10 keys to Solr's Future

•

2 gefällt mir•1,451 views

lucenerevolution

Technologie Design

10 KEYS TO SOLR’S FUTURE
Grant Ingersoll
Twitter: @gsingers

CTO, LucidWorks

3

http://mybloodybikeblog.com/wp-content/uploads/2013/01/you-are-here.jpg

Lucid Solr Modules

Splunk for Solr – Real-time Solr Monitoring and Data Joins

SPM – Scalable Performance Monitor by Sematext

Documill Visual Search

Zoomdata - Faceted Dashboarding for Solr

LogStash for Solr – Simple, scalable log analysis with Solr

But where should we be going?

http://us.123rf.com/400wm/400/400/chrisgloster/chrisgloster1005/ch
risgloster100500003/6952941-dense-high-rise-apartments-flats-inhong-kong.jpg

In Index Analytics and Machine Learning

https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQU2soI0L6BoomSYoXlviuQaBLKjUYWWWOz6YzXRiF3-jXZTNQQ44i1Mqa

Modularization

http://www.neatoshop.com/product/Time-y-Wimey?tag=104075

http://cdn.all-that-is-interesting.com/wordpress/wpcontent/uploads/2013/07/lenticular-clouds-over-sandwich-islands.jpg

http://bit.ly/19XgyNK

Weitere ähnliche Inhalte

Ähnlich wie 10 keys to Solr's Future

1. BigQueryを中心にした ML datapipelineの概要

1. BigQueryを中心にした ML datapipelineの概要

1. BigQueryを中心にした ML datapipelineの概要

幸太朗岩澤

Fujitsu IT Future 2013 : Alignement de l'IT avec les contraintes Business, té...

Fujitsu IT Future 2013 : Alignement de l'IT avec les contraintes Business, té...

Fujitsu IT Future 2013 : Alignement de l'IT avec les contraintes Business, té...

Splunk AI & Machine Learning Roundtable 2019 - Zurich

Splunk AI & Machine Learning Roundtable 2019 - Zurich

Splunk AI & Machine Learning Roundtable 2019 - Zurich

Applying Transfer Learning in TensorFlow

Applying Transfer Learning in TensorFlow

Applying Transfer Learning in TensorFlow

Sping roo intro_2013

Sping roo intro_2013

Sping roo intro_2013

.Net development with Azure Machine Learning (AzureML) Nov 2014

.Net development with Azure Machine Learning (AzureML) Nov 2014

.Net development with Azure Machine Learning (AzureML) Nov 2014

Mark Tabladillo

FeedForward, Metadata & Digital Repositories SIG, Feb 2008

FeedForward, Metadata & Digital Repositories SIG, Feb 2008

FeedForward, Metadata & Digital Repositories SIG, Feb 2008

Microsoft provides several technologies in and around SQL Server which can be used for casual to serious data science. This presentation provides an authoritative overview of five major options: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, Microsoft Azure Machine Learning, and F#. Also included are tips on working with Python and R. These technologies have been used by the presenter in various companies and industries.

Microsoft Data Science Technologies: Architecture Edition 201509

Microsoft Data Science Technologies: Architecture Edition 201509

Microsoft Data Science Technologies: Architecture Edition 201509

Mark Tabladillo

DevOps - Keepers of the Keys to the Kingdom

DevOps - Keepers of the Keys to the Kingdom

DevOps - Keepers of the Keys to the Kingdom

DevOpsDays Tel Aviv

Visitation time scheduling

Visitation time scheduling

Visitation time scheduling

Alfonso de la Fuente Ruiz

Scaling Gilt: from monolith ruby app to micro service scala service architecture

Scaling Gilt: from monolith ruby app to micro service scala service architecture

Scaling Gilt: from monolith ruby app to micro service scala service architecture

Gilt Tech Talks

Gilt from monolith ruby app to microservice scala service architecture

Gilt from monolith ruby app to microservice scala service architecture

Gilt from monolith ruby app to microservice scala service architecture

Jonathan (Yoni) Goldberg

Machine Learning Streams with Spark 1.0

Machine Learning Streams with Spark 1.0

Machine Learning Streams with Spark 1.0

5 Emerging Technologies that Transform the Experience

5 Emerging Technologies that Transform the Experience

5 Emerging Technologies that Transform the Experience

Mike fowler - Getting started with machine learning (london 2019)

