Powerful concurrency patterns that you should utilize as a Java Developer

Concurrency in Java can be achieved using threads and various synchronization mechanisms.

In this article let’s discuss Pipeline pattern, a common and powerful concurrency patterns we can use in Java.

In the Worker Pool Pattern, a fixed number of worker threads are created to process jobs. These workers fetch tasks from a queue and process them concurrently. This pattern is especially useful for managing resource utilization, as it prevents spawning an excessive number of threads, which could lead to higher memory usage and reduced performance. Remember that creating threads in Java has a higher overhead compared to goroutines in Go, so benchmarking is recommended to determine the optimal number of threads.

Controlled Concurrency: Offers control over how many tasks run concurrently.

Load Distribution: Evenly distributes tasks across multiple worker threads.

The Pipeline Pattern is inspired by the concept of assembly lines in manufacturing, where a product moves through various stages, each adding something to the final product. In Java, this can be implemented using threads and blocking queues:

Stages: Each stage in the pipeline is a group of threads performing the same function. A stage takes input from an inbound queue, processes it, and sends it to the next stage through an outbound queue.

Queues: Blocking queues are used to connect these stages. They allow for safe and synchronized communication between different stages in the pipeline.

Data Flow: Data flows through the pipeline from the first stage to the last, getting transformed/operated on at each stage.

The great part about the pipeline pattern is that we can have different numbers of concurrent threads at each stage, and we can define it based on the complexity of the task! To summarize the benefits, with pipline pattern we can achieve –

Modularity: Each stage is independent and encapsulates its processing logic, making the code more readable and maintainable.

Concurrency: Since each stage can run in parallel, the pattern can efficiently utilize multi-core processors.

Flexibility: It is easy to add, remove, or modify stages without affecting the entire pipeline.

In Java, we can use thread pools and blocking queues to implement these patterns effectively.