Actors Or Not Async Event Architectures
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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. -
Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka
White Paper Information Security | Machine Learning October 2020 IT@Intel: Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka Our Apache Kafka data pipeline based on Confluent Platform ingests tens of terabytes per day, providing in-stream processing for faster security threat detection and response Intel IT Authors Executive Summary Ryan Clark Advanced cyber threats continue to increase in frequency and sophistication, Information Security Engineer threatening computing environments and impacting businesses’ ability to grow. Jen Edmondson More than ever, large enterprises must invest in effective information security, Product Owner using technologies that improve detection and response times. At Intel, we Dennis Kwong are transforming from our legacy cybersecurity systems to a modern, scalable Information Security Engineer Cyber Intelligence Platform (CIP) based on Kafka and Splunk. In our 2019 paper, Transforming Intel’s Security Posture with Innovations in Data Intelligence, we Jac Noel discussed the data lake, monitoring, and security capabilities of Splunk. This Security Solutions Architect paper describes the essential role Apache Kafka plays in our CIP and its key Elaine Rainbolt benefits, as shown here: Industry Engagement Manager ECONOMIES OPERATE ON DATA REDUCE TECHNICAL GENERATES OF SCALE IN STREAM DEBT AND CONTEXTUALLY RICH Paul Salessi DOWNSTREAM COSTS DATA Information Security Engineer Intel IT Contributors Victor Colvard Information Security Engineer GLOBAL ALWAYS MODERN KAFKA LEADERSHIP SCALE AND REACH ON ARCHITECTURE WITH THROUGH CONFLUENT Juan Fernandez THRIVING COMMUNITY EXPERTISE Technical Solutions Specialist Frank Ober SSD Principal Engineer Apache Kafka is the foundation of our CIP architecture. We achieve economies of Table of Contents scale as we acquire data once and consume it many times. -
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. -
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. -
Unravel Data Systems Version 4.5
UNRAVEL DATA SYSTEMS VERSION 4.5 Component name Component version name License names jQuery 1.8.2 MIT License Apache Tomcat 5.5.23 Apache License 2.0 Tachyon Project POM 0.8.2 Apache License 2.0 Apache Directory LDAP API Model 1.0.0-M20 Apache License 2.0 apache/incubator-heron 0.16.5.1 Apache License 2.0 Maven Plugin API 3.0.4 Apache License 2.0 ApacheDS Authentication Interceptor 2.0.0-M15 Apache License 2.0 Apache Directory LDAP API Extras ACI 1.0.0-M20 Apache License 2.0 Apache HttpComponents Core 4.3.3 Apache License 2.0 Spark Project Tags 2.0.0-preview Apache License 2.0 Curator Testing 3.3.0 Apache License 2.0 Apache HttpComponents Core 4.4.5 Apache License 2.0 Apache Commons Daemon 1.0.15 Apache License 2.0 classworlds 2.4 Apache License 2.0 abego TreeLayout Core 1.0.1 BSD 3-clause "New" or "Revised" License jackson-core 2.8.6 Apache License 2.0 Lucene Join 6.6.1 Apache License 2.0 Apache Commons CLI 1.3-cloudera-pre-r1439998 Apache License 2.0 hive-apache 0.5 Apache License 2.0 scala-parser-combinators 1.0.4 BSD 3-clause "New" or "Revised" License com.springsource.javax.xml.bind 2.1.7 Common Development and Distribution License 1.0 SnakeYAML 1.15 Apache License 2.0 JUnit 4.12 Common Public License 1.0 ApacheDS Protocol Kerberos 2.0.0-M12 Apache License 2.0 Apache Groovy 2.4.6 Apache License 2.0 JGraphT - Core 1.2.0 (GNU Lesser General Public License v2.1 or later AND Eclipse Public License 1.0) chill-java 0.5.0 Apache License 2.0 Apache Commons Logging 1.2 Apache License 2.0 OpenCensus 0.12.3 Apache License 2.0 ApacheDS Protocol -
Talend Open Studio for Big Data Release Notes
Talend Open Studio for Big Data Release Notes 6.0.0 Talend Open Studio for Big Data Adapted for v6.0.0. Supersedes previous releases. Publication date July 2, 2015 Copyleft This documentation is provided under the terms of the Creative Commons Public License (CCPL). For more information about what you can and cannot do with this documentation in accordance with the CCPL, please read: http://creativecommons.org/licenses/by-nc-sa/2.0/ Notices Talend is a trademark of Talend, Inc. All brands, product names, company names, trademarks and service marks are the properties of their respective owners. License Agreement The software described in this documentation is licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.html. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. This product includes software developed at AOP Alliance (Java/J2EE AOP standards), ASM, Amazon, AntlR, Apache ActiveMQ, Apache Ant, Apache Avro, Apache Axiom, Apache Axis, Apache Axis 2, Apache Batik, Apache CXF, Apache Cassandra, Apache Chemistry, Apache Common Http Client, Apache Common Http Core, Apache Commons, Apache Commons Bcel, Apache Commons JxPath, Apache -
