Apache Camel with Spring Integration Example
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Akka Java Documentation Release 2.2.5
Akka Java Documentation Release 2.2.5 Typesafe Inc February 19, 2015 CONTENTS 1 Introduction 1 1.1 What is Akka?............................................1 1.2 Why Akka?..............................................3 1.3 Getting Started............................................3 1.4 The Obligatory Hello World.....................................7 1.5 Use-case and Deployment Scenarios.................................8 1.6 Examples of use-cases for Akka...................................9 2 General 10 2.1 Terminology, Concepts........................................ 10 2.2 Actor Systems............................................ 12 2.3 What is an Actor?.......................................... 14 2.4 Supervision and Monitoring..................................... 16 2.5 Actor References, Paths and Addresses............................... 19 2.6 Location Transparency........................................ 25 2.7 Akka and the Java Memory Model.................................. 26 2.8 Message Delivery Guarantees.................................... 28 2.9 Configuration............................................. 33 3 Actors 65 3.1 Actors................................................ 65 3.2 Typed Actors............................................. 84 3.3 Fault Tolerance............................................ 88 3.4 Dispatchers.............................................. 103 3.5 Mailboxes.............................................. 106 3.6 Routing................................................ 111 3.7 Building Finite State Machine -
Enterprise Integration Patterns N About Apache Camel N Essential Patterns Enterprise Integration Patterns N Conclusions and More
Brought to you by... #47 CONTENTS INCLUDE: n About Enterprise Integration Patterns n About Apache Camel n Essential Patterns Enterprise Integration Patterns n Conclusions and more... with Apache Camel Visit refcardz.com By Claus Ibsen ABOUT ENTERPRISE INTEGRATION PaTTERNS Problem A single event often triggers a sequence of processing steps Solution Use Pipes and Filters to divide a larger processing steps (filters) that are connected by channels (pipes) Integration is a hard problem. To help deal with the complexity Camel Camel supports Pipes and Filters using the pipeline node. of integration problems the Enterprise Integration Patterns Java DSL from(“jms:queue:order:in”).pipeline(“direct:transformOrd (EIP) have become the standard way to describe, document er”, “direct:validateOrder”, “jms:queue:order:process”); and implement complex integration problems. Hohpe & Where jms represents the JMS component used for consuming JMS messages Woolf’s book the Enterprise Integration Patterns has become on the JMS broker. Direct is used for combining endpoints in a synchronous fashion, allow you to divide routes into sub routes and/or reuse common routes. the bible in the integration space – essential reading for any Tip: Pipeline is the default mode of operation when you specify multiple integration professional. outputs, so it can be omitted and replaced with the more common node: from(“jms:queue:order:in”).to(“direct:transformOrder”, “direct:validateOrder”, “jms:queue:order:process”); Apache Camel is an open source project for implementing TIP: You can also separate each step as individual to nodes: the EIP easily in a few lines of Java code or Spring XML from(“jms:queue:order:in”) configuration. -
Up up and Out: Scaling Software with Akka
UP UP AND OUT: SCALING SOFTWARE WITH AKKA Jonas Bonér CTO Typesafe @jboner Scaling software with Jonas Bonér CTO Typesafe @jboner ScalingScaling softwaresoftware with with ScalingScaling softwaresoftware with with Akka (Áhkká) The name comes from the goddess in the Sami (native swedes) mythology that represented all the wisdom and beauty in the world. It is also the name of a beautiful mountain in Laponia in the north part of Sweden ScalingScaling softwaresoftware with with Manage System Overload Scale UP & Scale OUT How can we achieve this? How can we achieve this? Let’s use Actors How can we achieve this? What is an Actor? What is an Actor? What is an Actor? • Akka's unit of code organization is called an Actor What is an Actor? • Akka's unit of code organization is called an Actor • Like Java EE servlets and session beans, Actors is a model for organizing your code that keeps many “policy decisions” separate from the business logic What is an Actor? • Akka's unit of code organization is called an Actor • Like Java EE servlets and session beans, Actors is a model for organizing your code that keeps many “policy decisions” separate from the business logic • Actors may be new to many in the Java community, but they are a tried-and-true concept (Hewitt 1973) used for many years in telecom systems with 9 nines uptime Program at a Higher Level Program at a Higher Level Program at a Higher Level • Never think in terms of shared state, state visibility, threads, locks, concurrent collections, thread notifications etc. -
