Erik has spoken at conferences, events, and meetups around the world, entirely on open source projects. He has spoken at JavaOne, Uberconf, the NFJS circuit, Devoxx, Berlin Buzzwords, Lucene Revolution, and many other events and user group meetings.
Apache Solr serves search requests at enterprises and the largest companies around the world. Built on top of the top-notch Apache Lucene library, Solr makes indexing and searching integration into your applications straightforward. This talk will introduce Solr's capabilities with live demonstrations.
Solr provides faceted navigation, spell checking, highlighting, clustering, grouping, and other search features. Solr can index rich documents such as PDF, Word, HTML, and other file types. Query volume scales with replication and collection size with distributed capabilities including the power of the new SolrCloud near-real-time distributed indexing.
Solr Recipes provides quick and easy steps for common use cases with Apache Solr. Bite-sized recipes will be presented for data ingestion, textual analysis, client integration, and each of Solr’s features including faceting, more-like-this, spell checking/suggest, and others.
Quick and easy steps for common Apache Solr use cases
Ingesting recipes: CSV, relational databases, file system, web crawls, API
Analysis recipes: copyField, character mapping, tokenizing and filtering, configuring for suggest, data exploration
Faceting recipes: field, date and numeric range, pivot, and query faceting
Integration recipes: prototyping user interactions, working with Solr from PHP, Rails, Java, Ajax, and other environments
Other featured recipes: more like this, spell checking/suggest, grouping, clustering
Solr Recipes provides quick and easy steps for common use cases with Apache Solr. Bite-sized recipes will be presented for data ingestion, textual analysis, client integration, and each of Solr’s features including faceting, more-like-this, spell checking/suggest, and others.
Quick and easy steps for common Apache Solr use cases
Ingesting recipes: CSV, relational databases, file system, web crawls, API
Analysis recipes: copyField, character mapping, tokenizing and filtering, configuring for suggest, data exploration
Faceting recipes: field, date and numeric range, pivot, and query faceting
Integration recipes: prototyping user interactions, working with Solr from PHP, Rails, Java, Ajax, and other environments
Other featured recipes: more like this, spell checking/suggest, grouping, clustering
You’re Solr powered, and needing to customize its capabilities. Apache Solr is flexibly architected, with practically everything pluggable. Under the hood, Solr is driven by the well-known Apache Lucene. Lucene for Solr Developers will guide you through the various ways in which Solr can be extended, customized, and enhanced with a bit of Lucene API know-how. We’ll delve into improving analysis with custom character mapping, tokenizing, and token filtering extensions; show why and how to implement specialized query parsing, and how to add your own search and update request handling.
Apache Solr uses Lucene under the hood for its searching power
How does Solr work with Lucene already?
Solr can be customized in amazingly powerful ways with some Lucene API know-how: