Elasticsearch Elasticsearch Indexing Failure 

By Opster Team

Updated: Mar 10, 2024

| 2 min read

What does this mean?

Indexing operations may be rejected by Elasticsearch. This is usually due to mapping or syntax-related issues in the indexing requests. The index failed count represents the number of rejected indexing operations.

Why does this occur?

There are several reasons why indexing operations may fail in Elasticsearch. Some common causes include:

1. Incorrect mapping: The mapping defined for the index may not match the data being indexed, leading to rejection of indexing requests.
2. Syntax errors: The indexing requests may contain syntax errors or invalid data, causing Elasticsearch to reject the requests.
3. Resource constraints: Elasticsearch may be running low on resources, such as memory or disk space, leading to rejection of indexing requests.

Possible impact and consequences of failed indexing

A high index failed count can have several negative consequences for your Elasticsearch system:

1. Data loss: As indexing requests are rejected, the data in those requests will not be stored in Elasticsearch, leading to data loss.
2. Degraded search quality: The absence of indexed data can affect the quality and accuracy of search results in your system.
3. Performance issues: Repeatedly rejected indexing requests can put additional strain on your Elasticsearch cluster, potentially leading to performance degradation.

How to resolve

To resolve the issue of failed indexing operations, follow these steps:

1. Investigate the cause: Check the logs of your client applications to determine why indexing is failing. This can help you identify issues with mapping, syntax, or resources.

Command:

tail -f /path/to/your/client/application/logs

2. Fix mapping issues: If the issue is related to incorrect mapping, you might need to update the mapping for the index to match the data being indexed. Furthermore, since mappings cannot be changed after the index is created, you might need to recreate your index with the correct mapping. You can use the free Opster Template Analyzer tool to figure out any suboptimal mapping configurations.

3. Correct syntax errors: If the issue is due to syntax errors or invalid data in indexing requests, correct the errors in your client application and resend the requests.

4. Address resource constraints: If the issue is related to resource constraints, consider increasing the resources allocated to your Elasticsearch cluster, such as memory or disk space. You can also optimize your indexing process by using bulk indexing or adjusting the refresh interval.

Command to update refresh interval:

PUT /your_index/_settings
{
  "index": {
    "refresh_interval": "30s"
  }
}

Conclusion

By understanding the meaning, causes, and potential impact of failed indexing operations in Elasticsearch, you can take appropriate steps to resolve the issue and ensure the smooth functioning of your system. Regularly monitoring your Elasticsearch cluster and addressing issues promptly can help you maintain optimal performance and data integrity.