Diego has been a senior freelance engineer for the likes of Italian telecom powerhouse Italtel. He also cofounded a web-based CRM business.
Writing concurrent programs is hard. Having to deal with threads, locks, race conditions, and so on is highly error-prone and can lead to code that is difficult to read, test, and maintain.
Many therefore prefer to avoid multithreading altogether. Instead, they employ single-threaded processes exclusively, relying on external services (such as databases, queues, etc.) to handle any needed concurrent or asynchronous operations. While this approach is in some cases a legitimate alternative, there are many scenarios in which it is simply not a viable option. Many real-time systems – such as trading or banking applications, or real-time games – don’t have the luxury of waiting for a single-threaded process to complete (they need the answer now!). Other systems are so compute- or resource-intensive that they would take an inordinate amount of time (hours or even days in some cases) to run without introducing parallelization into their code.
One fairly common single-threaded approach (widely used in the Node.js world, for example) is to use an event-based, non-blocking paradigm. While this does help performance by avoiding context switches, locks, and blocking, it still does not address the issues of using multiple processors concurrently (doing so would require launching, and coordinating between, multiple independent processes).
So does this mean you have no choice but to journey deep into the bowels of threads, locks, and race conditions in order to build a concurrent application?
Thanks to the Akka framework, the answer is no. This tutorial introduces Akka examples and explores the ways in which it facilitates and simplifies the implementation of concurrent, distributed applications.
What is the difference between Akka Kill vs Stop vs Poison Pill?Both stop and PoisonPill will terminate the actor and stop the message queue. They will cause the actor to cease processing messages, send a stop call to all its children, wait for them to terminate, then call its postStop hook. All further messages are sent to the dead letters mailboBy contrast, the Kill message causes the actor to throw an ActorKilledException which gets handled using the normal supervisor mechanism.
Actors execute independently from the senders of a message, and they react to incoming messages sequentially, one at a time. While each actor processes messages sent to it sequentially, different actors work concurrently with each other so that an actor system can process as many messages simultaneously as the hardware will support.
Actor model resolves the issues with common programming practices by message passing that avoids locking and blocking. Instead of calling methods, actors send messages to each other. Sending a message does not transfer the thread of execution from the sender to the destination. An actor can send a message and continue without blocking. The difference between passing messages and calling methods is that messages have no return value. By sending a message, an actor delegates work to another actor(receiving). The receiving actor delivers the results in a reply message.
There are a few different ways to design a system like this, but one approach would be to have each actor maintain a list of other actors that it can communicate with. When an actor wants to send a message to another actor, it would simply add the message to the list of messages that the other actor needs to process. The other actor would then process the message when it is able to.
Actor paths are used to uniquely identify each actor in an Akka system. The path consists of the actor’s name and the path to the actor’s mailbox. The actor’s name is used to identify the actor within the scope of the actor system, while the path to the mailbox is used to identify the actor across different actor systems.
Here are 20 commonly asked Akka interview questions and answers to prepare you for your interview:
Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM. Akka is designed to work with both Java and Scala, and it integrates with popular build tools like Maven and sbt. Akka is used in a variety of applications, including big data, Internet of Things, microservices, and more. Some of the main benefits of using Akka include its ability to handle high throughput and low latency, its scalability, and its fault tolerance.
The main advantage of using Akka is that it can provide much better performance than traditional approaches. Akka is able to do this by using a much more efficient message passing system than what is typically used. This allows for a much higher degree of parallelism, which can lead to significant speedups.