docs: add 429 semantic_text troubleshooting

troubleshoot/elasticsearch/rejected-requests.md

@@ -67,7 +67,9 @@ These stats are cumulative from node startup.
 
 Indexing pressure rejections appear as an `EsRejectedExecutionException`, and indicate that they were rejected due to `combined_coordinating_and_primary`, `coordinating`, `primary`, or `replica`.
 
-These errors are often related to [backlogged tasks](task-queue-backlog.md), [bulk index](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-bulk) sizing, or the ingest target's [`refresh_interval` setting](elasticsearch://reference/elasticsearch/index-settings/index-modules.md).
+These errors are often related to [backlogged tasks](task-queue-backlog.md), [bulk index](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-bulk) sizing, or the ingest target's [`refresh_interval` setting](elasticsearch://reference/elasticsearch/index-settings/index-modules.md).¹
+
+¹ : Starting from versions 8.19+ and 9.1+, indexing to a semantic_text field can also cause 429 errors if the batch may otherwise incur an Out Of Memory (OOM) error.
 
 See [this video](https://www.youtube.com/watch?v=QuV8QqSfc0c) for a walkthrough of diagnosing indexing pressure rejections.
 
@@ -77,3 +79,11 @@ See [this video](https://www.youtube.com/watch?v=QuV8QqSfc0c) for a walkthrough
 **Fix high CPU and memory usage**
 
 If {{es}} regularly rejects requests and other tasks, your cluster likely has high CPU usage or high JVM memory pressure. For tips, see [High CPU usage](high-cpu-usage.md) and [High JVM memory pressure](high-jvm-memory-pressure.md).
+
+**Fix for semantic_text field issues:**
+
+When working with semantic_text fields in versions 8.19+ and 9.1+:
+
+1. First, try reducing the batch size of documents in your indexing requests.
+2. If reducing batch size doesn't resolve the issue, then consider scaling up your machine resources.
+3. A last resort option is to adjust the indexing_pressure.memory.coordinating.limit cluster setting. The default value is 10% of the heap. Increasing this limit allows more memory to be used for coordinating operations before rejections occur. This adjustment should only be considered after exhausting other options, as setting this value too high may risk Out of Memory (OOM) errors in your cluster. A cluster restart is required for this change to take effect.