, threads will compete for CPU cycles, causing context switching, which adds overhead. ``` Optimal Threads = Number of Cores ``` -???+ tip "When to use ?" +!!! tip "When to use ?" - Data crunching (e.g., scientific calculations). - Image or video processing. - Encryption/decryption tasks. @@ -30,69 +28,54 @@ ExecutorService cpuBoundPool = Executors.newFixedThreadPool(coreCount); ### **I/O-Bound Tasks** - Tasks that spend most of the time **waiting** for I/O operations (e.g., network, database, file I/O). and here the limiting factor is the time spent **waiting on I/O**. So it's better to use **more threads** than the number of cores to ensure that idle CPU cycles are used efficiently while waiting for I/O. + Tasks that spend most of the time waiting for I/O operations (e.g., network, database, file I/O). and here the limiting factor is the time spent waiting on I/O. So it's better to use more threads than the number of cores to ensure that idle CPU cycles are used efficiently while waiting for I/O. ```java title="Optimal Thread Pool Size for I/O-Bound Tasks" int coreCount = Runtime.getRuntime().availableProcessors(); int optimalThreads = coreCount * 2 + 1; ExecutorService ioBoundPool = Executors.newFixedThreadPool(optimalThreads); ``` -!!! note - Since the tasks spend significant time waiting for I/O, more threads can be created to make sure the **CPU is not idle** while other threads wait for input/output operations. +!!! note "Choosing count for I/O Bound Tasks" + Since the tasks spend significant time waiting for I/O, more threads can be created to make sure the CPU is not idle while other threads wait for input/output operations. ``` Optimal Threads = Number of Cores * (1 + Wait Time / Compute Time) ``` -???+ tip "When to use ?" + For example if a thread spends 70% of the time waiting on I/O, and only 30% performing work then + ``` + Optimal Threads = 4 * (1 + 0.7 / 0.3) = 12 + ``` + +!!! tip "When to use ?" - Web servers handling multiple HTTP requests. - Database query processing. - File upload/download tasks. - ---- + ## **Queues for ThreadPoolExecutor** -Choosing the right work queue is crucial for memory management and task scheduling. The queue holds **tasks waiting to be executed** when all threads are busy. +Choosing the right work queue is crucial for memory management and task scheduling. The queue holds tasks waiting to be executed when all threads are busy. ### **Unbounded Queue** -A queue with **no size limit**, but if too many tasks are submitted, it can lead to memory exhaustion (out-of-memory errors). +A queue with no size limit, but if too many tasks are submitted, it can lead to memory exhaustion (out-of-memory errors). ```java title="LinkedBlockingQueue" BlockingQueue queue = new LinkedBlockingQueue<>(); ``` -???+ tip "When to use ?" - Suitable only if you expect tasks to **complete quickly** and the queue will not grow indefinitely. +!!! tip "When to use ?" + Suitable only if you expect tasks to complete quickly and the queue will not grow indefinitely. ### **Bounded Queue** - A queue with a **fixed size limit**, it prevents unbounded memory usage, and If the queue is full, tasks will be **rejected** or handled based on a rejection policy. + A queue with a fixed size limit, it prevents unbounded memory usage, and If the queue is full, tasks will be rejected or handled based on a rejection policy. ```java title="ArrayBlockingQueue" BlockingQueue queue = new ArrayBlockingQueue<>(10); ``` -???+ tip "When to use ?" - Ideal for **controlled environments** where you want to cap the number of waiting tasks. - ---- +!!! tip "When to use ?" + Ideal for controlled environments where you want to cap the number of waiting tasks. -## **Thread Pool Size Tuning** - -``` title="For CPU-Bound Tasks" -Optimal Threads = Number of Cores -``` - -``` title="For I/O-Bound Tasks" -Optimal Threads = Number of Cores * (1 + Wait Time / Compute Time) -``` - -???+ example - If a thread spends 70% of the time waiting on I/O, and only 30% performing work: - ``` - Optimal Threads = 4 * (1 + 0.7 / 0.3) = 12 - ``` - ---- ## **Rejection Policies** @@ -126,7 +109,6 @@ When the task queue is full and the pool is at its maximum size, the `ThreadPool new ThreadPoolExecutor.DiscardOldestPolicy(); ``` ---- ## **Monitoring Thread Pools** @@ -138,7 +120,7 @@ Monitoring thread pools ensures that your configuration is correct and performin - **Rejected Tasks**: Track rejected tasks to see if the pool is overwhelmed. - **Average Task Time**: Measure how long tasks take to execute. -???+ example "Example: Monitoring Active Threads" +??? example "Monitoring Active Threads Example" ```java ThreadPoolExecutor executor = new ThreadPoolExecutor(2, 4, 30, TimeUnit.SECONDS, new ArrayBlockingQueue<>(2)); @@ -148,13 +130,12 @@ Monitoring thread pools ensures that your configuration is correct and performin System.out.println("Completed Tasks: " + executor.getCompletedTaskCount()); ``` ---- ## **Dynamic Thread Pool Adjustment** Sometimes, you may need to adjust the pool size at runtime to respond to changing workloads. -???+ example "Example: Adjusting Thread Pool Size Dynamically" +??? example "Adjusting Thread Pool Size Dynamically Example" ```java ThreadPoolExecutor executor = new ThreadPoolExecutor(2, 4, 30, TimeUnit.SECONDS, new ArrayBlockingQueue<>(10)); @@ -164,17 +145,13 @@ Sometimes, you may need to adjust the pool size at runtime to respond to changin executor.setMaximumPoolSize(6); ``` ---- ## **Best Practices** -- For **CPU-bound tasks**, set the size close to the number of CPU cores. -```java -int poolSize = Runtime.getRuntime().availableProcessors(); -ExecutorService executor = Executors.newFixedThreadPool(poolSize); -``` -- For **I/O-bound tasks**, use more threads than the number of cores. +- For CPU-bound tasks, set the size close to the number of CPU cores. + +- For I/O-bound tasks, use more threads than the number of cores. - Use bounded queues to prevent memory issues.