Apache Camel
Apache Camel USER GUIDE Version 2.0.0 Copyright 2007-2009, Apache Software Foundation 1 Table of Contents Table of Contents......................................................................... ii Chapter 1 Introduction ...................................................................................1 Chapter 2 Quickstart.......................................................................................1 Chapter 3 Getting Started..............................................................................7 Chapter 4 Architecture................................................................................ 17 Chapter 5 Enterprise Integration Patterns.............................................. 27 Chapter 6 Cook Book ................................................................................... 32 Chapter 7 Tutorials....................................................................................... 85 Chapter 8 Language Appendix.................................................................. 190 Chapter 9 Pattern Appendix..................................................................... 231 Chapter 10 Component Appendix ............................................................. 299 Index ................................................................................................0 ii APACHE CAMEL CHAPTER 1 °°°° Introduction Apache Camel is a powerful open source integration framework based on known Enterprise Integration Patterns with powerful Bean Integration. Camel lets you create the Enterprise Integration -
A Software Framework for the Actor Model Focusing on the Optimization of Message Passing
AICT 2018 : The Fourteenth Advanced International Conference on Telecommunications Actor4j: A Software Framework for the Actor Model Focusing on the Optimization of Message Passing David Alessandro Bauer, Juho Mäkiö Department of Informatics and Electronics University of Applied Sciences Emden/Leer Emden, Germany Email: [email protected], [email protected] Abstract—Common actor implementations often use also the Scale Cube by Abbott [6], which describes the three standardized thread pools without special optimization for the dimensions of scalability. message passing. For that, a high-performance solution was To ensure high parallelization, its one benefit to use worked out. The actor-oriented software framework Akka uses multi-core systems. The computer world of the last few internally a ForkJoinPool that is intended for a MapReduce years has been characterized by a change ("The Free Lunch approach. However, the MapReduce approach is not relevant for message passing, as it may lead to significant performance Is Over" [7]) from constantly increasing computing power losses. One solution is to develop a thread pool that focuses on to multi-core systems due to technical limitations. In the message passing. In the implementation of the Actor4j particular, technical progress always lags behind practical framework, the message queue of the actors is placed in requirements (Wirth's law [8]). Up to now, Moore's law was threads to enable an efficient message exchange. The actors are “that the number of transistors available to semiconductor operated directly from this queue (injecting the message), manufacturers would double approximately every 18 to 24 without further ado. -
An Enterprise Knowledge Network
Fogbeam Labs Cut Through The Information Fog http://www.fogbeam.com An Enterprise Knowledge Network Knowledge exists in many forms inside your organization – ranging from tacit knowledge which exists only in the minds of the users who possess it, to codified knowledge stored in databases and document repositories. Unfortunately while knowledge exists throughout the organization, it is often not easy (if even possible) to locate, use, share, and reuse existing knowledge. This results in a situation often described as “the left hand doesn't know what the right hand is doing” and damages morale as employees spend their days frustrated and complaining that “nobody knows what is going on around here”. The obstacles that hinder access to existing knowledge can be cultural, geographical, social, and/or technological. And while no technological solution can guarantee perfect knowledge-sharing, tools drawn from big data, data mining / machine learning, deep learning, and artificial intelligence techniques can improve an organization's power to generate, capture, use, share and reuse knowledge. Using technologies developed as part of the semantic web initiative, and applying the principles of linked data within the enterprise, the Fogbeam Labs Enterprise Knowledge Network approach can help your firm integrate and aggregate knowledge which is spread across your existing enterprise applications, content repositories and Intranet. An Enterprise Knowledge Network enables your firm's capabilities to: • engage in high levels of knowledge transfer and -
