[Note: this post has been updated to include video and slides from the June 2 presentation]
Back by popular demand! Sematext engineers Radu Gheorghe and Rafal Kuc returned to Berlin Buzzwords on Tuesday, June 2, with the second installment of their “Side by Side with Elasticsearch and Solr” talk. (You can check out Part 1 here.)
Elasticsearch and Solr Performance and Scalability
This brand new talk — which included a live demo, a video demo and slides — dove deeper into into how Elasticsearch and Solr scale and perform. And, of course, they took into account all the goodies that came with these search platforms since last year.
Radu and Rafal showed attendees how to tune Elasticsearch and Solr for two common use-cases: logging and product search. Then they showed what numbers they got after tuning. There was also some sharing of best practices for scaling out massive Elasticsearch and Solr clusters; for example, how to divide data into shards and indices/collections that account for growth, when to use routing, and how to make sure that coordinated nodes don’t become unresponsive.
Here is the video:
…and here are the slides:
Feedback & Questions — Bring It On
If you’ve got feedback or questions about topics like Elasticsearch vs. Solr (here’s a detailed comparison) and what’s new and exciting with both applications, just drop us a line. We live and breathe this stuff, so we’re always happy to hear from like-minded people.
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In the world of Information Science, the word performance means the ability to deliver results that are relevant to the query in the user’s judgement. Specifically, it is some formula that measures precision, the concentration of relevant documents at the top of the result list, and coverage, the completeness of all relevant results in the first n documents returned.
In the world of computer geekdom, performance means getting really big an going really fast. This is probably the easiest and least important attributes of a search engine.