Erik Hatcher
co-author of "Lucene in Action"
Erik advocates for Atlas Search at MongoDB, these days. Prior to this, he co-founded Lucidworks, innovating solutions for customers with Solr and Lucene. He has been a committer on various ASF projects, sits on the Lucene and Solr PMC, and a Member of the ASF.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.
Presentations
Introduction to Solr
9:00 AM MDT
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
10:45 AM MDT
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
1:30 PM MDT
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
Power Solr: Performance, Scaling, and Relevancy
3:15 PM MDT
Make the most out of Solr by leveraging these tips and tricks to increase performance, scale Solr to your needs, and tune search results. This talk will discuss Solr architecture decisions, performance and scaling best practices, and considerations and techniques for adjusting search results for your application.
Solr can generally handle your “big data” needs, if deployed and utilized properly. But there are some devilish details to scale up and out. We'll discuss Solr's caches and general best practices for configuring the, how Solr's distributed architecture works and how it's being deployed in production environments, and we'll delve into the voodoo of Lucene search result scoring and how to incorporate application/domain-specific factors.