Merge branch 'main' into aggs-composite-memory

Author: ivancea

distribution/docker/build.gradle

@@ -668,6 +668,11 @@ subprojects { Project subProject ->
       dependsOn compressExportTask
     }
 
+    tasks.named('assemble').configure {
+      dependsOn exportTask
+    }
+
+    // deprecated here for backwards compatibility of DistroTestPlugin and DistributionDownloadPlugin
     artifacts.add('default', file(tarFile)) {
       type = 'tar'
       name = artifactName

docs/reference/elasticsearch/mapping-reference/mapping-source-field.md

@@ -17,7 +17,11 @@ If disk usage is important to you, then consider the following options:
 
 ## Synthetic `_source` [synthetic-source]
 
-Though very handy to have around, the source field takes up a significant amount of space on disk. Instead of storing source documents on disk exactly as you send them, Elasticsearch can reconstruct source content on the fly upon retrieval. To enable this [subscription](https://www.elastic.co/subscriptions) feature, use the value `synthetic` for the index setting `index.mapping.source.mode`:
+:::{note}
+This feature requires a [subscription](https://www.elastic.co/subscriptions).
+:::
+
+Though very handy to have around, the source field takes up a significant amount of space on disk. Instead of storing source documents on disk exactly as you send them, Elasticsearch can reconstruct source content on the fly upon retrieval. To enable this feature, use the value `synthetic` for the index setting `index.mapping.source.mode`:
 
 $$$enable-synthetic-source-example$$$
 

docs/reference/query-languages/esql/_snippets/functions/description/contains.md

@@ -96,39 +96,35 @@ The filter is a pre-filter, meaning that it is applied **during** the approximat
 `similarity`
 :   (Optional, float) The minimum similarity required for a document to be considered a match. The similarity value calculated relates to the raw [`similarity`](/reference/elasticsearch/mapping-reference/dense-vector.md#dense-vector-similarity) used. Not the document score. The matched documents are then scored according to [`similarity`](/reference/elasticsearch/mapping-reference/dense-vector.md#dense-vector-similarity) and the provided `boost` is applied.
 
+`boost`
+:   (Optional, float) Floating point number used to multiply the scores of matched documents. This value cannot be negative. Defaults to `1.0`.
 
-`rescore_vector` {applies_to}`stack: preview 9.0, ga 9.1`
-:   (Optional, object) Apply oversampling and rescoring to quantized vectors.
-
-::::{note}
-Rescoring only makes sense for quantized vectors; when [quantization](/reference/elasticsearch/mapping-reference/dense-vector.md#dense-vector-quantization) is not used, the original vectors are used for scoring. Rescore option will be ignored for non-quantized `dense_vector` fields.
-::::
-
-
-`oversample`
-:   (Required, float)
-
-    Applies the specified oversample factor to `k` on the approximate kNN search. The approximate kNN search will:
-
-    * Retrieve `num_candidates` candidates per shard.
-    * From these candidates, the top `k * oversample` candidates per shard will be rescored using the original vectors.
-    * The top `k` rescored candidates will be returned.
-    Must be one of the following values: 
-      * \>= 1f to indicate the oversample factor
-      * Exactly `0` to indicate that no oversampling and rescoring should occur. {applies_to}`stack: ga 9.1`
 
+`_name`
+:   (Optional, string) Name field to identify the query
 
-See [oversampling and rescoring quantized vectors](docs-content://solutions/search/vector/knn.md#dense-vector-knn-search-rescoring) for details.
 
+`rescore_vector` {applies_to}`stack: preview 9.0, ga 9.1`
+:   (Optional, object) Apply oversampling and rescoring to quantized vectors.
 
-`boost`
-:   (Optional, float) Floating point number used to multiply the scores of matched documents. This value cannot be negative. Defaults to `1.0`.
+    **Parameters for `rescore_vector`**:
+    
+    `oversample`
+    :   (Required, float)
 
+        Applies the specified oversample factor to `k` on the approximate kNN search. The approximate kNN search will:
 
-`_name`
-:   (Optional, string) Name field to identify the query
+     * Retrieve `num_candidates` candidates per shard.
+     * From these candidates, the top `k * oversample` candidates per shard will be rescored using the original vectors.
+     * The top `k` rescored candidates will be returned. Must be one of the following values: 
+       * \>= 1f to indicate the oversample factor
+       * Exactly `0` to indicate that no oversampling and rescoring should occur. {applies_to}`stack: ga 9.1`
 
+    See [oversampling and rescoring quantized vectors](docs-content://solutions/search/vector/knn.md#dense-vector-knn-search-rescoring) for details.
 
+    ::::{note}
+    Rescoring only makes sense for [quantized](/reference/elasticsearch/mapping-reference/dense-vector.md#dense-vector-quantization) vectors. The `rescore_vector` option will be ignored for non-quantized `dense_vector` fields, because the original vectors are used for scoring.
+    ::::
 
 ## Pre-filters and post-filters in knn query [knn-query-filtering]
 

docs/reference/query-languages/esql/_snippets/functions/layout/contains.md

@@ -636,6 +636,15 @@ tests:
 - class: org.elasticsearch.xpack.esql.qa.multi_node.EsqlClientYamlIT
   method: test {p0=esql/60_usage/Basic ESQL usage output (telemetry) non-snapshot version}
   issue: https://github.com/elastic/elasticsearch/issues/133461
+- class: org.elasticsearch.xpack.esql.action.TimeSeriesRateIT
+  method: testRateWithTimeBucketAndClusterMultipleMetricsByMin
+  issue: https://github.com/elastic/elasticsearch/issues/133478
+- class: org.elasticsearch.xpack.esql.action.LookupJoinTypesIT
+  method: testLookupJoinOthers
+  issue: https://github.com/elastic/elasticsearch/issues/133480
+- class: org.elasticsearch.xpack.esql.action.CrossClusterAsyncQueryStopIT
+  method: testStopQueryLocal
+  issue: https://github.com/elastic/elasticsearch/issues/133481
 
 # Examples:
 #

docs/reference/query-languages/esql/_snippets/functions/parameters/contains.md

@@ -97,8 +97,8 @@ public void testRemoteClusterStats() throws ExecutionException, InterruptedExcep
             assertThat(remoteStats.get(clusterAlias).clusterUUID(), not(equalTo("")));
             assertThat(remoteStats.get(clusterAlias).mode(), oneOf("sniff", "proxy"));
         }
-        assertFalse(remoteStats.get(REMOTE1).skipUnavailable());
-        assertTrue(remoteStats.get(REMOTE2).skipUnavailable());
+        assertFalse(remoteStats.get(REMOTE1).skipUnavailable().get());
+        assertTrue(remoteStats.get(REMOTE2).skipUnavailable().get());
     }
 
     private void setupClusters() {