Apache Flume
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Apache Sentry
Apache Sentry Prasad Mujumdar [email protected] [email protected] Agenda ● Various aspects of data security ● Apache Sentry for authorization ● Key concepts of Apache Sentry ● Sentry features ● Sentry architecture ● Integration with Hadoop ecosystem ● Sentry administration ● Future plans ● Demo ● Questions Who am I • Software engineer at Cloudera • Committer and PPMC member of Apache Sentry • also for Apache Hive and Apache Flume • Part of the the original team that started Sentry work Aspects of security Perimeter Access Visibility Data Authentication Authorization Audit, Lineage Encryption, what user can do data origin, usage Kerberos, LDAP/AD Masking with data Data access Access ● Provide user access to data Authorization ● Manage access policies what user can do ● Provide role based access with data Agenda ● Various aspects of data security ● Apache Sentry for authorization ● Key concepts of Apache Sentry ● Sentry features ● Sentry architecture ● Integration with Hadoop ecosystem ● Sentry administration ● Future plans ● Demo ● Questions Apache Sentry (Incubating) Unified Authorization module for Hadoop Unlocks Key RBAC Requirements Secure, fine-grained, role-based authorization Multi-tenant administration Enforce a common set of policies across multiple data access path in Hadoop. Key Capabilities of Sentry Fine-Grained Authorization Permissions on object hierarchie. Eg, Database, Table, Columns Role-Based Authorization Support for role templetes to manage authorization for a large set of users and data objects Multi Tanent Administration -
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. -
Cómo Citar El Artículo Número Completo Más Información Del
DYNA ISSN: 0012-7353 Universidad Nacional de Colombia Iván-Herrera-Herrera, Nelson; Luján-Mora, Sergio; Gómez-Torres, Estevan Ricardo Integración de herramientas para la toma de decisiones en la congestión vehicular DYNA, vol. 85, núm. 205, 2018, Abril-Junio, pp. 363-370 Universidad Nacional de Colombia DOI: https://doi.org/10.15446/dyna.v85n205.67745 Disponible en: https://www.redalyc.org/articulo.oa?id=49657889045 Cómo citar el artículo Número completo Sistema de Información Científica Redalyc Más información del artículo Red de Revistas Científicas de América Latina y el Caribe, España y Portugal Página de la revista en redalyc.org Proyecto académico sin fines de lucro, desarrollado bajo la iniciativa de acceso abierto Integration of tools for decision making in vehicular congestion• Nelson Iván-Herrera-Herreraa, Sergio Luján-Morab & Estevan Ricardo Gómez-Torres a a Facultad de Ciencias de la Ingeniería e Industrias, Universidad Tecnológica Equinoccial, Quito, Ecuador. [email protected], [email protected] b Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, España. [email protected] Received: September 15th, 2017. Received in revised form: March 15th, 2018. Accepted: March 21th, 2018. Abstract The purpose of this study is to present an analysis of the use and integration of technological tools that help decision making in situations of vehicular congestion. The city of Quito-Ecuador is considered as a case study for the done work. The research is presented according to the development of an application, using Big Data tools (Apache Flume, Apache Hadoop, Apache Pig), favoring the processing of a lot of information that is required to collect, store and process. -
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 -
Database Licensing Information User Manual
Oracle® Database Database Licensing Information User Manual 19c E94254-04 April 2019 Oracle Database Database Licensing Information User Manual, 19c E94254-04 Copyright © 2004, 2019, Oracle and/or its affiliates. All rights reserved. Contributors: Penny Avril, Prabhaker Gongloor, Mughees Minhas, Anu Natarajan, Jill Robinson This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, delivered to U.S. Government end users are "commercial computer software" pursuant to the applicable Federal Acquisition Regulation and agency- specific supplemental regulations. As such, use, duplication, disclosure, modification, and adaptation of the programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, shall be subject to license terms and license restrictions applicable to the programs. -
HDP 3.1.4 Release Notes Date of Publish: 2019-08-26
