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Tag Archives: Akka

Reactive Queue with Akka Reactive Streams

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Reactive streams is a recently announced initiative to create a standard for asynchronous stream processing with built-in back-pressure, on the JVM. The working group is formed by companies such as Typesafe, Red Hat, Oracle, Netflix, and others. One of the early, experimental implementations is based on Akka. Preview version 0.3 includes actor producers & consumers, which opens up some new ...

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Simplifying trading system with Akka

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My colleagues are developing a trading system that processes quite heavy stream of incoming transactions. Each transaction covers one Instrument (think bond or stock) and has some (now) unimportant properties. They are stuck with Java (< 8), so let’s stick to it:               class Instrument implements Serializable, Comparable<Instrument> { private final String name; public ...

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Akka Java for large-scale event processing

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We are designing a large scale distributed event-driven system for real-time data replication across transactional databases. The data(messages) from the source system undergoes a series of transformations and routing-logic before reaching its destination. These transformations are multi-process and multi-threaded operations, comprising of smaller stateless steps and tasks that can be performed concurrently. There is no shared state across processes instead, the state transformations ...

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Akka Toolkit 2.3 released

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The release of 2.3.0 version of Akka toolkit was recently announced. Akka is a very useful toolkit and runtime for building highly concurrent, distributed, and fault tolerant event-driven applications on the JVM. It is distributed and provides high-level abstractions like Actors, Futures and STM. Its new release comes eight months after the 2.2.0 release and brings along new features. One ...

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Three flavours of request-response pattern in Akka

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Imagine a simple Akka actor system consisting of two parties: MonitoringActor and NetworkActor. Whenever someone (client) sends CheckHealth to the former one it asks the latter by sending Ping. NetworkActor is obligated to reply with Pong as soon as possible (scenario [A]). Once MonitoringActor receives such a reply it immediately replies to the client with Up status message. However MonitoringActor ...

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Sending Email with Java and Akka actors

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Akka is a concurrent framework written by Scala. Here I demonstrate sample application to send emails with Akka and implemented in Java. Reasons I decided to use Akka framework other than concurrency. Built-in configurable supervisor strategy to monitor child workers and decide what policy applies when there is an exception. Can reschedule delivery when application throwing some specific exception. Use ...

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Future Composition with Scala and Akka

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Scala is functional and object-oriented language, which runs on the JVM. For concurrent and/or parallel programming it is a suitable choice along with the Akka framework, which provides a rich toolset for all kind of concurrent tasks. In this post I want to show a little example how to schedule a logfile-search job on multiple files/servers with Futures and Actors. ...

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Managing congested actors in Akka

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There comes a time in an Akka application when an actor can longer handle increasing load. Since each actor can only handle one message at a time and it keeps a backlog of pending messages in a queue called mailbox, there is a risk of overloading one actor if too many messages are sent to one actor at the same ...

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Akka vs Storm

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I was recently working a bit with Twitter’s Storm, and it got me wondering, how does it compare to another high-performance, concurrent-data-processing framework, Akka. What’s Akka and Storm? Let’s start with a short description of both systems. Storm is a distributed, real-time computation system. On a Storm cluster, you execute topologies, which process streams of tuples (data). Each topology is ...

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