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fix: linkchecker include filter port mismatch (#2242)

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* initial commit; fixed anchor links on internal docs pages

* add back in absolute paths for links in code comments

* fix: update linkchecker include filter to match server port 1314

PR #1629 changed the Hugo server to port 1314 but forgot to update
the --include filter, which still matched port 1313. This caused all
links to be excluded, making the checker a no-op (0 checked, 82277 excluded).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* Fix url rewrite regex so images are not impacted

* Fix links from non-documentation pages

* Fix broken links

* more broken links

* more broken links

* broken link

* Add srcset width descriptor to .lycheeignore

* Ignore URLs that contain a % character

* Anchor regex so it matches the entire URL

---------

Co-authored-by: kanungle <neil.kanungo@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>
This commit is contained in:
Andrey Vasnetsov
2026-03-30 17:21:32 +02:00
committed by GitHub
co-authored by Claude Opus 4.6 kanungle Abdon Pijpelink
parent dc0080fffa
commit 1a40961d62
272 changed files with 872 additions and 879 deletions
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qdrant-landing/content/documentation/migrate-to-qdrant/from-elasticsearch.md
+4 -4
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@@ -68,16 +68,16 @@ docker run --net=host --rm -it registry.cloud.qdrant.io/library/qdrant-migration
## Hybrid Search Considerations
If your Elasticsearch setup uses hybrid BM25 + kNN scoring, you'll need to reconstruct this in Qdrant using [sparse vectors](/documentation/concepts/vectors/#sparse-vectors) (for BM25-like behavior) alongside dense vectors. The migration tool transfers the dense vectors; you'll need to generate sparse vectors separately if you want hybrid search in Qdrant.
If your Elasticsearch setup uses hybrid BM25 + kNN scoring, you'll need to reconstruct this in Qdrant using [sparse vectors](/documentation/manage-data/vectors/#sparse-vectors) (for BM25-like behavior) alongside dense vectors. The migration tool transfers the dense vectors; you'll need to generate sparse vectors separately if you want hybrid search in Qdrant.
Qdrant supports native hybrid search with [Reciprocal Rank Fusion (RRF)](/documentation/concepts/hybrid-queries/) to combine dense and sparse results.
Qdrant supports native hybrid search with [Reciprocal Rank Fusion (RRF)](/documentation/search/hybrid-queries/) to combine dense and sparse results.
## Gotchas
- **Nested documents:** Elasticsearch nested documents need to be flattened or restructured for Qdrant's payload model.
- **Score normalization:** Elasticsearch `_score` values are not comparable to Qdrant scores. Use rank-based metrics (recall@k, Spearman correlation) rather than raw score comparison when [verifying your migration](/documentation/migration-verification/).
- **Score normalization:** Elasticsearch `_score` values are not comparable to Qdrant scores. Use rank-based metrics (recall@k, Spearman correlation) rather than raw score comparison when [verifying your migration](/documentation/migration-guidance/).
- **BM25 is not migrated:** The migration tool transfers vectors and document fields. If you relied on Elasticsearch's BM25 scoring, you'll need to set up sparse vectors in Qdrant separately.
## Next Steps
After migration, verify your data arrived correctly with the [Migration Verification Guide](/documentation/migration-verification/).
After migration, verify your data arrived correctly with the [Migration Verification Guide](/documentation/migration-guidance/).