Mike fowler - Getting started with machine learning (london 2019)

Mike fowler - Getting started with machine learning (london 2019)

With the successful implementation of Large Language Models (LLMs) in chatbots like ChatGPT, there is growing attention on foundation models, which are anticipated to serve as core components in the development of future AI systems. Yet, systematic exploration into the design of foundation model-based systems, particularly concerning risk management, trust, and trustworthiness, remains limited. In this talk, I propose the challenges and initial approaches in both architecting LLM-based systems and how LLM systems have an impact on software engineering. I point to some initial directions such as architecting as a process of understanding (rather than designing/building), setting and trade-offing guardrails (rather than quality attributes), and radical observability.

Software Architecture for Foundation Model-Based Systems

Software Architecture for Foundation Model-Based Systems

Software Architecture for Foundation Model-Based Systems

Machine Learning (ML) is an exciting field that Cloud Computing has helped to accelerate. AWS has played a big part in this with it’s continually expanding range of services from the simply named Machine Learning through to SageMaker. But how do you get started? Thankfully you don’t need to become an expert in linear algebra or statistics, all you need to begin is good idea of the life-cycle of a ML project and a passing familiarity with these AWS services. In this talk we’ll outline a typical ML project and review services such as SageMaker and Rekognition so that you can begin to make use of them in your own projects.

Getting Started with Machine Learning on AWS

Getting Started with Machine Learning on AWS

Getting Started with Machine Learning on AWS

AWSの提供するioTソリューションと実例

AWSの提供するioTソリューションと実例

AWSの提供するioTソリューションと実例

Takashi Koyanagawa

Challenges in an E-Commerce Catalogue with SQL; How Mongo helps

Challenges in an E-Commerce Catalogue with SQL; How Mongo helps

Challenges in an E-Commerce Catalogue with SQL; How Mongo helps

Mongo @ homeshop18

Mongo @ homeshop18

Mongo @ homeshop18

Ähnlich wie 10 keys to Solr's Future (20)

1. BigQueryを中心にした ML datapipelineの概要

1. BigQueryを中心にした ML datapipelineの概要

1. BigQueryを中心にした ML datapipelineの概要

Fujitsu IT Future 2013 : Alignement de l'IT avec les contraintes Business, té...

Fujitsu IT Future 2013 : Alignement de l'IT avec les contraintes Business, té...

Fujitsu IT Future 2013 : Alignement de l'IT avec les contraintes Business, té...

