- Fast: Results are real-time or near real-time instead of batch oriented.
- Accurate: Answers are exact and don't have a margin of error.
- Big: You require horizontal scaling and need to distribute your data.
While Fast and Big are relatively easy to understand, Accurate is a bit harder to picture. This talk shows some concrete examples of accuracy tradeoffs Elasticsearch can take for terms aggregations, cardinality aggregations with HyperLogLog++, and the IDF part of full-text search. Or how to trade some speed or the distribution for more accuracy.
Informacije o predavanju
Jezik / Language: ENG
O Avtorju
Philipp lives to demo interesting technology. Having worked as a web, infrastructure, and database engineer for over ten years, Philipp is now working as a developer advocate at Elastic — the company behind the open source Elastic Stack consisting of Elasticsearch, Kibana, Beats, and Logstash.
