BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Pentabarf//Schedule 0.3//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALDESC;VALUE=TEXT:Search devroom X-WR-CALNAME;VALUE=TEXT:Search devroom X-WR-TIMEZONE;VALUE=TEXT:Europe/Brussels BEGIN:VEVENT METHOD:PUBLISH UID:8216@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T103000 DTEND:20190203T105500 SUMMARY:ElasticSearch Correctness and perfOrmance Validator DESCRIPTION:
Alright, you built an application to show off your impressive skills at data gathering and processing. Now you got data on ElasticSearch that you want to show, but your users may want to see too many data points and will shatter your DB performance. In this talk, we will present a project to formally measure the cost of queries before actually running them, and your app can decide, given a cost value, whether to launch a query or not.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/elasticsearch_correctness_performance_validator/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Santiago Saavedra":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:8774@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T110000 DTEND:20190203T115000 SUMMARY:Learning to Rank DESCRIPTION:Internet search has evolved from its early days. It has become smarter and morenatural, and people expect it to “just work.” But, anyone who has workedbehind-the-scenes with a search engine knows exactly how hard it is to get the“right” results to show up at the right time.
Not to mention, what happens when the trends change, when your users’ favoriteweirdly-shaped dinosaur isn’t a T-Rex anymore? Spending countless hours tuningthe boosts before your user can find their favorite two-legged tiny-armeddinosaur on the front page isn’t fun. What is cool is using Learning to Rank toautomate the process! In this talk, you will learn how Learning to Rank worksand how you can use it in Apache Solr — all from the Bloomberg team that builtand implemented it in the first place.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/learning_to_rank/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Sambhav Kothari":invalid:nomail ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Diego Ceccarelli":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:8723@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T120000 DTEND:20190203T122500 SUMMARY:From table to index (and back) with Hibernate Search 6 DESCRIPTION:On one side, Elasticsearch. It scales, has great support for full-text search, and many features you like.On the other side, a relational database. It has transactions, relational capabilities, implements standards, and lots of developers are familiar with it.Each is a great datastore targeting specific needs. What if you have many needs? What if you want both? Transactions, relations and scale; full-text search and SQL. Preferably without headaches.
Enters Hibernate Search. This Java library allows to define a mapping from Hibernate ORM entities to Elasticsearch documents, to transparently index entities as they are persisted in the ORM, and to conveniently query the index through APIs that make the most of a mixed entity/document model.Doing so, it solves the problems that arise when synchronizing data from a relational database to Elasticsearch:
In this talk, I will demonstrate how Hibernate Search 6, the new major version of Hibernate Search currently in development, can be used in an application based on Hibernate ORM.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/hibernate_search_6/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Yoann Rodiere":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:8782@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T123000 DTEND:20190203T132000 SUMMARY:A Deepdive into Tantivy DESCRIPTION:Tantivy is a search engine library, akin to Lucene but for Rust.
In this talk, we will walk through the building blocks that make a scalable full-text search engine. While this talk will be centered on tantivy, most of the concepts introduced should apply to other inverted-list search engines like Lucene.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/deepdive_tantivy/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Paul Masurel":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:8825@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T133000 DTEND:20190203T135500 SUMMARY:Apache Lucene and Apache Solr 8 DESCRIPTION:Spring 2019 will be the time for a new major release of Apache Lucene and the well-known search server Apache Solr. Since Lucene 7 a lot new features have been developed, mainly a new way to short circuit query execution if the total number of hits is not needed. This may improve query execution for common full text search use cases enormously. The talk will also present other new features and changes like change to a more standard BM25 implementation or optimizations for Java 9 and later Java versions using MR-JAR files.The second part of this talk will quickly cover news in Apache Solr: Solr 8 now also uses HTTP/2 for its cloud communication.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/apache_lucene_solr_8/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Uwe Schindler":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:8758@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T140000 DTEND:20190203T142500 SUMMARY:Super-speedy scoring in Lucene 8 DESCRIPTION:Lucene 8 will have some remarkable speed-ups when it comes to querying across large datasets. In this talk I will describe how this has been implemented, from new data structures through to changes in the scoring API, and the trade-offs required to make them possible.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/super_speedy_scoring_lucene/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Alan Woodward":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:8785@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T143000 DTEND:20190203T145500 SUMMARY:Lucene Upgrade in Jira 8.0 DESCRIPTION:Jira 8.0 will be shipped with Lucene 7.3. It's been the first update for 7 years. In this talks I'll describe why it took so long, what it taught us and how the new Lucene improved Jira.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/lucene_upgrade_jira_8/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Kamil Cichy":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:8822@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T150000 DTEND:20190203T155000 SUMMARY:Rated Ranking Evaluator: an open-source approach for Search Quality Evaluation DESCRIPTION:Every team working on information retrieval software struggles with the task of evaluating how well their system performs in terms of search quality(currently and historically).Evaluating search quality is important both to understand and size the improvement or regression of your search application across the development cycles, and to communicate such progress to relevant stakeholders.In the industry, and especially in the open source community, the landscape is quite fragmented: such requirements are often achieved using ad-hoc partial solutions that each time require a considerable amount of development and customization effort.To provide a standard, unified and approachable technology, we developed the Rated Ranking Evaluator (RRE), an open source tool for evaluating and measuring the search quality of a given search infrastructure.RRE is modular, compatible with multiple search technologies and easy to extend.The focus of the presentation will be on a live demo showing an example project with a set of initial relevancy issues that we will solve iteration after iteration: using RRE output feedbacks to gradually drive the improvement process until we reach an optimal balance between quality evaluation measures.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/rated_ranking_evaluator/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Andrea Gazzarini":invalid:nomail ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Alessandro Benedetti":invalid:nomail END:VEVENT BEGIN:VEVENT METHOD:PUBLISH UID:7584@FOSDEM19@fosdem.org TZID:Europe-Brussels DTSTART:20190203T160000 DTEND:20190203T165000 SUMMARY:CANCELLED Full-text Search Tips and Tricks DESCRIPTION:Unfortunately our speaker cannot make it. Have a quick recovery, Denis!
The real challenge in search is not how to pick the best search engine framework or how to find a match, but how to bring the most relevant results. In this talk we will discuss about relevance and to extract most of your search engine framework by indexing your data in multiple ways, boosting fields correctly, using analyzers, fuzziness, penalizing results, facets, and searching on data with different structures.
In this session we are also going to build from scratch a movie’s search microservice.
CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Search URL:https:/fosdem.org/2019/schedule/2019/schedule/event/fulltext_search_tips_tricks/ LOCATION:K.3.201 ATTENDEE;ROLE=REQ-PARTICIPANT;CUTYPE=INDIVIDUAL;CN="Denis Wilson Souza Rosa":invalid:nomail END:VEVENT END:VCALENDAR