Reactive Programming with Scala, Lagom, Spark, Akka and Play
Issue October 2016 | presented by www.jaxenter.com #53 The digital magazine for enterprise developers Reactive Programming with Scala, Lagom, Spark, Akka and Play Interview with Scala creator Martin Odersky The state of Scala The Lagom Framework Lagom gives the developer a clear path DevOpsCon 2016: Our mission statement This is how we interpret modern DevOps ©istockphoto.com/moorsky Editorial Reactive programming is gaining momentum “We believe that a coherent approach to systems architec- If the definition “stream of events” does not satisfy your ture is needed, and we believe that all necessary aspects are thirst for knowledge, get ready to find out what reactive pro- already recognized individually: we want systems that are Re- gramming means to our experts in Scala, Lagom, Spark, Akka sponsive, Resilient, Elastic and Message Driven. We call these and Play. Plus, we talked to Scala creator Martin Odersky Reactive Systems.” – The Reactive Manifesto about the impending Scala 2.12, the current state of this pro- Why should anyone adopt reactive programming? Because gramming language and the technical innovations that await it allows you to make code more concise and focus on im- us. portant aspects such as the interdependence of events which Thirsty for more? Open the magazine and see what we have describe the business logic. Reactive programming means dif- prepared for you. ferent things to different people and we are not trying to rein- vent the wheel or define this concept. Instead we are allowing Gabriela Motroc, Editor our authors to prove how Scala, Lagom, Spark, Akka and Play co-exist and work together to create a reactive universe. -
Architecture of Mule and Servicemix 42 3 ■ Setting up the Mule and Servicemix Environments 72 4 ■ the Foundation of an Integration Solution 111
Open Source ESBs in Action Open Source ESBs in Action EXAMPLE IMPLEMENTATIONS IN MULE AND SERVICEMIX TIJS RADEMAKERS JOS DIRKSEN MANNING Greenwich (74° w. long.) For online information and ordering of this and other Manning books, please visit www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact: Special Sales Department Manning Publications Co. Sound View Court 3B Fax: (609) 877-8256 Greenwich, CT 06830 Email: [email protected] ©2009 by Manning Publications Co. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acid-free paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are printed on paper that is at least 15% recycled and processed elemental chlorine-free Development Editor: Jeff Bleil Manning Publications Co. Copyeditors: Liz Welch, Tiffany Taylor Sound View Court 3B Typesetter: Denis -
Lightweight Affinity and Object Capabilities in Scala
http://www.diva-portal.org Postprint This is the accepted version of a paper presented at ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA). Citation for the original published paper: Haller, P., Loiko, A. (2016) LaCasa: Lightweight Affinity and Object Capabilities in Scala. In: Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (pp. 272-291). Association for Computing Machinery (ACM) https://doi.org/10.1145/3022671.2984042 N.B. When citing this work, cite the original published paper. © Author | ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications, http://dx.doi.org/10.1145/3022671.2984042. Permanent link to this version: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-197902 LACASA: Lightweight Affinity and Object Capabilities in Scala Philipp Haller Alex Loiko KTH Royal Institute of Technology, Sweden Google, Sweden ∗ [email protected] [email protected] Abstract difficulty of reasoning about program behavior and software Aliasing is a known source of challenges in the context of architecture [3], and it can introduce data races in concur- imperative object-oriented languages, which have led to im- rent programs. These observations have informed the devel- portant advances in type systems for aliasing control. How- opment of a number of type disciplines aimed at providing ever, their large-scale adoption has turned out to be a surpris- static aliasing properties, such as linear types [33, 51, 64], ingly difficult challenge. -
Comparing Languages for Engineering Server Software: Erlang, Go, and Scala with Akka
