Adds clarification for vector preloading, what extension is to what
storage kind, and that quantized vectors are stored in separate files
allowing for individual preload.
closes: https://github.com/elastic/elasticsearch/issues/116273
* docs: update synthetic source docs
* fix: also doc values false works
* Revert "fix: also doc values false works"
This reverts commit 0895a76758.
* fix: update synthetic source documentation
* fix: all field types support it
* fix: no need to explicitly mention it
* fix: synthetic source sorting
* fix: may instead of might
* Remove `es-test-dir` book-scoped variable
* Remove `plugins-examples-dir` book-scoped variable
* Remove `:dependencies-dir:` and `:xes-repo-dir:` book-scoped variables
- In `index.asciidoc`, two variables (`:dependencies-dir:` and `:xes-repo-dir:`) were removed.
- In `sql/index.asciidoc`, the `:sql-tests:` path was updated to fuller path
- In `esql/index.asciidoc`, the `:esql-tests:` path was updated idem
* Replace `es-repo-dir` with `es-ref-dir`
* Move `:include-xpack: true` to few files that use it, remove from index.asciidoc
Adds new `quantization_options` to `dense_vector`. This allows for
vectors to be automatically quantized to `byte` when indexed.
Example:
```
PUT vectors
{
"mappings": {
"properties": {
"my_vector": {
"type": "dense_vector",
"index": true,
"index_options": {
"type": "int8_hnsw"
}
}
}
}
}
```
When querying, the query vector is automatically quantized and used when
querying the HNSW graph. This reduces the memory required to only `25%`
of what was previously required for `float` vectors at a slight loss of
accuracy.
This is currently only available when `index: true` and when using
`hnsw`
`dot_product` requires vectors to be unit-length. Previously, we would
check that vectors were unit-length and throw if they were not.
Instead, we will now auto-normalize vectors as they are indexed.
`cosine` will continue to behave as usual, not normalizing the vectors.
closes: https://github.com/elastic/elasticsearch/issues/98935
In this tuning guide we mentioned preload to warm up
the filesystem cache, but we did not provide file extensions
used in vector search. This adds these extensions.
This commit removes the experimental tag from kNN search docs and makes some
docs improvements:
* Add a prominent warning about memory usage in the kNN search guide
* Link to the performance tuning guide from the main guide
* Clarify the memory requirements section in the tuning guide