Splunk AI & Machine Learning Roundtable 2019 - Zurich

Splunk AI & Machine Learning Roundtable 2019 - Zurich

Splunk AI & Machine Learning Roundtable 2019 - Zurich

Applying Transfer Learning in TensorFlow

Applying Transfer Learning in TensorFlow

Applying Transfer Learning in TensorFlow

Sping roo intro_2013

Sping roo intro_2013

Sping roo intro_2013

.Net development with Azure Machine Learning (AzureML) Nov 2014

.Net development with Azure Machine Learning (AzureML) Nov 2014

.Net development with Azure Machine Learning (AzureML) Nov 2014

FeedForward, Metadata & Digital Repositories SIG, Feb 2008

FeedForward, Metadata & Digital Repositories SIG, Feb 2008

FeedForward, Metadata & Digital Repositories SIG, Feb 2008

Microsoft Data Science Technologies: Architecture Edition 201509

Microsoft Data Science Technologies: Architecture Edition 201509

Microsoft Data Science Technologies: Architecture Edition 201509

DevOps - Keepers of the Keys to the Kingdom

DevOps - Keepers of the Keys to the Kingdom

DevOps - Keepers of the Keys to the Kingdom

Visitation time scheduling

Visitation time scheduling

Visitation time scheduling

Scaling Gilt: from monolith ruby app to micro service scala service architecture

Scaling Gilt: from monolith ruby app to micro service scala service architecture

Scaling Gilt: from monolith ruby app to micro service scala service architecture

Gilt from monolith ruby app to microservice scala service architecture

Gilt from monolith ruby app to microservice scala service architecture

Gilt from monolith ruby app to microservice scala service architecture

Machine Learning Streams with Spark 1.0

Machine Learning Streams with Spark 1.0

Machine Learning Streams with Spark 1.0

5 Emerging Technologies that Transform the Experience

5 Emerging Technologies that Transform the Experience

5 Emerging Technologies that Transform the Experience

Mike fowler - Getting started with machine learning (london 2019)

Mike fowler - Getting started with machine learning (london 2019)

Mike fowler - Getting started with machine learning (london 2019)

Software Architecture for Foundation Model-Based Systems

Software Architecture for Foundation Model-Based Systems

Software Architecture for Foundation Model-Based Systems

Getting Started with Machine Learning on AWS

Getting Started with Machine Learning on AWS

Getting Started with Machine Learning on AWS

AWSの提供するioTソリューションと実例

AWSの提供するioTソリューションと実例

AWSの提供するioTソリューションと実例

Challenges in an E-Commerce Catalogue with SQL; How Mongo helps

Challenges in an E-Commerce Catalogue with SQL; How Mongo helps

Challenges in an E-Commerce Catalogue with SQL; How Mongo helps

Mongo @ homeshop18

Mongo @ homeshop18

Mongo @ homeshop18

Mehr von lucenerevolution

Presented by Markus Klose, Search + Big Data Consultant SHI Elektronische Medien GmbH at Lucene/Solr Revolution 2013 Dublin Kibana4Solr is search-driven, scalable, browser based and extremely user friendly (also for non-technical users). Logs are everywhere. Any device, system or human can potentially produce a huge amount of information saved in logs. The amount of available logs and their semi-structured nature make a meaningful processing in real-time quite a difficult task. Thus, valuable business insights stored in logs might be not found. Kibana4Solr is a search-driven approach to handle that challenge. It offers user-friendly and browser-based dashboard which can be easily customized to particular needs. In the session the Kibana4Solr will be introduced. Some light will be shed on the architectural features of Kibana4Solr. Some ideas will be given in terms of possible business uses cases. And finally a live demo of Kibana4Solr will be shown. Configure

State of the Art Logging. Kibana4Solr is Here!

State of the Art Logging. Kibana4Solr is Here!

State of the Art Logging. Kibana4Solr is Here!

lucenerevolution

Search at Twitter

Search at Twitter

Search at Twitter

lucenerevolution

Presented by Daniel Beach, Search Application Developer, OpenSource Connections Solr is a powerful search engine, but creating a custom user interface can be daunting. In this fast paced session I will present an overview of how to implement a client-side search application using Solr. Using open-source frameworks like SpyGlass (to be released in September) can be a powerful way to jumpstart your development by giving you out-of-the box results views with support for faceting, autocomplete, and detail views. During this talk I will also demonstrate how we have built and deployed lightweight applications that are able to be performant under large user loads, with minimal server resources.

Building Client-side Search Applications with Solr

Building Client-side Search Applications with Solr

Building Client-side Search Applications with Solr

lucenerevolution

Presented by Timothy Potter, Founder, Text Centrix Storm is a real-time distributed computation system used to process massive streams of data. Many organizations are turning to technologies like Storm to complement batch-oriented big data technologies, such as Hadoop, to deliver time-sensitive analytics at scale. This talk introduces on an emerging architectural pattern of integrating Solr and Storm to process big data in real time. There are a number of natural integration points between Solr and Storm, such as populating a Solr index or supplying data to Storm using Solr’s real-time get support. In this session, Timothy will cover the basic concepts of Storm, such as spouts and bolts. He’ll then provide examples of how to integrate Solr into Storm to perform large-scale indexing in near real-time. In addition, we'll see how to embed Solr in a Storm bolt to match incoming tuples against pre-configured queries, commonly known as percolator. Attendees will come away from this presentation with a good introduction to stream processing technologies and several real-world use cases of how to integrate Solr with Storm.

