Presentation: Tweet"Organizing Work"
Maintaining your Elasticsearch Indexes / 11:30 - 11:45
Some years ago, I was facing multiple projects with search challenges like "we need more options like synonyms, fuzzy search and facets", "our search engine is to slow" and "I cannot find what I am looking for". I got to know elasticsearch and by using elasticsearch I was able to create solutions for these challenges. While doing these projects I noticed doing some things over and over again. An example: you have to deal with the indexes your create, changes in the mapping, the number of shards. This occurs in development and in production. Another example: after importing some data, you want to check what is in your index. Can I execute the queries and filters I need and obtain the results I want?
Based on these experiences I first created some code to copy-paste from project to project and I created an AngularJS based gui to play with your data. Later on I added tools like: "where are my shards" to locate shards in your cluster and "Snapshots" to create and restore snapshots. The next step was to create a java based maintenance tool to maintain your indexes, set some cluster wide properties and manage the snapshots of your data.
In this talk I will give you the most important tips you want to know as an elasticsearch developer. I will show of the some tools I use and code I re-use in every project.
Working with what you got: Making the Best of Legacy Code / 11:50 - 12:05
In an ideal situation, a developer will work with either a blank slate or well-organized and succinctly-documented code, but in actuality that's rarely the case. In this talk, we'll briefly discuss common problems and frustrations with legacy code, demonstrate how it parallels with problems in legacy in other departments, and discuss how to reduce friction for others working with our own legacies.
by Nicollette Lui & Laurel Hechanova
Document Database Schema Design / 12:10 - 12:25
This talk is a short introduction of different schema design and patterns that one can apply on their application to match their use cases and MongoDB. We will briefly discuss the decision to use a specific design according to the rules of usage, data life cycle, query richness and write / read ratios.
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