Merge branch 'main' into refactor_sparsevectorquerybuilder

Author: mridula-s109

docs/changelog/134320.yaml

@@ -0,0 +1,5 @@
+pr: 134320
+summary: Add CHUNK function
+area: ES|QL
+type: enhancement
+issues: []

docs/reference/elasticsearch/mapping-reference/pattern-text.md

@@ -46,14 +46,16 @@ In both cases, all queries return a constant score of 1.0.
 
 ## Index sorting for improved compression
 The compression provided by `pattern_text` can be significantly improved if the index is sorted by the `template_id` field.
-For example, a typical approach would be to sort first by `message.template_id`, then by `@timestamp`, as shown in the following example.
+This sorting is not applied by default, but can be enabled for the `message` field of LogsDB indices (assuming it is of type `pattern_text`) by setting the index setting `index.logsdb.default_sort_on_message_template` to `true`.
+This will cause the index to be sorted by `host.name` (if present), then `message.template_id`, and finally by `@timestamp`.
+If the index is not LogsDB or the `pattern_text` field is named something other than `message`, index sorting can still be manually applied as shown in the following example.
 
 ```console
 PUT logs
 {
   "settings": {
     "index": {
-      "sort.field": [ "message.template_id", "@timestamp" ],
+      "sort.field": [ "notice.template_id", "@timestamp" ],
       "sort.order": [ "asc", "desc" ]
     }
   },
@@ -62,7 +64,7 @@ PUT logs
       "@timestamp": {
         "type": "date"
       },
-      "message": {
+      "notice": {
         "type": "pattern_text"
       }
     }

docs/reference/elasticsearch/mapping-reference/semantic-text.md

@@ -424,20 +424,20 @@ POST test-index/_search
 
 ## Updates and partial updates for `semantic_text` fields [semantic-text-updates]
 
-When updating documents that contain `semantic_text` fields, it’s important to understand how inference is triggered:
+When updating documents that contain `semantic_text` fields, it's important to understand how inference is triggered:
 
-* **Full document updates**
-  When you perform a full document update, **all `semantic_text` fields will re-run inference** even if their values did not change. This ensures that the embeddings are always consistent with the current document state but can increase ingestion costs.
+Full document updates
+:   Full document updates re-run inference on all `semantic_text` fields, even if their values did not change. This ensures that embeddings remain consistent with the current document state but can increase ingestion costs.
 
-* **Partial updates using the Bulk API**
-  Partial updates that **omit `semantic_text` fields** and are submitted through the [Bulk API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-bulk) will **reuse the existing embeddings** stored in the index. In this case, inference is **not triggered** for fields that were not updated, which can significantly reduce processing time and cost.
+Partial updates using the Bulk API
+:   Partial updates submitted through the [Bulk API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-bulk) reuse existing embeddings when you omit `semantic_text` fields. Inference does not run for omitted fields, which can significantly reduce processing time and cost.
 
-* **Partial updates using the Update API**
-  When using the [Update API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-update) with a `doc` object that **omits `semantic_text` fields**, inference **will still run** on all `semantic_text` fields. This means that even if the field values are not changed, embeddings will be re-generated.
+Partial updates using the Update API
+:   Partial updates submitted through the [Update API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-update) re-run inference on all `semantic_text` fields, even when you omit them from the `doc` object. Embeddings are re-generated regardless of whether field values changed.
 
-If you want to avoid unnecessary inference and keep existing embeddings:
+To preserve existing embeddings and avoid unnecessary inference costs:
 
- * Use **partial updates through the Bulk API**.
+ * Use partial updates with the Bulk API.
  * Omit any `semantic_text` fields that did not change from the `doc` object in your request.
 
 ### Scripted updates