One of many great recent posts from Sematext on ElasticSearch performance.
We’ve been doing a ton of work with ElasticSearch. Not long ago, we had a few situations where ElasticSearch would “eat” all the JVM heap memory we give it. It was so hungry, we could not feed it enough memory to keep it happy. It was insatiable. After some troubleshooting and looking at SPM for ElasticSearch (btw. we released a new version of the SPM agent earlier this week, so if you don’t have it, go grab agent v1.5.0) we figured out the cause – ElasticSearch default field cache setting was not quite right for our deployment. In this post we’ll share our experience on this topic, explain why this was happening and how to minimize the negative effect of large field caches.
ElasticSearch Cache Types
There are two types of caches in ElasticSearch whose behaviors you can control. The first cache is the filter cache. This cache is responsible for…
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