Elasticsearch Elasticsearch Indexing Issues in Data Tiers

By Opster Team

Updated: Jul 4, 2023

| 2 min read

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Before you dig into the details of this guide, have you tried asking OpsGPT? You’ll receive concise answers that will help streamline your Elasticsearch/OpenSearch operations.

Try OpsGPT now for step-by-step guidance and tailored insights into your search operation.

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What does this mean?

It is not recommended to run indexing operations on warm data nodes. Indexing should ideally be performed on hot data nodes to ensure optimal performance and resource utilization.

This issue is monitored by Opster AutoOps in real-time with personalized recommendations provided for your own system. You can also configure notifications to avoid this issue forming in the future.

Why does this occur?

This may occur due to various reasons, such as misconfiguration of data tier architecture, incorrect index templates, or improper mappings. It is essential to identify the root cause of the issue to prevent it from happening in the future.

Possible impact and consequences of indexing issues in data tiers

Indexing on warm data nodes can lead to several issues, including:

  1. Reduced performance: Warm nodes are optimized for read-heavy operations, and indexing on these nodes can lead to slower indexing and query performance.
  2. Increased resource utilization: Indexing on warm nodes can consume more resources than necessary, leading to higher costs and potential resource contention.
  3. Data inconsistency: If indexing is happening on both hot and warm nodes, it can lead to data inconsistency and difficulty in managing the data lifecycle.

How to resolve

To resolve the issue of indexing on warm data nodes, follow these recommendations:

  1. Reappraise your data tier architecture: Review your current data tier setup and ensure that it best suits your operational needs. Make necessary adjustments to optimize resource utilization and performance.
  1. Review templates and mappings: Examine the templates and settings for the indices to prevent indexing on warm data nodes in the future. Ensure that the correct data tier is specified in the index settings. You can use the free Opster Template Analyzer tool to help you with this.
  2. Move indices to the right data tier: If you have indices on warm data nodes that should be on hot data nodes, move the shards of the index from the warm data node to the hot data node using the following command:
POST /_cluster/reroute
{
  "commands": [
    {
      "move": {
        "index": "<index_name>",
        "shard": <shard_number>,
        "from_node": "<source_warm_node>",
        "to_node": "<destination_hot_node>"
      }
    }
  ]
}

Replace `<index_name>`, `<shard_number>`, `<source_warm_node>`, and `<destination_hot_node>` with the appropriate values for your cluster.

Conclusion

By following this guide, you should be able to resolve the issue of indexing on warm data nodes in Elasticsearch. Ensuring that indexing operations are performed on the appropriate data tier will help optimize performance, resource utilization, and data management.

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