[8.15] Updating retriever documentation to better explain how filters are applied (#112201)

docs/reference/rest-api/common-parms.asciidoc

@@ -1326,13 +1326,21 @@ that lower ranked documents have more influence. This value must be greater than
 equal to `1`. Defaults to `60`.
 end::rrf-rank-constant[]
 
-tag::rrf-window-size[]
-`window_size`::
+tag::rrf-rank-window-size[]
+`rank_window_size`::
 (Optional, integer)
 +
 This value determines the size of the individual result sets per
 query. A higher value will improve result relevance at the cost of performance. The final
 ranked result set is pruned down to the search request's <<search-size-param, size>>.
-`window_size` must be greater than or equal to `size` and greater than or equal to `1`.
+`rank_window_size` must be greater than or equal to `size` and greater than or equal to `1`.
 Defaults to the `size` parameter.
-end::rrf-window-size[]
+end::rrf-rank-window-size[]
+
+tag::rrf-filter[]
+`filter`::
+(Optional, <<query-dsl, query object or list of query objects>>)
++
+Applies the specified <<query-dsl-bool-query, boolean query filter>> to all of the specified sub-retrievers,
+according to each retriever's specifications.
+end::rrf-filter[]

docs/reference/search/retriever.asciidoc

@@ -198,7 +198,7 @@ GET my-embeddings/_search
 
 An <<rrf, RRF>> retriever returns top documents based on the RRF formula,
 equally weighting two or more child retrievers.
-Reciprocal rank fusion (RRF) is a method for combining multiple result 
+Reciprocal rank fusion (RRF) is a method for combining multiple result
 sets with different relevance indicators into a single result set.
 
 ===== Parameters
@@ -207,7 +207,9 @@ include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-retrievers]
 
 include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-rank-constant]
 
-include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-window-size]
+include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-rank-window-size]
+
+include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-filter]
 
 ===== Restrictions
 
@@ -225,7 +227,7 @@ A simple hybrid search example (lexical search + dense vector search) combining
 ----
 GET /restaurants/_search
 {
-  "retriever": { 
+  "retriever": {
     "rrf": { <1>
       "retrievers": [ <2>
         {
@@ -340,6 +342,10 @@ Currently you can:
 ** Refer to the <<text-similarity-reranker-retriever-example-eland,example>> on this page for a step-by-step guide.
 
 ===== Parameters
+`retriever`::
+(Required, <<retriever, retriever>>)
++
+The child retriever that generates the initial set of top documents to be re-ranked.
 
 `field`::
 (Required, `string`)
@@ -366,6 +372,13 @@ The number of top documents to consider in the re-ranking process. Defaults to `
 +
 Sets a minimum threshold score for including documents in the re-ranked results. Documents with similarity scores below this threshold will be excluded. Note that score calculations vary depending on the model used.
 
+`filter`::
+(Optional, <<query-dsl, query object or list of query objects>>)
++
+Applies the specified <<query-dsl-bool-query, boolean query filter>> to the child  <<retriever, retriever>>.
+If the child retriever already specifies any filters, then this top-level filter is applied in conjuction
+with the filter defined in the child retriever.
+
 ===== Restrictions
 
 A text similarity re-ranker retriever is a compound retriever. Child retrievers may not use elements that are restricted by having a compound retriever as part of the retriever tree.
@@ -441,13 +454,13 @@ eland_import_hub_model \
 +
 [source,js]
 ----
-PUT _inference/rerank/my-msmarco-minilm-model 
+PUT _inference/rerank/my-msmarco-minilm-model
 {
   "service": "elasticsearch",
   "service_settings": {
     "num_allocations": 1,
     "num_threads": 1,
-    "model_id": "cross-encoder__ms-marco-minilm-l-6-v2" 
+    "model_id": "cross-encoder__ms-marco-minilm-l-6-v2"
   }
 }
 ----

docs/reference/search/rrf.asciidoc

@@ -1,9 +1,7 @@
 [[rrf]]
 === Reciprocal rank fusion
 
-preview::["This functionality is in technical preview and may be changed or removed in a future release.
-The syntax will likely change before GA.
-Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features."]
+preview::["This functionality is in technical preview and may be changed or removed in a future release. The syntax will likely change before GA. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features."]
 
 https://plg.uwaterloo.ca/~gvcormac/cormacksigir09-rrf.pdf[Reciprocal rank fusion (RRF)]
 is a method for combining multiple result sets with different relevance indicators into a single result set.
@@ -43,7 +41,7 @@ include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-retrievers]
 
 include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-rank-constant]
 
-include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-window-size]
+include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=rrf-rank-window-size]
 
 An example request using RRF:
 

docs/reference/search/search-your-data/retrievers-reranking/retrievers-overview.asciidoc

@@ -13,23 +13,23 @@ For implementation details, including notable restrictions, check out the
 
 [discrete]
 [[retrievers-overview-types]]
-==== Retriever types 
+==== Retriever types
 
 Retrievers come in various types, each tailored for different search operations.
 The following retrievers are currently available:
 
