Search and beyond with Elasticsearch
In this presentation, we will look at real-life examples of innovative solutions that take advantage of Elasticsearch’s capabilities in Drupal projects. Elasticsearch is an open source search engine that rose to the top, being chosen from large organisations like wikipedia and github to small innovative startups. Elasticsearch also makes a very interesting complement to Drupal, pushing what can be done regarding search functionality, but it doesn't stop there. Elasticsearch also goes beyond search, and enables us to manage and understand massive amounts data, both structured and unstructured.
Here are some examples of functionality we have built which we'll cover:
- Fast, interactive search interfaces that guide users with smart autocompletion
- Context-sensitive ranking for improved relevancy
- Interfacing Drupal with massive amounts of structured data that wouldn’t performantly fit in Drupal
- Understanding and visualizing large amounts of data
- Searching content with language-aware text analysis
- Effective handling of saved searches and notifications with percolators
For each example we will look at the challenges from conception to concrete implementation details, giving you a good overview of the doors opened by an integration between Drupal and Elasticsearch, but also a solid head start on how to build such solutions yourself.