Join the Elastic Community for a session of sharing by Elastic's local Support Engineer, and our Developer Advocate from France! 6.30pm – Doors open, food & beverages, registration Speaker 1: Louis Ong, Support Engineer, Elastic During this meetup, I will be discussing what can cause slow queries and how to identify them within the context of Elasticsearch. This discussion stems from some of our common troubleshooting methods that may require one to be fairly intimate with how Elasticsearch works. --- Speaker 2: David Pilato, Developer Advocate, Elastic Most of the time postal addresses from our customers or users are not very well formatted or defined in our information systems. And it can become a nightmare if you are a call center employee for example and want to find a customer by its address. Imagine as well how a sales service could easily put on a map where are located the customers and where they can open a new shop... In this live coding session, I will show you how to solve all those questions using the Elastic stack with a lot of focus on Logstash and Elasticsearch. --- Bring any questions/queries about the Elastic stack and your own experiences along to discuss on the night. We look forward to meeting all our awesome users again - hope to see you there! Venue sponsor: WeWork Suntec
7.00pm – Finding & fixing slow queries in Elasticsearch by Louis Ong
7.20pm – Enriching postal addresses with Elastic Stack by David Pilato
8.00pm – Q&A, Discussion
Topic: Finding & fixing slow queries in Elasticsearch
Synopsis: Elasticsearch is a very flexible and feature-rich application that provides many different ways to query your data. But have you ever experienced query speeds that were less than you hoped for? With a distributed system like Elasticsearch, there can be various possible factors contributing to query performance, including external factors such as load-balancer settings, network latency (bandwidth, NIC cards/drivers), etc.
Topic: Enriching postal addresses with Elastic Stack
Synopsis: Come and learn how you can enrich your existing data with normalized postal addresses with geo location points thanks to open data and BANO project.