-* <<standard-retriever,*Standard Retriever*>>. Returns top documents from a 
-traditional https://www.elastic.co/guide/en/elasticsearch/reference/master/query-dsl.html[query]. 
-Mimics a traditional query but in the context of a retriever framework. This 
-ensures backward compatibility as existing `_search` requests remain supported. 
-That way you can transition to the new abstraction at your own pace without 
+* <<standard-retriever,*Standard Retriever*>>. Returns top documents from a
+traditional https://www.elastic.co/guide/en/elasticsearch/reference/master/query-dsl.html[query].
+Mimics a traditional query but in the context of a retriever framework. This
+ensures backward compatibility as existing `_search` requests remain supported.
+That way you can transition to the new abstraction at your own pace without
 mixing syntaxes.
-* <<knn-retriever,*kNN Retriever*>>. Returns top documents from a <<search-api-knn,knn search>>, 
+* <<knn-retriever,*kNN Retriever*>>. Returns top documents from a <<search-api-knn,knn search>>,
 in the context of a retriever framework.
 * <<rrf-retriever,*RRF Retriever*>>. Combines and ranks multiple first-stage retrievers using
-the reciprocal rank fusion (RRF) algorithm. Allows you to combine multiple result sets 
+the reciprocal rank fusion (RRF) algorithm. Allows you to combine multiple result sets
 with different relevance indicators into a single result set.
-An RRF retriever is a *compound retriever*, where its `filter` element is 
+An RRF retriever is a *compound retriever*, where its `filter` element is
 propagated to its sub retrievers.
 +
 Sub retrievers may not use elements that are restricted by having a compound retriever as part of the retriever tree.
@@ -38,7 +38,7 @@ See the <<rrf-using-multiple-standard-retrievers,RRF documentation>> for detaile
 Requires first creating a `rerank` task using the <<put-inference-api,{es} Inference API>>.
 
 [discrete]
-==== What makes retrievers useful? 
+==== What makes retrievers useful?
 
 Here's an overview of what makes retrievers useful and how they differ from regular queries.
 
@@ -140,7 +140,7 @@ GET example-index/_search
   ],
   "rank":{
     "rrf":{
-      "window_size":50,
+      "rank_window_size":50,
       "rank_constant":20
     }
   }
@@ -155,14 +155,14 @@ GET example-index/_search
 
 Here are some important terms:
 
-* *Retrieval Pipeline*. Defines the entire retrieval and ranking logic to 
+* *Retrieval Pipeline*. Defines the entire retrieval and ranking logic to
 produce top hits.
 * *Retriever Tree*. A hierarchical structure that defines how retrievers interact.
 * *First-stage Retriever*. Returns an initial set of candidate documents.
-* *Compound Retriever*. Builds on one or more retrievers, 
+* *Compound Retriever*. Builds on one or more retrievers,
 enhancing document retrieval and ranking logic.
-* *Combiners*. Compound retrievers that merge top hits 
-from multiple sub-retrievers. 
+* *Combiners*. Compound retrievers that merge top hits
+from multiple sub-retrievers.
 * *Rerankers*. Special compound retrievers that reorder hits and may adjust the number of hits, with distinctions between first-stage and second-stage rerankers.
 
 [discrete]
@@ -180,4 +180,4 @@ Refer to the {kibana-ref}/playground.html[Playground documentation] for more inf
 [[retrievers-overview-api-reference]]
 ==== API reference
 
-For implementation details, including notable restrictions, check out the <<retriever,reference documentation>> in the Search API docs.
+For implementation details, including notable restrictions, check out the <<retriever,reference documentation>> in the Search API docs.

server/src/main/java/org/elasticsearch/action/search/RankFeaturePhase.java

@@ -28,8 +28,8 @@
 
 /**
  * This search phase is responsible for executing any re-ranking needed for the given search request, iff that is applicable.
- * It starts by retrieving {@code num_shards * window_size} results from the query phase and reduces them to a global list of
- * the top {@code window_size} results. It then reaches out to the shards to extract the needed feature data,
+ * It starts by retrieving {@code num_shards * rank_window_size} results from the query phase and reduces them to a global list of
+ * the top {@code rank_window_size} results. It then reaches out to the shards to extract the needed feature data,
  * and finally passes all this information to the appropriate {@code RankFeatureRankCoordinatorContext} which is responsible for reranking
  * the results. If no rank query is specified, it proceeds directly to the next phase (FetchSearchPhase) by first reducing the results.
  */
@@ -88,7 +88,7 @@ public void onFailure(Exception e) {
 
     void innerRun() throws Exception {
         // if the RankBuilder specifies a QueryPhaseCoordinatorContext, it will be called as part of the reduce call
-        // to operate on the first `window_size * num_shards` results and merge them appropriately.
+        // to operate on the first `rank_window_size * num_shards` results and merge them appropriately.
         SearchPhaseController.ReducedQueryPhase reducedQueryPhase = queryPhaseResults.reduce();
         RankFeaturePhaseRankCoordinatorContext rankFeaturePhaseRankCoordinatorContext = coordinatorContext(context.getRequest().source());
         if (rankFeaturePhaseRankCoordinatorContext != null) {

server/src/main/java/org/elasticsearch/search/rank/context/QueryPhaseRankCoordinatorContext.java

@@ -17,7 +17,7 @@
 /**
  * {@link QueryPhaseRankCoordinatorContext} is running on the coordinator node and is
  * responsible for combining the query phase results from the shards and rank them accordingly.
- * The output is a `window_size` ranked list of ordered results from all shards.
+ * The output is a `rank_window_size` ranked list of ordered results from all shards.
  * Note: Currently this can use only sort by score; sort by field is not supported.
  */
 public abstract class QueryPhaseRankCoordinatorContext {

server/src/main/java/org/elasticsearch/search/rank/context/QueryPhaseRankShardContext.java

@@ -15,7 +15,7 @@
 import java.util.List;
 
 /**
- * {@link QueryPhaseRankShardContext} is used to generate the top {@code window_size}
+ * {@link QueryPhaseRankShardContext} is used to generate the top {@code rank_window_size}
  * results on each shard. It specifies the queries to run during {@code QueryPhase} and is responsible for combining all query scores and
  * order all results through the {@link QueryPhaseRankShardContext#combineQueryPhaseResults} method.
  */