Datacenter Simulation Methodologies Web Search
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Lucene in Action Second Edition
Covers Apache Lucene 3.0 IN ACTION SECOND EDITION Michael McCandless Erik Hatcher , Otis Gospodnetic FOREWORD BY DOUG CUTTING MANNING www.it-ebooks.info Praise for the First Edition This is definitely the book to have if you’re planning on using Lucene in your application, or are interested in what Lucene can do for you. —JavaLobby Search powers the information age. This book is a gateway to this invaluable resource...It suc- ceeds admirably in elucidating the application programming interface (API), with many code examples and cogent explanations, opening the door to a fine tool. —Computing Reviews A must-read for anyone who wants to learn about Lucene or is even considering embedding search into their applications or just wants to learn about information retrieval in general. Highly recommended! —TheServerSide.com Well thought-out...thoroughly edited...stands out clearly from the crowd....I enjoyed reading this book. If you have any text-searching needs, this book will be more than sufficient equipment to guide you to successful completion. Even, if you are just looking to download a pre-written search engine, then this book will provide a good background to the nature of information retrieval in general and text indexing and searching specifically. —Slashdot.org The book is more like a crystal ball than ink on pape--I run into solutions to my most pressing problems as I read through it. —Arman Anwar, Arman@Web Provides a detailed blueprint for using and customizing Lucene...a thorough introduction to the inner workings of what’s arguably the most popular open source search engine...loaded with code examples and emphasizes a hands-on approach to learning. -
Security Log Analysis Using Hadoop Harikrishna Annangi Harikrishna Annangi, [email protected]
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by St. Cloud State University St. Cloud State University theRepository at St. Cloud State Culminating Projects in Information Assurance Department of Information Systems 3-2017 Security Log Analysis Using Hadoop Harikrishna Annangi Harikrishna Annangi, [email protected] Follow this and additional works at: https://repository.stcloudstate.edu/msia_etds Recommended Citation Annangi, Harikrishna, "Security Log Analysis Using Hadoop" (2017). Culminating Projects in Information Assurance. 19. https://repository.stcloudstate.edu/msia_etds/19 This Starred Paper is brought to you for free and open access by the Department of Information Systems at theRepository at St. Cloud State. It has been accepted for inclusion in Culminating Projects in Information Assurance by an authorized administrator of theRepository at St. Cloud State. For more information, please contact [email protected]. Security Log Analysis Using Hadoop by Harikrishna Annangi A Starred Paper Submitted to the Graduate Faculty of St. Cloud State University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Information Assurance April, 2016 Starred Paper Committee: Dr. Dennis Guster, Chairperson Dr. Susantha Herath Dr. Sneh Kalia 2 Abstract Hadoop is used as a general-purpose storage and analysis platform for big data by industries. Commercial Hadoop support is available from large enterprises, like EMC, IBM, Microsoft and Oracle and Hadoop companies like Cloudera, Hortonworks, and Map Reduce. Hadoop is a scheme written in Java that allows distributed processes of large data sets across clusters of computers using programming models. A Hadoop frame work application works in an environment that provides storage and computation across clusters of computers. -
Building a Scalable Index and a Web Search Engine for Music on the Internet Using Open Source Software
Department of Information Science and Technology Building a Scalable Index and a Web Search Engine for Music on the Internet using Open Source software André Parreira Ricardo Thesis submitted in partial fulfillment of the requirements for the degree of Master in Computer Science and Business Management Advisor: Professor Carlos Serrão, Assistant Professor, ISCTE-IUL September, 2010 Acknowledgments I should say that I feel grateful for doing a thesis linked to music, an art which I love and esteem so much. Therefore, I would like to take a moment to thank all the persons who made my accomplishment possible and hence this is also part of their deed too. To my family, first for having instigated in me the curiosity to read, to know, to think and go further. And secondly for allowing me to continue my studies, providing the environment and the financial means to make it possible. To my classmate André Guerreiro, I would like to thank the invaluable brainstorming, the patience and the help through our college years. To my friend Isabel Silva, who gave me a precious help in the final revision of this document. Everyone in ADETTI-IUL for the time and the attention they gave me. Especially the people over Caixa Mágica, because I truly value the expertise transmitted, which was useful to my thesis and I am sure will also help me during my professional course. To my teacher and MSc. advisor, Professor Carlos Serrão, for embracing my will to master in this area and for being always available to help me when I needed some advice. -
