Question 1

How do I add Elasticlunr.js to a static website for search?

Accepted Answer

Include the elasticlunr.js script in your HTML, build the index offline with your documents, save it as a JSON file, and load it client-side. The README provides examples for browser and Node.js setups.

Question 2

What's the difference between Elasticlunr.js and Lunr.js?

Accepted Answer

Elasticlunr.js is based on Lunr.js but offers query-time boosting, field-search, faster performance, and smaller index sizes by optimizing scoring mechanisms. It's more flexible but may have fewer community resources.

Question 3

How can I save and load the search index in Elasticlunr.js?

Accepted Answer

Use JSON.stringify() to save the index to a file and elasticlunr.Index.load() to reload it. The README includes Node.js examples for building and persisting indices for offline use.

Question 4

Does Elasticlunr.js support languages other than English?

Accepted Answer

Yes, but it requires integration with lunr-languages for stemmers and stop words. You need to include additional scripts and call this.use() with the language module, as detailed in the documentation.

Question 5

How do I handle document updates if I don't store the original JSON?

Accepted Answer

It's inconvenient because you must re-add the entire document or manage references externally. The README notes that saving the original JSON is optional but recommended for updates and deletions.

Question 6

Is Elasticlunr.js or a full backend like Elasticsearch better for my app?

Accepted Answer

Choose Elasticlunr.js for lightweight, client-side search on static sites or small datasets; use Elasticsearch for scalable, server-side search with advanced features and real-time indexing on large volumes.

Elasticlunr

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