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https://issues.apache.org/jira/browse/CAMEL-14952?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17153795#comment-17153795
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Zoran Regvart commented on CAMEL-14952:
---------------------------------------
If I search for "kafka" this is what I see (on the [PR#423
preview|https://deploy-preview-423--camel.netlify.app/]):
!Screenshot_2020-07-08 Home - Apache Camel.png!
Seems like we have two different ideas on how to implement this, I find it the
easiest to write down a set of criteria like the ones in
[comment|https://issues.apache.org/jira/browse/CAMEL-14952?focusedCommentId=17152661&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-17152661],
and list what we think is required for the first iteration of the search
improvement and then test each implementation against those. Perhaps we can
start there and see what do we find important right now and see if one
implementation vs the other can deliver the desired results.
> Better search on the website
> ----------------------------
>
> Key: CAMEL-14952
> URL: https://issues.apache.org/jira/browse/CAMEL-14952
> Project: Camel
> Issue Type: Improvement
> Components: website
> Reporter: Zoran Regvart
> Priority: Major
> Attachments:
> BH4D9OD16A_apache_camel_20200608-20200614_no_result_searches.csv,
> List_Of_Crawled_Pages_by_DocSearch.txt, Screenshot_2020-07-08 Home - Apache
> Camel.png, apache_demo.json, camel.json, error-search.png,
> getbootstrap-searchresult.png, image-2020-06-13-14-39-08-776.png,
> list_of_crawled_pages.txt, pr-preview-search.png, search-results-example.png,
> sitemap-camel.png
>
>
> We use [Algolia|http://algolia.com/] for the search functionality on the
> website using their [free plan|https://www.algolia.com/for-open-source/] for
> Open Source projects. The index is built by Algolia's crawler using the
> [DocSearch|https://docsearch.algolia.com/].
> When this was done we built our own UI on top of Algolia JavaScript API, as
> one if requirements is that clients use Algolia's JavaScript clients. We did
> not use Algolia UI as at that point it was rather large JavaScript dependency
> to add and it would slow down the loading of the website.
> We also have some [initial
> work|https://github.com/apache/camel-website/pull/74] on creating our own
> Algolia index at build time.
> The current search doesn't seem to index the whole website, some results
> don't appear in the search, looks like most of the content from Antora is not
> indexed: trying to search for {{removeHeader}}, the [FAQ
> entry|https://camel.apache.org/manual/latest/faq/how-to-avoid-sending-some-or-all-message-headers.html]
> is not found. There's also a list of failed searches on the Algolia
> dashboard we can use to benchmark the search.
> What we need is to build the search index over the whole content. Approach
> taken in [#74|https://github.com/apache/camel-website/pull/74] is good start
> for Hugo generated content. We need to expand that to Antora built content as
> well.
> This search index would be built at the website build time and would include
> both Hugo and Algolia content in the same file or possibly in several files
> if we use multi-index search. More on how indexes are built can be seen in
> the [Algolia
> documentation|https://www.algolia.com/doc/guides/sending-and-managing-data/prepare-your-data/].
> We need to figure out what data to send and how to integrate this with
> Antora, for Hugo we have a good idea from
> [#74|https://github.com/apache/camel-website/pull/74], importantly the
> structure needs to be the same. One good source of inspiration on building
> the index for Antora content is in the [Lunr.js
> integration|https://github.com/Mogztter/antora-lunr].
> We need to build the index with the search UI in mind, i.e. the index needs
> to contain the data we wish to present in the UI as well as enough content
> for Algolia to be able to use the content to perform search. So starting with
> a mockup of what we wish to present/utilize in the search UI and deriving the
> data structure for the index from that would be a good start.
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