Apache Lucene Searching the Web and Everything Else
Apache Lucene Searching the Web and Everything Else Daniel Naber Mindquarry GmbH ID 380 2 AGENDA > What's a search engine > Lucene Java – Features – Code example > Solr – Features – Integration > Nutch – Features – Usage example > Conclusion and alternative solutions 3 About the Speaker > Studied computational linguistics > Java developer > Worked 3.5 years for an Enterprise Search company (using Lucene Java) > Now at Mindquarry, creators on an Open Source Collaboration Software (Mindquarry uses Solr) 4 Question: What is a Search Engine? > Answer: A software that – builds an index on text – answers queries using that index “But we have a database already“ – A search engine offers Scalability Relevance Ranking Integrates different data sources (email, web pages, files, database, ...) 5 What is a search engine? (cont.) > Works on words, not on substrings auto != automatic, automobile > Indexing process: – Convert document – Extract text and meta data – Normalize text – Write (inverted) index – Example: Document 1: “Apache Lucene at Jazoon“ Document 2: “Jazoon conference“ Index: apache -> 1 conference -> 2 jazoon -> 1, 2 lucene -> 1 6 Apache Lucene Overview > Lucene Java 2.2 – Java library > Solr 1.2 – http-based index and search server > Nutch 0.9 – Internet search engine software > http://lucene.apache.org 7 Lucene Java > Java library for indexing and searching > No dependencies (not even a logging framework) > Works with Java 1.4 or later > Input for indexing: Document objects – Each document: set of Fields, field name: field content (plain text) > Input for searching: query strings or Query objects > Stores its index as files on disk > No document converters > No web crawler 8 Lucene Java Users > IBM OmniFind Yahoo! Edition > technorati.com > Eclipse > Furl > Nuxeo ECM > Monster.com > .. -
Magnify Search Security and Administration Release 8.2 Version 04
Magnify Search Security and Administration Release 8.2 Version 04 April 08, 2019 Active Technologies, EDA, EDA/SQL, FIDEL, FOCUS, Information Builders, the Information Builders logo, iWay, iWay Software, Parlay, PC/FOCUS, RStat, Table Talk, Web390, WebFOCUS, WebFOCUS Active Technologies, and WebFOCUS Magnify are registered trademarks, and DataMigrator and Hyperstage are trademarks of Information Builders, Inc. Adobe, the Adobe logo, Acrobat, Adobe Reader, Flash, Adobe Flash Builder, Flex, and PostScript are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States and/or other countries. Due to the nature of this material, this document refers to numerous hardware and software products by their trademarks. In most, if not all cases, these designations are claimed as trademarks or registered trademarks by their respective companies. It is not this publisher's intent to use any of these names generically. The reader is therefore cautioned to investigate all claimed trademark rights before using any of these names other than to refer to the product described. Copyright © 2019, by Information Builders, Inc. and iWay Software. All rights reserved. Patent Pending. This manual, or parts thereof, may not be reproduced in any form without the written permission of Information Builders, Inc. Contents Preface ......................................................................... 7 Conventions ......................................................................... 7 Related Publications ................................................................. -
Enterprise Search Technology Using Solr and Cloud Padmavathy Ravikumar Governors State University