Integrate Solr with real-time stream processing applications

Integrate Solr with real-time stream processing applications

Integrate Solr with real-time stream processing applications

lucenerevolution

Configure your Solr cluster to handle hundreds of millions of documents without even noticing, handle queries in milliseconds, use Near Real Time indexing and searching with document versioning. Scale your cluster both horizontally and vertically by using shards and replicas. In this session you'll learn how to make your indexing process blazing fast and make your queries efficient even with large amounts of data in your collections. You'll also see how to optimize your queries to leverage caches as much as your deployment allows and how to observe your cluster with Solr administration panel, JMX, and third party tools. Finally, learn how to make changes to already deployed collections —split their shards and alter their schema by using Solr API.

Scaling Solr with SolrCloud

Scaling Solr with SolrCloud

Scaling Solr with SolrCloud

lucenerevolution

Presented by Rafal Kuć, Consultant and Software engineer, , Sematext Group, Inc. Even though Solr can run without causing any troubles for long periods of time it is very important to monitor and understand what is happening in your cluster. In this session you will learn how to use various tools to monitor how Solr is behaving at a high level, but also on Lucene, JVM, and operating system level. You'll see how to react to what you see and how to make changes to configuration, index structure and shards layout using Solr API. We will also discuss different performance metrics to which you ought to pay extra attention. Finally, you'll learn what to do when things go awry - we will share a few examples of troubleshooting and then dissect what was wrong and what had to be done to make things work again.

Administering and Monitoring SolrCloud Clusters

Administering and Monitoring SolrCloud Clusters

Administering and Monitoring SolrCloud Clusters

lucenerevolution

In a recent project with the United States Patent and Trademark Office, Opensource Connections was asked to prototype the next generation of patent search - using Solr and Lucene. An important aspect of this project was the implementation of BRS, a specialized search syntax used by patent examiners during the examination process. In this fast paced session we will relate our experiences and describe how we used a combination of Parboiled (a Parser Expression Grammar [PEG] parser), Lucene Queries and SpanQueries, and an extension of Solr's QParserPlugin to build BRS search functionality in Solr. First we will characterize the patent search problem and then define the BRS syntax itself. We will then introduce the Parboiled parser and discuss various considerations that one must make when designing a syntax parser. Following this we will describe the methodology used to implement the search functionality in Lucene/Solr. Finally, we will include an overview our syntactic and semantic testing strategies. The audience will leave this session with an understanding of how Solr, Lucene, and Parboiled may be used to implement their own custom search parser.

Implementing a Custom Search Syntax using Solr, Lucene, and Parboiled

Implementing a Custom Search Syntax using Solr, Lucene, and Parboiled

Implementing a Custom Search Syntax using Solr, Lucene, and Parboiled

lucenerevolution

Many of us tend to hate or simply ignore logs, and rightfully so: they’re typically hard to find, difficult to handle, and are cryptic to the human eye. But can we make logs more valuable and more usable if we index them in Solr, so we can search and run real-time statistics on them? Indeed we can, and in this session you’ll learn how to make that happen. In the first part of the session we’ll explain why centralized logging is important, what valuable information one can extract from logs, and we’ll introduce the leading tools from the logging ecosystems everyone should be aware of - from syslog and log4j to LogStash and Flume. In the second part we’ll teach you how to use these tools in tandem with Solr. We’ll show how to use Solr in a SolrCloud setup to index large volumes of logs continuously and efficiently. Then, we'll look at how to scale the Solr cluster as your data volume grows. Finally, we'll see how you can parse your unstructured logs and convert them to nicely structured Solr documents suitable for analytical queries.

