Scaling Elasticsearch & Autosuggest in Lucene

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Scaling Elasticsearch in Production

Elasticsearch was built ground up as a powerful distributed system which makes search and analytics freaky fast. In this talk we will explore the "elastic" part of Elasticsearch, which is essential to understand before deploying and maintaining a large cluster. Suyog will introduce concepts of shards, indices, partitioning strategies, master responsibilities etc. With this knowledge we will approach the big question -- how do we size our cluster? He'll end with some production best practices.

Autosuggest in Lucene

Query suggestions are a key component of nearly all search applications. Google has set a high bar for user expectations: so how can you make your application deliver? A major advantage of Lucene-based search solutions is the ability to tailor the search behaviour to meet your specific application needs. This talk will go into how the same can be done with query suggestions.
This talk will introduce Lucene's suggester implementations and how to use their features efficiently, including real world use cases.

About Suyog Rao (Software Engineer, Elastic)

Suyog (https://www.linkedin.com/in/suyograo) is the engineering team lead for Logstash and is based in San Francisco, CA. He primarily develops for the Logstash project and is actively involved with supporting customers and training users on the ELK stack At his previous job, he was involved with developing a high throughput, low latency infrastructure for ingesting and analyzing terabytes of log data using Elasticsearch, Apache Kafka and Storm. Suyog has several years of experience developing analytics software for startups as well as large enterprises. He is proficient in Java and C++ and loves working with open source technologies.

About Areek Zillur (Software Engineer, Elastic)

Areek (https://www.linkedin.com/in/areekzillur) is a Apache Lucene committer and Elasticsearch core developer based in Toronto, Canada. He earned his BASc in Computer Engineering from University of Waterloo. He is a passionate software engineer interested in information retrieval, distributed systems and algorithmic trading systems. He loves writing Java and Python for fun and profit.

Special thanks to Leslie Hawthorn (https://twitter.com/lhawthorn) of Elastic (https://www.elastic.co/) in seeking us out and sending over Suyog and Areek to do their talks. Thanks to Beier Cai (https://twitter.com/beiercai) and Justin Long (https://twitter.com/crockpotveggies) to helping us resolve a venue schedule conflict.

Schedule

• 6:00 PM Doors are open, feel free to mingle
• 6:30 PM Presentation start
• ~8:00 PM Off to a nearby restaurant (Original Joe's) for food, drinks, and breakout discussions

Getting There

By transit there a number of high frequency buses (check Google Maps or the Translink site for your particular case) that will get you there. For the drivers, there is a fair bit of street parking (free and pay) in the area, especially after 6.

Code of Conduct

tl;dr: Be Excellent to Each Other! And please, don’t be a jerk.

Full details can be found on our about page, under the "Code of Conduct" heading: http://www.meetup.com/PolyglotVancouver/about/

How to Contact Us / Re Comments

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