Lessons learned from improving full-text search at Snyk with Elasticsearch

Elasticsearch is a popular open-source search engine used for adding full-text search capabilities in projects due to its real-time speeds and robust API. However, it can be complicated at first, but with the right configuration, it can provide flexible text search results. A standard analyzer may not be enough if you want better and more flexible search results, as seen in the example where a custom analyzer was created to achieve case-insensitive search using incomplete words of 3-8 characters in length. The custom analyzer uses an edge-ngram tokenizer, which breaks up tokens based on length, and a lowercase token filter to make search case insensitive. With this configuration, Elasticsearch provides great custom search results, and the next step will be exploring aggregations.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.