Using Solr to Search and Analyze Logs

Using Solr to Search and Analyze Logs

Using Solr to Search and Analyze Logs

lucenerevolution

Enhancing relevancy through personalization & semantic search

Enhancing relevancy through personalization & semantic search

Enhancing relevancy through personalization & semantic search

lucenerevolution

Building real-time notification systems is often limited to basic filtering and pattern matching against incoming records. Allowing users to query incoming documents using Solr's full range of capabilities is much more powerful. In our environment we needed a way to allow for tens of thousands of such query subscriptions, meaning we needed to find a way to distribute the query processing in the cloud. By creating in-memory Lucene indices from our Solr configuration, we were able to parallelize our queries across our cluster. To achieve this distribution, we wrapped the processing in a Storm topology to provide a flexible way to scale and manage our infrastructure. This presentation will describe our experiences creating this distributed, real-time inverted search notification framework.

Real-time Inverted Search in the Cloud Using Lucene and Storm

Real-time Inverted Search in the Cloud Using Lucene and Storm

Real-time Inverted Search in the Cloud Using Lucene and Storm

lucenerevolution

Like many Web-Applications in the past, the Solr Admin UI up until 4.0 was entirely server based. It used separate code on the server to generate their Dashboards, Overviews and Statistics. All that code had to be maintained and still ... you weren't really able to use that kind of data for the things you needed it for. It was wrapped into HTML, most of the time difficult to extract and changed the structure from time to time w/o announcement. After a short look back, we're going to look into the current state of the Solr Admin UI - a client-side application, running completely in your browser. We'll see how it works, where it gets its data from and how you can get the very same data and wire that into your own custom applications, dashboards and/oder monitoring systems.

Solr's Admin UI - Where does the data come from?

Solr's Admin UI - Where does the data come from?

Solr's Admin UI - Where does the data come from?

lucenerevolution

Schemaless Solr and the Solr Schema REST API

Schemaless Solr and the Solr Schema REST API

Schemaless Solr and the Solr Schema REST API

lucenerevolution

Presented by Renaud Delbru, Co-Founder, SindiceTech In this presentation, we will discuss how Lucene and Solr can be used for very efficient search of tree-shaped schemaless document, e.g. JSON or XML, and can be then made to address both graph and relational data search. We will discuss the capabilities of SIREn, a Lucene/Solr plugin we have developed to deal with huge collections of tree-shaped schemaless documents, and how SIREn is built using Lucene extensibility capabilities (Analysis, Codec, Flexible Query Parser). We will compare it with Lucene's BlockJoin Query API in nested schemaless data intensive scenarios. We will then go through use cases that show how relational or graph data can be turned into JSON documents using Hadoop and Pig, and how this can be used in conjunction with SIREn to create relational faceting systems with unprecedented performance. Take-away lessons from this session will be awareness about using Lucene/Solr and Hadoop for relational and graph data search, as well as the awareness that it is now possible to have relational faceted browsers with sub-second response time on commodity hardware.

High Performance JSON Search and Relational Faceted Browsing with Lucene

High Performance JSON Search and Relational Faceted Browsing with Lucene

High Performance JSON Search and Relational Faceted Browsing with Lucene

lucenerevolution

In this session we will show how to build a text classifier using the Apache Lucene/Solr with libSVM libraries. We classify our corpus of job offers into a number of predefined categories. Each indexed document (a job offer) then belongs to zero, one or more categories. Known machine learning techniques for text classification include naïve bayes model, logistic regression, neural network, support vector machine (SVM), etc. We use Lucene/Solr to construct the features vector. Then we use the libsvm library known as the reference implementation of the SVM model to classify the document. We construct as many one-vs-all svm classifiers as there are classes in our setting, then using the Hadoop MapReduce Framework we reconcile the result of our classifiers. The end result is a scalable multi-class classifier. Finally we outline how the classifier is used to enrich basic solr keyword search.

Text Classification with Lucene/Solr, Apache Hadoop and LibSVM

Text Classification with Lucene/Solr, Apache Hadoop and LibSVM

Text Classification with Lucene/Solr, Apache Hadoop and LibSVM

lucenerevolution

Faceted search is a powerful technique to let users easily navigate the search results. It can also be used to develop rich user interfaces, which give an analyst quick insights about the documents space. In this session I will introduce the Facets module, how to use it, under-the-hood details as well as optimizations and best practices. I will also describe advanced faceted search capabilities with Lucene Facets.

