How do you choose the appropriate multithreading design pattern for your problem domain?

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Multithreading is a powerful technique to improve the performance and responsiveness of your applications, but it also introduces new challenges and complexities. How do you decide which multithreading design pattern to use for your problem domain? In this article, you will learn about some common multithreading design patterns and how to choose the best one for your needs.

本文章的要点总结

Analyze task complexity:

Consider the nature of your tasks when choosing a multithreading pattern. If you have complex tasks that can be broken down into smaller, independent subtasks, the pipeline pattern might be your best bet. It allows for segmented processing, enhancing efficiency.
Combine patterns flexibly:

Don't hesitate to mix multithreading patterns to fit your needs. For instance, you can use the reactor pattern for handling events and pair it with the future/promise pattern for managing asynchronous operations effectively. This hybrid approach can optimize processing.

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Fuad Efendi

Capital Markets, Blockchain, Web3
Deepak Kumar

Propelling AI To Reinvent The Future ||…

1 Producer-consumer pattern

The producer-consumer pattern is a classic multithreading design pattern that involves two types of threads: producers and consumers. Producers generate data or tasks and put them into a shared buffer or queue. Consumers take data or tasks from the buffer or queue and process them. The producer-consumer pattern is useful when you have multiple sources of data or tasks that need to be processed by multiple workers in parallel. For example, you can use this pattern to implement a web crawler, a message broker, or a video encoder.

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2 Worker pool pattern

The worker pool pattern is a variation of the producer-consumer pattern that uses a fixed number of threads to process tasks from a shared queue. The worker pool pattern is useful when you want to limit the number of threads and reuse them for different tasks. For example, you can use this pattern to implement a web server, a database connection pool, or a thread-safe object pool.

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Fuad Efendi

Capital Markets, Blockchain, Web3
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"database connection pool" and "thread-safe object pool" are object pools and NOT thread pools. These "pools" do not use shared queue. For thread safe application, we need to serialize object state changes, "A happens before B" guarantee, if it is randomized (unpredictable) it is not safe. To achieve this, for example, Oracle internally uses "serial" transaction log; Cassandra uses "append new versioned record" (instead of updating existing one); and in Java, we can use Queue (to serialize sequence of events) and thread pool listening to "events". For example, web server typically has single dispatcher (listening on port 80 or 443), putting HTTP requests into "queue", and thread pool of "workers".

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3 Pipeline pattern

The pipeline pattern is another variation of the producer-consumer pattern that uses multiple stages of processing for each task. Each stage is performed by a different thread or group of threads, and the output of one stage is the input of the next stage. The pipeline pattern is useful when you have a complex task that can be decomposed into smaller and independent subtasks. For example, you can use this pattern to implement a data analysis, a image processing, or a text processing application.

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4 Reactor pattern

The reactor pattern is a multithreading design pattern that uses a single thread to handle multiple events from multiple sources. The reactor thread waits for events to occur, and dispatches them to appropriate handlers that run on separate threads. The reactor pattern is useful when you have a high number of concurrent events that are short-lived and non-blocking. For example, you can use this pattern to implement a network server, a user interface, or a game engine.

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5 Future/promise pattern

The future/promise pattern is a multithreading design pattern that uses abstractions to represent the results of asynchronous operations. A future is an object that holds the state and value of an operation that will be completed in the future. A promise is an object that can fulfill or reject a future with a value or an error. The future/promise pattern is useful when you want to write concise and readable code that handles asynchronous operations without blocking or waiting. For example, you can use this pattern to implement a web service client, a file system access, or a parallel computation.

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6 Actor model

The actor model is a multithreading design pattern that uses autonomous and concurrent entities called actors to communicate and coordinate with each other. Actors have their own state and behavior, and they only interact with other actors by exchanging messages. Actors can create, send, receive, and process messages asynchronously and transparently. The actor model is useful when you want to write scalable and fault-tolerant applications that can handle complex and dynamic interactions. For example, you can use this pattern to implement a distributed system, a chat application, or a simulation.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Deepak Kumar

Propelling AI To Reinvent The Future || Mentor|| Leader || Innovator || Machine learning Specialist || Distributed architecture | IoT | Cloud Computing
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We should not think that we need to apply only one pattern in a process.. We can use multiple patterns together for a problem.. Refer below example which uses reactor pattern and future/promise pattern. Suppose you have a server that listens for incoming connections. When a connection is established, the server creates a new thread to handle the connection. The new thread uses the reactor design pattern to handle incoming data from the client. When the client sends data, the reactor dispatches it to an appropriate handler that runs on a separate thread. The handler uses the future/promise pattern to perform some asynchronous operation (such as reading from a file), and returns a promise object that represents the result of the operation.

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Fuad Efendi

Capital Markets, Blockchain, Web3
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There are two more classic (J2EE, EJB) database transactions patterns: Optimistic Concurrency, and Pessimistic Concurrency. Pessimistic Concurrency: for example, adding "synchronized" keyword before method signature in Java; or locking database record (in worst case: table) before making changes. It is "pessimistic" because it assumes there could be many potential problems (many users) Optimistic Concurrency: for example, using version control field in a database and updating records with DML like "UPDATE employee SET department_id=?, version=6 WHERE employee_id=? AND version=5". In this case, we read record, version=5, and then we try to update "WHERE ... AND version=5", and if record (version) changed transaction fails.

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How do you choose the appropriate multithreading design pattern for your problem domain?

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1 Producer-consumer pattern

2 Worker pool pattern

3 Pipeline pattern

4 Reactor pattern

5 Future/promise pattern

6 Actor model

7 Here’s what else to consider

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