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In addition to learning about Elasticsearch loaded master nodes and the three ways to resolve this issue, we recommend you run the Elasticsearch Health Check-Up. It will detect issues and improve your Elasticsearch performance by analyzing your shard sizes, threadpools, memory, snapshots, disk watermarks and more.
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.
Sometimes you can observe that the CPU and load on one of your master nodes is higher than on others.
This is absolutely normal behavior assuming that the loaded master node is the elected master. Although you need more than one master node (and ideally an odd number), only one of these nodes will be active at any one time. If CPU is very high and the node appears to be overloaded, then this may be cause for concern, since an overloaded master node may cause instability in the cluster.
How to resolve it
How to fix loaded master nodes in Elasticsearch
- Check for split brain
If you are using an Elasticsearch version earlier than 7, then make sure you are not suffering from the split brain problem described here: Elasticsearch Split Brain – A Thorough Guide, Including How To Avoid It.
- Check other processes
Ensure that there are no other processes running on the master node which could cause it to become unstable.
- Check the master node logs
Check the loaded master node logs. If the elected master is loaded, the log can reveal the potential causes, such as: high rate of mapping exceptions, too many doc types (for ES versions older than v6), or large metadata – too many fields/indices/shards.
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