Faceted Search with Lucene

Faceted Search with Lucene

Faceted Search with Lucene

lucenerevolution

As part of their work with large media monitoring companies, Flax has developed a technique for applying tens of thousands of stored Lucene queries to a document in under a second. We'll talk about how we built intelligent filters to reduce the number of actual queries applied and how we extended Lucene to extract the exact hit positions of matches, the challenges of implementation, and how it can be used, including applications that monitor hundreds of thousands of news stories every day.

Turning search upside down

Turning search upside down

Turning search upside down

lucenerevolution

Presented by Xavier Sanchez Loro, Ph.D, Trovit Search SL This session aims to explain the implementation and use case for spellchecking in Trovit search engine. Trovit is a classified ads search engine supporting several different sites, one for each on country and vertical. Our search engine supports multiple indexes in multiple languages, each with several millions of indexed ads. Those indexes are segmented in several different sites depending on the type of ads (homes, cars, rentals, products, jobs and deals). We have developed a multi-language spellchecking system using solr and lucene in order to help our users to better find the desired ads and avoid the dreaded 0 results as much as possible. As such our goal is not pure orthographic correction, but also suggestion of correct searches for a certain site.

Spellchecking in Trovit: Implementing a Contextual Multi-language Spellchecke...

Spellchecking in Trovit: Implementing a Contextual Multi-language Spellchecke...

Spellchecking in Trovit: Implementing a Contextual Multi-language Spellchecke...

lucenerevolution

Shrinking the haystack wes caldwell - final

Shrinking the haystack wes caldwell - final

Shrinking the haystack wes caldwell - final

lucenerevolution

Presented by Mark Miller, Software Developer, Cloudera Apache Lucene/Solr committer Mark Miller talks about how Solr has been integrated into the Hadoop ecosystem to provide full text search at "Big Data" scale. This talk will give an overview of how Cloudera has tackled integrating Solr into the Hadoop ecosystem and highlights some of the design decisions and future plans. Learn how Solr is getting 'cozy' with Hadoop, which contributions are going to what project, and how you can take advantage of these integrations to use Solr efficiently at "Big Data" scale. Learn how you can run Solr directly on HDFS, build indexes with Map/Reduce, load Solr via Flume in 'Near Realtime' and much more.

The First Class Integration of Solr with Hadoop

The First Class Integration of Solr with Hadoop

The First Class Integration of Solr with Hadoop

lucenerevolution

Presented by Rajini Maski, Senior Software Engineer, Happiest Minds Technologies An important problem with document-search in any content management system (CMS) is the handling of permission-based search requests for each user. In this session, we present an algorithm and framework that allows the Search Engine to plainly index both public and privileged documents without any early binding overhead—thus enforcing document-level security policies only at the time of search. With our late-binding approach for ACL (access control lists) and some custom components, we have achieved reduction in search-time overhead. We will also discuss the order of complexity and execution time for the search overhead.

A Novel methodology for handling Document Level Security in Search Based Appl...

A Novel methodology for handling Document Level Security in Search Based Appl...

A Novel methodology for handling Document Level Security in Search Based Appl...

lucenerevolution

Mehr von lucenerevolution (20)

State of the Art Logging. Kibana4Solr is Here!

State of the Art Logging. Kibana4Solr is Here!

State of the Art Logging. Kibana4Solr is Here!

