Elastic Search meetup Berlin #

Today Retresco hosted the (to my knowledge fourth) Elastic Search User Group Berlin - a group dedicated to using Lucene as part of Elastic Search. With roughly fifteen attendees the meetup attracted a decent crowd - most interestingly many of the people there were already using the software either in production or for closed beta projects.

The fist talk given was by people from ferret-go - a company doing media monitoring for brands focused on the German market. They are pretty new to the search topic, on top they aren’t fluent Java developers but do most stuff in Python. Essentially their whole application is built on top of Elastic Search - most features are implemented as more or less complex search queries. In recent weeks they had to deal with typical problems related to growing data set sizes, nodes getting hot in particular when load balancing isn’t configured quite right and balancing shards on a per index level instead of doing it globally for all shards (particularly bad in their case as they added an index with smaller shards and one with significantly larger shards into ES).

The second talk gave a really nice overview on things to keep in mind before putting ES to production - as is usually the case, the default configuration makes it easy to get started but most likely is not what you want in your production environment.

Really nice, technically focused event. Thanks to Retresco for hosting the meetup including beer and Club Mate and to ElasticSearch.com for paying for the pizza. Check their meetup page for the next event - most likely to be scheduled in January.

Also if you’d like to learn more on Lucene 4 (talk by Simon Willnauer) - make sure to attend the Apache Hadoop Get Together December 2012 (if you need another ticket, it might make sense to politely ask the organiser, make sure you are registered, otherwise most likely you won’t get through security). Other two talks scheduled: Pere Urbon Bayes on NoSQL and Graph, a love story! as well as myself on How to Fail Your Big Data Project Quick and Rapidly.