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. -
Talend ESB System Management Integration User Guide
Talend ESB System Management Integration User Guide 6.0.1 Publication date: September 10, 2015 Copyright © 2011-2015 Talend Inc. All rights reserved. Copyleft This documentation is provided under the terms of the Creative Commons Public License (CCPL). For more information about what you can and cannot do with this documentation in accordance with the CCPL, please read: http://creativecommons.org/licenses/by-nc-sa/2.0/ This document may include documentation produced at The Apache Software Foundation which is licensed under The Apache License 2.0. Notices Talend and Talend ESB are trademarks of Talend, Inc. Apache CXF, CXF, Apache Karaf, Karaf, Apache Camel, Camel, Apache Maven, Maven, Apache Archiva, Archiva, Apache Syncope, Syncope, Apache ActiveMQ, ActiveMQ, Apache Log4j, Log4j, Apache Felix, Felix, Apache ServiceMix, ServiceMix, Apache Ant, Ant, Apache Derby, Derby, Apache Tomcat, Tomcat, Apache ZooKeeper, ZooKeeper, Apache Jackrabbit, Jackrabbit, Apache Santuario, Santuario, Apache DS, DS, Apache Avro, Avro, Apache Abdera, Abdera, Apache Chemistry, Chemistry, Apache CouchDB, CouchDB, Apache Kafka, Kafka, Apache Lucene, Lucene, Apache MINA, MINA, Apache Velocity, Velocity, Apache FOP, FOP, Apache HBase, HBase, Apache Hadoop, Hadoop, Apache Shiro, Shiro, Apache Axiom, Axiom, Apache Neethi, Neethi, Apache WSS4J, WSS4J are trademarks of The Apache Foundation. Eclipse Equinox is a trademark of the Eclipse Foundation, Inc. SoapUI is a trademark of SmartBear Software. Hyperic is a trademark of VMware, Inc. Nagios is a trademark of Nagios Enterprises, LLC. All other brands, product names, company names, trademarks and service marks are the properties of their respective owners. Table of Contents 1. Introduction .............................................................................................................. 1 2. Hyperic HQ Integration .............................................................................................. 3 2.1. -
Release Notes Date Published: 2021-03-25 Date Modified
Cloudera Runtime 7.2.8 Release Notes Date published: 2021-03-25 Date modified: https://docs.cloudera.com/ Legal Notice © Cloudera Inc. 2021. All rights reserved. The documentation is and contains Cloudera proprietary information protected by copyright and other intellectual property rights. No license under copyright or any other intellectual property right is granted herein. Copyright information for Cloudera software may be found within the documentation accompanying each component in a particular release. Cloudera software includes software from various open source or other third party projects, and may be released under the Apache Software License 2.0 (“ASLv2”), the Affero General Public License version 3 (AGPLv3), or other license terms. Other software included may be released under the terms of alternative open source licenses. Please review the license and notice files accompanying the software for additional licensing information. Please visit the Cloudera software product page for more information on Cloudera software. For more information on Cloudera support services, please visit either the Support or Sales page. Feel free to contact us directly to discuss your specific needs. Cloudera reserves the right to change any products at any time, and without notice. Cloudera assumes no responsibility nor liability arising from the use of products, except as expressly agreed to in writing by Cloudera. Cloudera, Cloudera Altus, HUE, Impala, Cloudera Impala, and other Cloudera marks are registered or unregistered trademarks in the United States and other countries. All other trademarks are the property of their respective owners. Disclaimer: EXCEPT AS EXPRESSLY PROVIDED IN A WRITTEN AGREEMENT WITH CLOUDERA, CLOUDERA DOES NOT MAKE NOR GIVE ANY REPRESENTATION, WARRANTY, NOR COVENANT OF ANY KIND, WHETHER EXPRESS OR IMPLIED, IN CONNECTION WITH CLOUDERA TECHNOLOGY OR RELATED SUPPORT PROVIDED IN CONNECTION THEREWITH. -
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.