Governors State University OPUS Open Portal to University Scholarship All Capstone Projects Student Capstone Projects Spring 2015 Enterprise Search Technology Using Solr and Cloud Padmavathy Ravikumar Governors State University Follow this and additional works at: http://opus.govst.edu/capstones Part of the Databases and Information Systems Commons Recommended Citation Ravikumar, Padmavathy, "Enterprise Search Technology Using Solr and Cloud" (2015). All Capstone Projects. 91. http://opus.govst.edu/capstones/91 For more information about the academic degree, extended learning, and certificate programs of Governors State University, go to http://www.govst.edu/Academics/Degree_Programs_and_Certifications/ Visit the Governors State Computer Science Department This Project Summary is brought to you for free and open access by the Student Capstone Projects at OPUS Open Portal to University Scholarship. It has been accepted for inclusion in All Capstone Projects by an authorized administrator of OPUS Open Portal to University Scholarship. For more information, please contact [email protected]. ENTERPRISE SEARCH TECHNOLOGY USING SOLR AND CLOUD By Padmavathy Ravikumar Masters Project Submitted in partial fulfillment of the requirements For the Degree of Master of Science, With a Major in Computer Science Governors State University University Park, IL 60484 Fall 2014 ENTERPRISE SEARCH TECHNOLOGY USING SOLR AND CLOUD 2 Abstract Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database in9tegration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. -
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 -
Natural Language Processing Technique for Information Extraction and Analysis
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) Volume 2, Issue 8, August 2015, PP 32-40 ISSN 2349-4840 (Print) & ISSN 2349-4859 (Online) www.arcjournals.org Natural Language Processing Technique for Information Extraction and Analysis T. Sri Sravya1, T. Sudha2, M. Soumya Harika3 1 M.Tech (C.S.E) Sri Padmavati Mahila Visvavidyalayam (Women’s University), School of Engineering and Technology, Tirupati. [email protected] 2 Head (I/C) of C.S.E & IT Sri Padmavati Mahila Visvavidyalayam (Women’s University), School of Engineering and Technology, Tirupati. [email protected] 3 M. Tech C.S.E, Assistant Professor, Sri Padmavati Mahila Visvavidyalayam (Women’s University), School of Engineering and Technology, Tirupati. [email protected] Abstract: In the current internet era, there are a large number of systems and sensors which generate data continuously and inform users about their status and the status of devices and surroundings they monitor. Examples include web cameras at traffic intersections, key government installations etc., seismic activity measurement sensors, tsunami early warning systems and many others. A Natural Language Processing based activity, the current project is aimed at extracting entities from data collected from various sources such as social media, internet news articles and other websites and integrating this data into contextual information, providing visualization of this data on a map and further performing co-reference analysis to establish linkage amongst the entities. Keywords: Apache Nutch, Solr, crawling, indexing 1. INTRODUCTION In today’s harsh global business arena, the pace of events has increased rapidly, with technological innovations occurring at ever-increasing speed and considerably shorter life cycles. -
IBM Cloudant: Database As a Service Fundamentals
Front cover IBM Cloudant: Database as a Service Fundamentals Understand the basics of NoSQL document data stores Access and work with the Cloudant API Work programmatically with Cloudant data Christopher Bienko Marina Greenstein Stephen E Holt Richard T Phillips ibm.com/redbooks Redpaper Contents Notices . 5 Trademarks . 6 Preface . 7 Authors. 7 Now you can become a published author, too! . 8 Comments welcome. 8 Stay connected to IBM Redbooks . 9 Chapter 1. Survey of the database landscape . 1 1.1 The fundamentals and evolution of relational databases . 2 1.1.1 The relational model . 2 1.1.2 The CAP Theorem . 4 1.2 The NoSQL paradigm . 5 1.2.1 ACID versus BASE systems . 7 1.2.2 What is NoSQL? . 8 1.2.3 NoSQL database landscape . 9 1.2.4 JSON and schema-less model . 11 Chapter 2. Build more, grow more, and sleep more with IBM Cloudant . 13 2.1 Business value . 15 2.2 Solution overview . 16 2.3 Solution architecture . 18 2.4 Usage scenarios . 20 2.5 Intuitively interact with data using Cloudant Dashboard . 21 2.5.1 Editing JSON documents using Cloudant Dashboard . 22 2.5.2 Configuring access permissions and replication jobs within Cloudant Dashboard. 24 2.6 A continuum of services working together on cloud . 25 2.6.1 Provisioning an analytics warehouse with IBM dashDB . 26 2.6.2 Data refinement services on-premises. 30 2.6.3 Data refinement services on the cloud. 30 2.6.4 Hybrid clouds: Data refinement across on/off–premises. 31 Chapter 3. -
Final Report CS 5604: Information Storage and Retrieval
