# High CPU Usage on Data Node

**URL:** <https://discuss.elastic.co/t/high-cpu-usage-on-data-node/57879>\
**Category:** Elasticsearch\
**Created:** [August 12, 2016, 5:16am UTC](https://discuss.elastic.co/t/high-cpu-usage-on-data-node/57879 "2016-08-12T05:16:53Z")\
**Posts on this page:** 5\
**Page:** 1

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**Author:** ![astro](https://avatars.discourse-cdn.com/v4/letter/a/9dc877/32.png) [@astro](https://discuss.elastic.co/u/astro)\
**Post date:** [August 12, 2016, 5:16am UTC](https://discuss.elastic.co/t/high-cpu-usage-on-data-node/57879/1 "2016-08-12T05:16:53Z")

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Hi team ,

I have a linux server on which I am running elasticsearch datanode , Config of server is

48G of RAM , 1 TB HDD , 8 Core

. I am constantly having load of around 5-10

10:45:27 up 51 days, 17:54, 1 user, load average: 5.00, 6.04, 5.62

Please help me so that load can be made low .

Thanks & Regards  
Arvind

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**Author:** ![warkolm](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/warkolm/32/39224_2.png) [@warkolm](https://discuss.elastic.co/u/warkolm)\
**Post date:** [August 12, 2016, 5:18am UTC](https://discuss.elastic.co/t/high-cpu-usage-on-data-node/57879/2 "2016-08-12T05:18:46Z")

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Why do you want to lower i? Is it causing issues?

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**Author:** ![astro](https://avatars.discourse-cdn.com/v4/letter/a/9dc877/32.png) [@astro](https://discuss.elastic.co/u/astro)\
**Post date:** [August 12, 2016, 5:20am UTC](https://discuss.elastic.co/t/high-cpu-usage-on-data-node/57879/3 "2016-08-12T05:20:10Z")

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Seems due to this kibana is responding very slowly . and indexing performance is also low

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**Author:** ![taras](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/taras/32/507_2.png) [@taras](https://discuss.elastic.co/u/taras)\
**Post date:** [August 12, 2016, 9:32pm UTC](https://discuss.elastic.co/t/high-cpu-usage-on-data-node/57879/4 "2016-08-12T21:32:13Z")

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If you're saying that load of 5-10 on an 8 core machine is causing really slow response, I would suggest adding another machine. If your load actually hovers closer to 5, which your average suggests, then moving to an _SSD_ instead of _HDD_ would be a good boost.

Main returns you're going to see are going to be from optimizing your mappings, and the way you index / query.

Taking a few shots in the dark here:

- Make sure you're indexing in bulk instead of single documents
- Increase `refresh_interval` for the index to a larger value of `60s` or more.
- Don't allocate more than 31GB to your elasticsearch heap. 32G+ requires 64-bit pointers, so you get less by giving your process more.
- If reading disk indeed is a major bottleneck, try giving your elastic process 20G heap to leave more room for filesystem cache. (monitor with `iostat`)
- Create your index with 7-8 shards instead of default 5, to spread load more across the cores if you are mainly indexing and have a few Kibana users to look at the data.

For more help please share mappings, sample of data, indexing and query patterns.

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**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [July 5, 2017, 10:27pm UTC](https://discuss.elastic.co/t/high-cpu-usage-on-data-node/57879/5 "2017-07-05T22:27:56Z")

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