Comparing Languages for Engineering Server Software: Erlang, Go, and Scala with Akka Ivan Valkov, Natalia Chechina, and Phil Trinder School of Computing Science, University of Glasgow G12 8RZ, United Kingdom [email protected], {Natalia.Chechina, Phil.Trinder}@glasgow.ac.uk Abstract functional or object-oriented, with high-level coordination models, Servers are a key element of current IT infrastructures, and must e.g. actors as in Erlang [2] or a process algebra as in Go [6]. Indeed, often deal with large numbers of concurrent requests. The program- the success of some server-based companies is even attributed to ming language used to construct the server has an important role their use of specific languages. As examples WhatsApp’s success in engineering efficient server software, and must support massive is attributed to their use of Erlang [27]; the video streaming leader concurrency on multicore machines with low communication and Twitch uses Go to serve millions of users a day [13]. Research synchronisation overheads. contributions of this paper include the following: This paper investigates 12 highly concurrent programming lan- • A survey of programming language characteristics relevant for guages suitable for engineering servers, and analyses three repre- servers (Section 2.1). sentative languages in detail: Erlang, Go, and Scala with Akka. • The design and implementation of three benchmarks to analyse We have designed three server benchmarks that analyse key per- the multicore server capabilities of Erlang, Go, and Scala with formance characteristics of the languages. The benchmark results Akka (Section 3). suggest that where minimising message latency is crucial, Go and Erlang are best; that Scala with Akka is capable of supporting the • An evaluation of Erlang, Go, and Scala with Akka for key largest number of dormant processes; that for servers that frequently server capabilities, i.e. -
Pick Technologies & Tools Faster by Coding with Jhipster: Talk Page At
Picks, configures, and updates best technologies & tools “Superstar developer” Writes all the “boring plumbing code”: Production grade, all layers What is it? Full applications with front-end & back-end Open-source Java application generator No mobile apps Generates complete application with user Create it by running wizard or import management, tests, continuous integration, application configuration from JHipster deployment & monitoring Domain Language (JDL) file Import data model from JDL file Generates CRUD front-end & back-end for our entities Re-import after JDL file changes Re-generates application & entities with new JHipster version What does it do? Overwriting your own code changes can be painful! Microservices & Container Updates application Receive security patches or framework Fullstack Developer updates (like Spring Boot) Shift Left Sometimes switches out library: yarn => npm, JavaScript test libraries, Webpack => Angular Changes for Java developers from 10 years CLI DevOps ago JHipster picked and configured technologies & Single Page Applications tools for us Mobile Apps We picked architecture: monolith Generate application Generated project Cloud Live Demo We picked technologies & tools (like MongoDB or React) Before: Either front-end or back-end developer inside app server with corporate DB Started to generate CRUD screens Java back-end Generate CRUD Before and after Web front-end Monolith and microservices After: Code, test, run & support up to 4 applications iOS front-end Java and Kotlin More technologies & tools? Android -
Jhipster.NET Documentation!
JHipster.NET Release 3.1.1 Jul 28, 2021 Introduction 1 Big Picture 3 2 Getting Started 5 2.1 Prerequisites...............................................5 2.2 Generate your first application......................................5 3 Azure 7 3.1 Deploy using Terraform.........................................7 4 Code Analysis 9 4.1 Running SonarQube by script......................................9 4.2 Running SonarQube manually......................................9 5 CQRS 11 5.1 Introduction............................................... 11 5.2 Create your own Queries or Commands................................. 11 6 Cypress 13 6.1 Introduction............................................... 13 6.2 Pre-requisites............................................... 13 6.3 How to use it............................................... 13 7 Database 15 7.1 Using database migrations........................................ 15 8 Dependencies Management 17 8.1 Nuget Management........................................... 17 8.2 Caution.................................................. 17 9 DTOs 19 9.1 Using DTOs............................................... 19 10 Entities auditing 21 10.1 Audit properties............................................. 21 10.2 Audit of generated Entities........................................ 21 10.3 Automatically set properties audit.................................... 22 11 Fronts 23 i 11.1 Angular.................................................. 23 11.2 React................................................... 23 11.3 Vue.js..................................................