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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

11:00 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

Lucene for Solr Developers

3:15 PM MDT

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?

  • Standard query parsing differences
  • Filter and function queries
  • Caching
  • Replicated and distributed search

Solr can be customized in amazingly powerful ways with some Lucene API know-how:

  • Write your own analyzer components for character mapping, tokenizing, and filtering tokens
  • Customize query parsing
  • Add your own search-time request components
  • Hook into Solr startup, commit, and optimize events
  • Adapt Solr’s response writing to your needs