Release Notes 3 HDP 3.1.4 Release Notes Date of Publish: 2019-08-26 https://docs.hortonworks.com Release Notes | Contents | ii Contents HDP 3.1.4 Release Notes..........................................................................................4 Component Versions.................................................................................................4 Descriptions of New Features..................................................................................5 Deprecation Notices.................................................................................................. 6 Terminology.......................................................................................................................................................... 6 Removed Components and Product Capabilities.................................................................................................6 Testing Unsupported Features................................................................................ 6 Descriptions of the Latest Technical Preview Features.......................................................................................7 Upgrading to HDP 3.1.4...........................................................................................7 Behavioral Changes.................................................................................................. 7 Apache Patch Information.....................................................................................11 Accumulo........................................................................................................................................................... -
Flume 1.8.0 Developer Guide
Apache ™ Flume™ Flume 1.8.0 Developer Guide Introduction Overview Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store. Apache Flume is a top-level project at the Apache Software Foundation. There are currently two release code lines available, versions 0.9.x and 1.x. This documentation applies to the 1.x codeline. For the 0.9.x codeline, please see the Flume 0.9.x Developer Guide. Architecture Data flow model An Event is a unit of data that flows through a Flume agent. The Event flows from Source to Channel to Sink, and is represented by an implementation of the Event interface. An Event carries a payload (byte array) that is accompanied by an optional set of headers (string attributes). A Flume agent is a process (JVM) that hosts the components that allow Events to flow from an external source to a external destination. A Source consumes Events having a specific format, and those Events are delivered to the Source by an external source like a web server. For example, an AvroSource can be used to receive Avro Events from clients or from other Flume agents in the flow. When a Source receives an Event, it stores it into one or more Channels. The Channel is a passive store that holds the Event until that Event is consumed by a Sink. One type of Channel available in Flume is the FileChannel which uses the local filesystem as its backing store. -
An Empirical Performance Evaluation of Apache Kafka
How Fast Can We Insert? An Empirical Performance Evaluation of Apache Kafka Guenter Hesse, Christoph Matthies, Matthias Uflacker Hasso Plattner Institute University of Potsdam Germany fi[email protected] about such study results is a prerequisite for making informed Abstract—Message brokers see widespread adoption in modern decisions about whether a system is suitable for the existing IT landscapes, with Apache Kafka being one of the most use cases. Additionally, it is also crucial for finding or fine- employed platforms. These systems feature well-defined APIs for use and configuration and present flexible solutions for tuning appropriate system configurations. various data storage scenarios. Their ability to scale horizontally The contributions of this research are as follows: enables users to adapt to growing data volumes and changing • We propose a user-centered and extensible monitoring environments. However, one of the main challenges concerning framework, which includes tooling for analyzing any message brokers is the danger of them becoming a bottleneck within an IT architecture. To prevent this, knowledge about the JVM-based system. amount of data a message broker using a specific configuration • We present an analysis that highlights the capabilities of can handle needs to be available. In this paper, we propose a Apache Kafka regarding the maximum achievable rate of monitoring architecture for message brokers and similar Java incoming records per time unit. Virtual Machine-based systems. We present a comprehensive • We enable reproducibility of the presented results by performance analysis of the popular Apache Kafka platform 1 using our approach. As part of the benchmark, we study selected making all needed artifacts available online . -
Full-Graph-Limited-Mvn-Deps.Pdf
org.jboss.cl.jboss-cl-2.0.9.GA org.jboss.cl.jboss-cl-parent-2.2.1.GA org.jboss.cl.jboss-classloader-N/A org.jboss.cl.jboss-classloading-vfs-N/A org.jboss.cl.jboss-classloading-N/A org.primefaces.extensions.master-pom-1.0.0 org.sonatype.mercury.mercury-mp3-1.0-alpha-1 org.primefaces.themes.overcast-${primefaces.theme.version} org.primefaces.themes.dark-hive-${primefaces.theme.version}org.primefaces.themes.humanity-${primefaces.theme.version}org.primefaces.themes.le-frog-${primefaces.theme.version} org.primefaces.themes.south-street-${primefaces.theme.version}org.primefaces.themes.sunny-${primefaces.theme.version}org.primefaces.themes.hot-sneaks-${primefaces.theme.version}org.primefaces.themes.cupertino-${primefaces.theme.version} org.primefaces.themes.trontastic-${primefaces.theme.version}org.primefaces.themes.excite-bike-${primefaces.theme.version} org.apache.maven.mercury.mercury-external-N/A