Search at Twitter

Search at Twitter

Search at Twitter

Building Client-side Search Applications with Solr

Building Client-side Search Applications with Solr

Building Client-side Search Applications with Solr

Integrate Solr with real-time stream processing applications

Integrate Solr with real-time stream processing applications

Integrate Solr with real-time stream processing applications

Scaling Solr with SolrCloud

Scaling Solr with SolrCloud

Scaling Solr with SolrCloud

Administering and Monitoring SolrCloud Clusters

Administering and Monitoring SolrCloud Clusters

Administering and Monitoring SolrCloud Clusters

Implementing a Custom Search Syntax using Solr, Lucene, and Parboiled

Implementing a Custom Search Syntax using Solr, Lucene, and Parboiled

Implementing a Custom Search Syntax using Solr, Lucene, and Parboiled

Using Solr to Search and Analyze Logs

Using Solr to Search and Analyze Logs

Using Solr to Search and Analyze Logs

Enhancing relevancy through personalization & semantic search

Enhancing relevancy through personalization & semantic search

Enhancing relevancy through personalization & semantic search

Real-time Inverted Search in the Cloud Using Lucene and Storm

Real-time Inverted Search in the Cloud Using Lucene and Storm

Real-time Inverted Search in the Cloud Using Lucene and Storm

Solr's Admin UI - Where does the data come from?

Solr's Admin UI - Where does the data come from?

Solr's Admin UI - Where does the data come from?

Schemaless Solr and the Solr Schema REST API

Schemaless Solr and the Solr Schema REST API

Schemaless Solr and the Solr Schema REST API

High Performance JSON Search and Relational Faceted Browsing with Lucene

High Performance JSON Search and Relational Faceted Browsing with Lucene

High Performance JSON Search and Relational Faceted Browsing with Lucene

Text Classification with Lucene/Solr, Apache Hadoop and LibSVM

Text Classification with Lucene/Solr, Apache Hadoop and LibSVM

Text Classification with Lucene/Solr, Apache Hadoop and LibSVM

Faceted Search with Lucene

Faceted Search with Lucene

Faceted Search with Lucene

Turning search upside down

Turning search upside down

Turning search upside down

Spellchecking in Trovit: Implementing a Contextual Multi-language Spellchecke...

Spellchecking in Trovit: Implementing a Contextual Multi-language Spellchecke...

Spellchecking in Trovit: Implementing a Contextual Multi-language Spellchecke...

Shrinking the haystack wes caldwell - final

Shrinking the haystack wes caldwell - final

Shrinking the haystack wes caldwell - final

The First Class Integration of Solr with Hadoop

The First Class Integration of Solr with Hadoop

The First Class Integration of Solr with Hadoop

A Novel methodology for handling Document Level Security in Search Based Appl...

A Novel methodology for handling Document Level Security in Search Based Appl...

A Novel methodology for handling Document Level Security in Search Based Appl...

Kürzlich hochgeladen

Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Join our latest Connector Corner webinar to discover how UiPath Integration Service revolutionizes API-centric automation in a 'Quote to Cash' process—and how that automation empowers businesses to accelerate revenue generation. A comprehensive demo will explore connecting systems, GenAI, and people, through powerful pre-built connectors designed to speed process cycle times. Speakers: James Dickson, Senior Software Engineer Charlie Greenberg, Host, Product Marketing Manager

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

This presentation explores the impact of HTML injection attacks on web applications, detailing how attackers exploit vulnerabilities to inject malicious code into web pages. Learn about the potential consequences of such attacks and discover effective mitigation strategies to protect your web applications from HTML injection vulnerabilities. for more information visit https://bostoninstituteofanalytics.org/category/cyber-security-ethical-hacking/

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

Boston Institute of Analytics

Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

The Digital Insurer

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Maria Levchenko

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

sudhanshuwaghmare1

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

Real Time Object Detection Using Open CV

Real Time Object Detection Using Open CV

Real Time Object Detection Using Open CV

Created by Mozilla Research in 2012 and now part of Linux Foundation Europe, the Servo project is an experimental rendering engine written in Rust. It combines memory safety and concurrency to create an independent, modular, and embeddable rendering engine that adheres to web standards. Stewardship of Servo moved from Mozilla Research to the Linux Foundation in 2020, where its mission remains unchanged. After some slow years, in 2023 there has been renewed activity on the project, with a roadmap now focused on improving the engine’s CSS 2 conformance, exploring Android support, and making Servo a practical embeddable rendering engine. In this presentation, Rakhi Sharma reviews the status of the project, our recent developments in 2023, our collaboration with Tauri to make Servo an easy-to-use embeddable rendering engine, and our plans for the future to make Servo an alternative web rendering engine for the embedded devices industry. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://ossna2024.sched.com/event/1aBNF/a-year-of-servo-reboot-where-are-we-now-rakhi-sharma-igalia

A Year of the Servo Reboot: Where Are We Now?

