# Memory usage of the machine with ES is continuously increasing

**URL:** <https://discuss.elastic.co/t/memory-usage-of-the-machine-with-es-is-continuously-increasing/23537>\
**Category:** Elasticsearch\
**Created:** [May 4, 2015, 10:47am UTC](https://discuss.elastic.co/t/memory-usage-of-the-machine-with-es-is-continuously-increasing/23537 "2015-05-04T10:47:40Z")\
**Posts on this page:** 1\
**Showing post:** 10

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**Author:** ![vangap](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/vangap/32/44927_2.png) [@vangap](https://discuss.elastic.co/u/vangap)\
**Post date:** [May 20, 2015, 10:03am UTC](https://discuss.elastic.co/t/memory-usage-of-the-machine-with-es-is-continuously-increasing/23537/10 "2015-05-20T10:03:40Z")

</div>

I have straced elasticsearch for a couple of minutes  
strace -fp PID -o file.txt

out of the 40k+ events recorded  
2.2k + events have resulted in errors like this

> <https://gist.github.com/vanga/55ca296f737b3c1fb9a2>

I think this is the reason for the dentry bloating, though I am not sure if  
there is some thing wrong with my cluster or not.

On Monday, May 4, 2015 at 4:17:40 PM UTC+5:30, Pradeep Reddy wrote:

> ES version 1.5.2  
> Arch Linux on Amazon EC2  
> of the available 16 GB, 8 GB is heap (mlocked). Memory consumption is  
> continuously increasing (225 MB per day).  
> Total no of documents is around 800k, 500 MB.
> 
> cat /proc/meminfo has
> 
> > Slab: 3424728 kB
> 
> SReclaimable: 3407256 kB
> 
> > 
> 
> curl -XGET '[http://localhost:9200/\_nodes/stats/jvm?pretty](http://localhost:9200/_nodes/stats/jvm?pretty)'
> 
> > "heap\_used\_in\_bytes" : 5788779888,  
> > "heap\_used\_percent" : 67,  
> > "heap\_committed\_in\_bytes" : 8555069440,
> 
> slabtop  
> OBJS ACTIVE USE OBJ SIZE SLABS OBJ/SLAB CACHE SIZE  
> NAME  
> 17750313 17750313 100% 0.19K 845253 21 3381012K dentry
> 
> So the continuous increase in memory usage is because of the slab usage I  
> think, If I restart ES, then slab memory is freed. I see that ES still has  
> some free heap available, but from elastic documentation
> 
> > Lucene is designed to leverage the underlying OS for caching in-memory  
> > data structures. Lucene segments are stored in individual files. Because  
> > segments are immutable, these files never change. This makes them very  
> > cache friendly, and the underlying OS will happily keep hot segments  
> > resident in memory for faster access.
> 
> My question is, should I add more nodes or increase the ram of each node  
> to let lucene use as much memory as it wants ? how significant performance  
> difference will be there if I choose to upgrade ES machines to have more  
> RAM.
> 
> Or, can I make some optimizations that decreases the slab usage or clean  
> slab memory partially?

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