org.primefaces.themes.redmond-${primefaces.theme.version}org.primefaces.themes.afterwork-${primefaces.theme.version}org.primefaces.themes.glass-x-${primefaces.theme.version}org.primefaces.themes.home-${primefaces.theme.version} org.primefaces.themes.black-tie-${primefaces.theme.version}org.primefaces.themes.eggplant-${primefaces.theme.version} org.apache.maven.mercury.mercury-repo-remote-m2-N/Aorg.apache.maven.mercury.mercury-md-sat-N/A org.primefaces.themes.ui-lightness-${primefaces.theme.version}org.primefaces.themes.midnight-${primefaces.theme.version}org.primefaces.themes.mint-choc-${primefaces.theme.version}org.primefaces.themes.afternoon-${primefaces.theme.version}org.primefaces.themes.dot-luv-${primefaces.theme.version}org.primefaces.themes.smoothness-${primefaces.theme.version}org.primefaces.themes.swanky-purse-${primefaces.theme.version} -
Linux on Z Platform ISV Strategy Summary
Linux on IBM Z / LinuxONE Open Source Ecosystem Status and Strategy for NY/NJ Linux Council Meeting on March 1, 2019 Enyu Wang Program Director, Ecosystem Strategy and Business Development [email protected] As an enterprise platform WHY ARE WE INVESTING IN OPEN SOURCE ECOSYSTEM? IBM Z / Open Source Ecosystem / Mar 1, 2019 / © 2019 IBM Corporation 2 TREND: Enterprise Going Open Source • 83% hiring managers surveyed for the 2018 Open Source Jobs report said hiring open source talent was a priority this year • Some of the biggest trends in enterprise IT, such as containers and hybrid cloud, rely on open source technologies including Linux and Kubernetes IBM Z / Open Source Ecosystem / Mar 1, 2019 / © 2019 IBM Corporation 3 OPEN SOURCE Building Blocks for Enterprise Digital Transformation IBM Z / Open Source Ecosystem / Mar 1, 2019 / © 2019 IBM Corporation 4 OUR MISSION Provide a Rich and Robust Ecosystem to Clients. Help Accelerate their Digital Transformation IBM Z / Open Source Ecosystem / Mar 1, 2019 / © 2019 IBM Corporation 5 Rich Open Source Ecosystem on Linux on Z/LinuxONE Analytics/ Distributions Hypervisors PaaS / IaaS Languages Runtimes Management Database ML LPA R IBM Cloud Private Community Versions LLVM vRealize LXD (Ubuntu) Apache Tomcat DPM Db2 IBM Z / Open Source Ecosystem / Mar 1, 2019 / © 2019 IBM Corporation 6 Building an Open Ecosystem Isn’t Just Porting… IBM Z / Open Source Ecosystem / Mar 1, 2019 / © 2019 IBM Corporation 7 Composition of Open Source Ecosystem on Z – a combination of community based projects and vendor -
The Geography of Job Tasks
Working Papers WP 21-27 August 2021 https://doi.org/10.21799/frbp.wp.2021.27 The Geography of Job Tasks Enghin Atalay Federal Reserve Bank of Philadelphia Research Department Sebastian Sotelo University of Michigan-Ann Arbor Daniel Tannenbaum University of Nebraska-Lincoln ISSN: 1962-5361 Disclaimer: This Philadelphia Fed working paper represents preliminary research that is being circulated for discussion purposes. The views expressed in these papers are solely those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. Philadelphia Fed working papers are free to download at: https://philadelphiafed.org/research-and-data/publications/working-papers. The Geography of Job Tasks ∗ Enghin Atalay Sebastian Sotelo Daniel Tannenbaum August 3, 2021 Abstract The returns to skills and the nature of work differ systematically across labor mar- kets of different sizes. Prior research has pointed to worker interactions, technological innovation, and specialization as key sources of urban productivity gains, but has been limited by the available data in its ability to fully characterize work across geographies. We study the sources of geographic inequality and present new facts about the geog- raphy of work using online job ads. We show that the (i) intensity of interactive and analytic tasks, (ii) technological requirements, and (iii) task specialization all increase with city size. The gradient for tasks and technologies exists both across and within occupations. It is also steeper for jobs requiring a college degree and for workers employed in non-tradable industries. -
Storage and Ingestion Systems in Support of Stream Processing
Storage and Ingestion Systems in Support of Stream Processing: A Survey Ovidiu-Cristian Marcu, Alexandru Costan, Gabriel Antoniu, María Pérez-Hernández, Radu Tudoran, Stefano Bortoli, Bogdan Nicolae To cite this version: Ovidiu-Cristian Marcu, Alexandru Costan, Gabriel Antoniu, María Pérez-Hernández, Radu Tudoran, et al.. Storage and Ingestion Systems in Support of Stream Processing: A Survey. [Technical Report] RT-0501, INRIA Rennes - Bretagne Atlantique and University of Rennes 1, France. 2018, pp.1-33. hal-01939280v2 HAL Id: hal-01939280 https://hal.inria.fr/hal-01939280v2 Submitted on 14 Dec 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Storage and Ingestion Systems in Support of Stream Processing: A Survey Ovidiu-Cristian Marcu, Alexandru Costan, Gabriel Antoniu, María S. Pérez-Hernández, Radu Tudoran, Stefano Bortoli, Bogdan Nicolae TECHNICAL REPORT N° 0501 November 2018 Project-Team KerData ISSN 0249-0803 ISRN INRIA/RT--0501--FR+ENG Storage and Ingestion Systems in Support of Stream Processing: A Survey Ovidiu-Cristian Marcu∗, Alexandru