Final Report CS 5604: Information Storage and Retrieval Solr Team Abhinav Kumar, Anand Bangad, Jeff Robertson, Mohit Garg, Shreyas Ramesh, Siyu Mi, Xinyue Wang, Yu Wang January 16, 2018 Instructed by Professor Edward A. Fox Virginia Polytechnic Institute and State University Blacksburg, VA 24061 1 Abstract The Digital Library Research Laboratory (DLRL) has collected over 1.5 billion tweets and millions of webpages for the Integrated Digital Event Archiving and Library (IDEAL) and Global Event Trend Archive Research (GETAR) projects [6]. We are using a 21 node Cloudera Hadoop cluster to store and retrieve this information. One goal of this project is to expand the data collection to include more web archives and geospatial data beyond what previously had been collected. Another important part in this project is optimizing the current system to analyze and allow access to the new data. To accomplish these goals, this project is separated into 6 parts with corresponding teams: Classification (CLA), Collection Management Tweets (CMT), Collection Management Webpages (CMW), Clustering and Topic Analysis (CTA), Front-end (FE), and SOLR. This report describes the work completed by the SOLR team which improves the current searching and storage system. We include the general architecture and an overview of the current system. We present the part that Solr plays within the whole system with more detail. We talk about our goals, procedures, and conclusions on the improvements we made to the current Solr system. This report also describes how we coordinate with other teams to accomplish the project at a higher level. Additionally, we provide manuals for future readers who might need to replicate our experiments. -
Apache Lucene™ Integration Reference Guide
Hibernate Search Apache Lucene™ Integration Reference Guide 3.3.0.Final Preface ............................................................................................................................ vii 1. Getting started ............................................................................................................. 1 1.1. System Requirements ......................................................................................... 1 1.2. Using Maven ...................................................................................................... 2 1.3. Configuration ...................................................................................................... 3 1.4. Indexing ............................................................................................................. 7 1.5. Searching ........................................................................................................... 7 1.6. Analyzer ............................................................................................................. 8 1.7. What's next ...................................................................................................... 10 2. Architecture ............................................................................................................... 11 2.1. Overview .......................................................................................................... 11 2.2. Back end ......................................................................................................... -
Building a Search Engine for the Cuban Web
Building a Search Engine for the Cuban Web Jorge Luis Betancourt Search/Crawl Engineer NOVEMBER 16-18, 2016 • SEVILLE, SPAIN Who am I 01 Jorge Luis Betancourt González Search/Crawl Engineer Apache Nutch Committer & PMC Apache Solr/ES enthusiast 2 Agenda • Introduction & motivation • Technologies used • Customizations • Conclusions and future work 3 Introduction / Motivation Cuba Internet Intranet Global search engines can’t access documents hosted the Cuban Intranet 4 Writing your own web search engine from scratch? or … 5 Common search engine features 1 Web search: HTML & documents (PDF, DOC) • highlighting • suggestions • filters (facets) • autocorrection 2 Image search (size, format, color, objects) • thumbnails • show metadata • filters (facets) • match text with images 3 News search (alerting, notifications) • near real time • email, push, SMS 6 How to fulfill these requirements? store query At the core a search engine: stores some information a retrieve this information when a question is received 7 Open Source to the rescue … crawler 1 Index Server 2 web interface 3 8 Apache Nutch Nutch is a well matured, production ready “ Web crawler. Enables fine grained configuration, relying on Apache Hadoop™ data structures, which are great for batch processing. 9 Apache Nutch • Highly scalable • Highly extensible • Pluggable parsing protocols, storage, indexing, scoring, • Active community • Apache License 10 Apache Solr TOTAL DOWNLOADS 8M+ MONTHLY DOWNLOADS 250,000+ • Apache License • Great community • Highly modular • Stability / Scalability