da0hn/virtual-thread-structured-concurrency-sandbox

Java 21 Virtual Thread and Structured Concurrency Udemy Course

Java 21 Virtual Threads and Structured Concurrency

Java Threads and Scalability

• Task types
• Concurrency and Parallelism
• Non Blocking IO
• Introduce Project Loom

Task Types

%%{ init: { 'flowchart': { 'curve': 'cardinal' } } }%%
flowchart LR
    subgraph External World
        browser(("Browser"))
    end
    subgraph Typical Web Application
        application["\nWeb Application\n(Process)\n"]
        database_1[(Database 1)]
        database_2[(Database 2)]
        ms_1{{"Microservice 1\n(Process)"}}
        ms_2{{"Microservice 2\n(Process)"}}

    end
    application --> external_api
    browser -->|User Request| application
    browser -->|User Request| application
    browser -->|User Request| application
    application <--> database_1
    application <--> database_2
    application <--> ms_1
    application <--> ms_2

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Process Per Request (CGI)

flowchart LR
    web-server["Web Server\n(Process)"]
    handler-1["User 1 Handler\nCGI Script\n(Process)"]
    handler-2["User 2 Handler\nCGI Script\n(Process)"]
    handler-3["User 3 Handler\nCGI Script\n(Process)"]
    external-call["\n\n\n\n\n\n       "]
    external-call -->|User 1 Request| web-server
    external-call -->|User 2 Request| web-server
    external-call -->|User 3 Request| web-server
    web-server <-->|" (1) Start Process "| handler-1
    web-server <-->|" (2) Start Process "| handler-2
    web-server <-->|" (3) Start Process "| handler-3

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• Process is heavyweight
• Limited number of processes per machine
  • Scalability issues
  • Cannot support large number of users
• Expensive Process startup and termination time
• Difficult to share data or communicate between Processes
• FastCGI
  • Pooling of Processes
  • CGI processes are started upfront for performance

Thread Per Request

flowchart LR
    user-request["\n\n\n\n\n"]
    subgraph web-application["fa:fa-internet-explorer Web Application"]
        thread-1-start(("start"))
        thread-1-finish(("end"))
        thread-2-start(("start"))
        thread-2-finish(("end"))
        thread-3-start(("start"))
        thread-3-finish(("end"))
    end
    user-request -->|User 1 Request| web-application
    user-request -->|User 2 Request| web-application
    user-request -->|User 3 Request| web-application
    thread-1-start -->|" 1. Thread process "| thread-1-finish
    thread-2-start -->|" 2. Thread process "| thread-2-finish
    thread-3-start -->|" 3. Thread process "| thread-3-finish

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• Threads are lightweight
  • But has its own stack
• Can handle larger number of concurrent users
• Can share data or communicate between threads
• Improved Performance
  • No extra process to deal with
• Easy to understand
• Easy to debug

Concurrency and Parallelism

Concurrency

• Multiple independent tasks are making progress but may not execute at the same time
• Appearance of simultaneous execution (parallelism)
• Concurrency is about dealing with lots of things at once
• CPU time slicing

Parallelism

• Multiple dependent sub-tasks are executing at the same time
• Multiple cores needed
• No parallelism in single core

Synchronous Call

• Sequential execution of code
• Easy to understand
• Easy to debug

Asynchronous Call

• Does not wait for call to complete
• Callbacks, Futures...
• More complex to understand
• In java, user Threads

Threads and Scalability

• Default stack size 1M
  • As number of users increase, memory usage increases
• There is a max limit to the max threads
  • Depends on VM or Machine Memory
  • Much more socket connections can be supported
  • This prevents optimum scalability
• IO Bound Tasks
  • Paralyzes the OS thread for a longer time than necessary

Scalability Solutions

• {Optimized Scalable Application} + {Vertial Scaling} + {Horizontal Scaling}

Vertical Scaling

• Increase resources
• CPU, Memory, Disk Space, etc...
• Limit to scaling
• Increases cost
• Cloud Environment

Horizontal Scaling

• Increase number of Application (Instances) nodes
• No limit
• Costly

Non Blocking IO

• Pseudo Code For Blocking IO

Blocking IO program flux

// Fetch some data from DB
var data1 = fetchDataFromDB(dbUrl);

// Fetch some data from Microservice
var data2 = fetchDataFromService(serviceUrl);

// Process all data
var combinedData = processAndCombine(data1, data2);

// Send data to user
sendData(combinedData);

Non-Blocking IO program flux

// Non Blocking: Fetch some data from DB
return fetchDataFromDb(dbUrl, data1 -> {
    // Non Blocking: Fetch some data from Microservice
    return fetchDataFromService(serviceUrl, data2 -> {
        // Process all data and send
        var combinedData = processAndCombine(data1, data2);
        return sendData(combinedData);
    });
});

Virtual Threads

• Lightweight threads (Extends the Thread Class)
  • Fast creation time
  • Exhibits same behaviour as Platform Threads
  • Scales to millions of instances

Advantages

• No need for Thread Pool
• Can block on IO with no scalability issues
• Optimal concurrency
• Code can still be sequential
• Existing code will benefit from using Virtual Thread
• Combine with Future's and CompletableFuture's

Limitations

• Blocking with native frames on Stack (JNI)
  • This is rare
• Control memory per stack
  • Reduce ThreadLocal's usage
  • No deep recursions