This allows a `rescore_vector: {oversample: 0}` to indicate bypassing
oversampling and rescoring.
This is useful for:
- Updating a quantized mapping to turn off automatic rescoring
- Bypassing oversampling at query time in an ad-hoc manner if its on by default in the mapping
closes: https://github.com/elastic/elasticsearch/issues/125157
Adds a new cache and setting
TransportGetAllocationStatsAction.CACHE_TTL_SETTING
"cluster.routing.allocation.stats.cache.ttl" to configure the max age
for cached NodeAllocationStats on the master. The default
value is currently 1 minute per the suggestion in issue 110716.
Closes#110716
In a few previous PR's we restructured the ES|QL docs to make it possible to generate them dynamically.
This PR just moves a few files around to make the query languages docs easier to work with, and a little more organized like the ES|QL docs.
A bit part of this was setting up redirects to the new locations, so other repo's could correctly link to the elasticsearch docs.
Clarify that it is expected sometimes to see inter-node connections
sending zero-window advertisements as part of the usual TCP backpressure
mechanism.
This adds a new parameter to the quantized index mapping that allows
default oversampling and rescoring to occur.
This doesn't adjust any of the defaults. It allows it to be configured.
When the user provides `rescore_vector: {oversample: <number>}` in the
query it will overwrite it.
For example, here is how to use it with bbq:
```
PUT rescored_bbq
{
"mappings": {
"properties": {
"vector": {
"type": "dense_vector",
"index_options": {
"type": "bbq_hnsw",
"rescore_vector": {"oversample": 3.0}
}
}
}
}
}
```
Then, when querying, it will auto oversample the `k` by `3x` and rerank
with the raw vectors.
```
POST _search
{
"knn": {
"query_vector": [...],
"field": "vector"
}
}
```
