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fix formatting, address pr comments
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troubleshoot/elasticsearch/rejected-requests.md

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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).
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{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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::::{note}
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{applies_to}`stack: ga 9.1`{applies_to}`serverless: ga`
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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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stack: ga 9.1
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serverless: ga
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```
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When bulk indexing documents with the `semantic_text` field type, you may encounter rejections due to high memory usage during inference processing.
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These rejections will appear as an `InferenceException` in your cluster logs.
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**To resolve this issue:**
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1. Reduce the batch size of documents in your indexing requests.
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2. If reducing batch size doesn't resolve the issue, then consider scaling up your machine resources.
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{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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3. {applies_to}`serverless: unavailable` 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}
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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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