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docs: add 429 semantic_text troubleshooting #2507
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@@ -67,13 +67,27 @@ These stats are cumulative from node startup. | |
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Indexing pressure rejections appear as an `EsRejectedExecutionException`, and indicate that they were rejected due to `combined_coordinating_and_primary`, `coordinating`, `primary`, or `replica`. | ||
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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). | ||
{applies_to}`stack: ga 9.1`{applies_to}`serverless: ga`Another cause of indexing pressure rejections might be the use of the [`semantic_text`](https://www.elastic.co/docs/reference/elasticsearch/mapping-reference/semantic-text) field type, which can cause rejections when indexing large batches of documents if the batch may otherwise incur an Out Of Memory (OOM) error. | ||
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See [this video](https://www.youtube.com/watch?v=QuV8QqSfc0c) for a walkthrough of diagnosing indexing pressure rejections. | ||
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## Prevent rejected requests [prevent-rejected-requests] | ||
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**Fix high CPU and memory usage** | ||
### Fix high CPU and memory usage [fix-high-cpu-memory-usage] | ||
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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). | ||
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### Fix for `semantic_text` ingestion issues [fix-semantic-text-ingestion-issues] | ||
```{applies_to} | ||
stack: ga 9.1 | ||
serverless: ga | ||
``` | ||
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1. Reduce 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. | ||
{applies_to}`serverless: unavailable`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. | ||
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::::{warning} | ||
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. | ||
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