A Year of the Servo Reboot: Where Are We Now?

A Year of the Servo Reboot: Where Are We Now?

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Three things you will take away from the session: • How to run an effective tenant-to-tenant migration • Best practices for before, during, and after migration • Tips for using migration as a springboard to prepare for Copilot in Microsoft 365 Main ideas: Migration Overview: The presentation covers the current reality of cross-tenant migrations, the triggers, phases, best practices, and benefits of a successful tenant migration Considerations: When considering a migration, it is important to consider the migration scope, performance, customization, flexibility, user-friendly interface, automation, monitoring, support, training, scalability, data integrity, data security, cost, and licensing structure Next Wave: The next wave of change includes the launch of Copilot, which requires businesses to be prepared for upcoming changes related to Copilot and the cloud, and to consolidate data and tighten governance ShareGate: ShareGate can help with pre-migration analysis, configurable migration tool, and automated, end-user driven collaborative governance

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Histor y of HAM Radio presentation slide

Histor y of HAM Radio presentation slide

Histor y of HAM Radio presentation slide

Advantages of Hiring UIUX Design Service Providers for Your Business

Advantages of Hiring UIUX Design Service Providers for Your Business

Advantages of Hiring UIUX Design Service Providers for Your Business

Pixlogix Infotech

Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Enterprise Knowledge

The value of a flexible API Management solution for Open Banking Steve Melan, Manager for IT Innovation and Architecture - State's and Saving's Bank of Luxembourg Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

Boost PC performance: How more available memory can improve productivity

Boost PC performance: How more available memory can improve productivity

Boost PC performance: How more available memory can improve productivity

Principled Technologies

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

Remote DBA Services

Kürzlich hochgeladen (20)

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Real Time Object Detection Using Open CV

Real Time Object Detection Using Open CV

Real Time Object Detection Using Open CV

A Year of the Servo Reboot: Where Are We Now?

A Year of the Servo Reboot: Where Are We Now?

A Year of the Servo Reboot: Where Are We Now?

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Histor y of HAM Radio presentation slide

Histor y of HAM Radio presentation slide

Histor y of HAM Radio presentation slide

Advantages of Hiring UIUX Design Service Providers for Your Business

Advantages of Hiring UIUX Design Service Providers for Your Business

Advantages of Hiring UIUX Design Service Providers for Your Business

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Boost PC performance: How more available memory can improve productivity

Boost PC performance: How more available memory can improve productivity

Boost PC performance: How more available memory can improve productivity

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

10 keys to Solr's Future

1.

2. 10 KEYS TO SOLR’S FUTURE Grant Ingersoll Twitter: @gsingers CTO, LucidWorks

3. 3 http://mybloodybikeblog.com/wp-content/uploads/2013/01/you-are-here.jpg

4. Lucid Solr Modules

5. Splunk for Solr – Real-time Solr Monitoring and Data Joins

6. SPM – Scalable Performance Monitor by Sematext

7. Documill Visual Search

8. Zoomdata - Faceted Dashboarding for Solr

9. LogStash for Solr – Simple, scalable log analysis with Solr

10. But where should we be going?

11. http://us.123rf.com/400wm/400/400/chrisgloster/chrisgloster1005/ch risgloster100500003/6952941-dense-high-rise-apartments-flats-inhong-kong.jpg

12.

13. In Index Analytics and Machine Learning https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQU2soI0L6BoomSYoXlviuQaBLKjUYWWWOz6YzXRiF3-jXZTNQQ44i1Mqa

14. Modularization

15. http://www.neatoshop.com/product/Time-y-Wimey?tag=104075

16.

17.

18. http://cdn.all-that-is-interesting.com/wordpress/wpcontent/uploads/2013/07/lenticular-clouds-over-sandwich-islands.jpg

19.

20. http://bit.ly/19XgyNK