# Some ES stats (at yfrog.com)

**URL:** <https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753>\
**Category:** Elasticsearch\
**Created:** [February 20, 2012, 5:58am UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753 "2012-02-20T05:58:57Z")\
**Posts on this page:** 7\
**Page:** 1

<div class="post-metadata">

**Author:** ![jacque74](https://avatars.discourse-cdn.com/v4/letter/j/4af34b/32.png) [@jacque74](https://discuss.elastic.co/u/jacque74)\
**Post date:** [February 20, 2012, 5:58am UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753/1 "2012-02-20T05:58:57Z")

</div>

Hello all, I thought I would share some stats on how we are using  
ElasticSearch.

At yfrog, we are indexing corpus of tweets that users use in  
conjunction with photos uploaded to twitter from mobile and web. Our  
total index is about 950 million docs. We run 500 shards across 12  
servers, which are 8 core x 16GB, and some are 12 core x 32GB boxes.  
Routing allows us to provide timeline search (per user), so that each  
user's data is always in one shard. Here is a screenshot btw:  
[http://a.yfrog.com/img703/8096/xil.png](http://a.yfrog.com/img703/8096/xil.png)

Each shard is about 1G large, which makes total data to be about 1TB  
with 50% of being replicated (e.g. 1 replica). The other interesting  
parts is that each server runs with 4x2TB disks, with ZFS over them.  
So far we have had no issues with ZFS on linux, and servers have had  
definite performance improvement.

We are currently indexing 3ml new docs per day (new tweets). So far  
the challenges have been to keep file descriptors low, we are  
basically running with ulimit -n 256000. Merging down to appropriate  
number of segments under shard is always a must, but that  
significantly taxes CPU, and slows down bulk indexing should we ever  
try to re-index the whole corpus.

On the other hand, as you can see from the screenshot the read search  
performance is just awesome, you can try some searches yourself at  
[http://yfrog.com/user/TechCrunch/profile](http://yfrog.com/user/TechCrunch/profile)

-Jack

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<div class="post-metadata">

**Author:** ![Clinton\_Gormley](https://avatars.discourse-cdn.com/v4/letter/c/50afbb/32.png) [@Clinton\_Gormley](https://discuss.elastic.co/u/Clinton_Gormley)\
**Post date:** [February 20, 2012, 6:46am UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753/2 "2012-02-20T06:46:47Z")

</div>

Hiya Jack

On Sun, 2012-02-19 at 21:58 -0800, Jack Levin wrote:

> Hello all, I thought I would share some stats on how we are using  
> Elasticsearch.

great post - thanks for sharing.

> The other interesting  
> parts is that each server runs with 4x2TB disks, with ZFS over them.  
> So far we have had no issues with ZFS on linux, and servers have had  
> definite performance improvement.

That's very interesting. I hadn't seen that native ZFS was available for  
linux. A link for the interested: [http://zfsonlinux.org/](http://zfsonlinux.org/)

clint

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<div class="post-metadata">

**Author:** ![dadoonet](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/dadoonet/32/137187_2.png) [@dadoonet](https://discuss.elastic.co/u/dadoonet)\
**Post date:** [February 20, 2012, 6:46am UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753/3 "2012-02-20T06:46:57Z")

</div>

Thanks for sharing this.

It would be nice to add it here : [Elasticsearch Platform — Find real-time answers at scale | Elastic](http://www.elasticsearch.org/users/)

David 😉  
@dadoonet

Le 20 févr. 2012 à 06:58, Jack Levin [magnito@gmail.com](mailto:magnito@gmail.com) a écrit :

> Hello all, I thought I would share some stats on how we are using  
> Elasticsearch.
> 
> At yfrog, we are indexing corpus of tweets that users use in  
> conjunction with photos uploaded to twitter from mobile and web. Our  
> total index is about 950 million docs. We run 500 shards across 12  
> servers, which are 8 core x 16GB, and some are 12 core x 32GB boxes.  
> Routing allows us to provide timeline search (per user), so that each  
> user's data is always in one shard. Here is a screenshot btw:  
> [http://a.yfrog.com/img703/8096/xil.png](http://a.yfrog.com/img703/8096/xil.png)
> 
> Each shard is about 1G large, which makes total data to be about 1TB  
> with 50% of being replicated (e.g. 1 replica). The other interesting  
> parts is that each server runs with 4x2TB disks, with ZFS over them.  
> So far we have had no issues with ZFS on linux, and servers have had  
> definite performance improvement.
> 
> We are currently indexing 3ml new docs per day (new tweets). So far  
> the challenges have been to keep file descriptors low, we are  
> basically running with ulimit -n 256000. Merging down to appropriate  
> number of segments under shard is always a must, but that  
> significantly taxes CPU, and slows down bulk indexing should we ever  
> try to re-index the whole corpus.
> 
> On the other hand, as you can see from the screenshot the read search  
> performance is just awesome, you can try some searches yourself at  
> [ImageShack - Best place for all of your image hosting and image sharing needs](http://yfrog.com/user/TechCrunch/profile)
> 
> -Jack

---

<div class="post-metadata">

**Author:** ![Clinton\_Gormley](https://avatars.discourse-cdn.com/v4/letter/c/50afbb/32.png) [@Clinton\_Gormley](https://discuss.elastic.co/u/Clinton_Gormley)\
**Post date:** [February 20, 2012, 6:47am UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753/4 "2012-02-20T06:47:08Z")

</div>

Hiya Jack

On Sun, 2012-02-19 at 21:58 -0800, Jack Levin wrote:

> Hello all, I thought I would share some stats on how we are using  
> Elasticsearch.

great post - thanks for sharing.

> The other interesting  
> parts is that each server runs with 4x2TB disks, with ZFS over them.  
> So far we have had no issues with ZFS on linux, and servers have had  
> definite performance improvement.

That's very interesting. I hadn't seen that native ZFS was available for  
linux. A link for the interested: [http://zfsonlinux.org/](http://zfsonlinux.org/)

clint

---

<div class="post-metadata">

**Author:** ![kimchy](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/kimchy/32/44952_2.png) [@kimchy](https://discuss.elastic.co/u/kimchy)\
**Post date:** [February 20, 2012, 1:19pm UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753/5 "2012-02-20T13:19:28Z")

</div>

Jack, really thanks for sharing the data!. Its really important for people to share this type of info with elasticsearch users.

Regarding the segments, by default, elasticsearch uses the tiered merge policy ([Elasticsearch Platform — Find real-time answers at scale | Elastic](http://www.elasticsearch.org/guide/reference/index-modules/merge.html)). The important thing to remember about it is that it has (an estimated) max size bound on a segment. The max\_merged\_segment is the setting, and it defaults to 5gb (same as in Lucene). This can cause for many segments to be created for a large index. I have been back and forth and possibly increasing this default value to a higher value (which will cause more merges, but less resources being used - file descriptors, memory, faster searches).

One thing that you can use to gauge it is the segments API, which returns detailed data on segments used in each shard of an index. Lukas has been doing amazing job with big desk, I hope that we will be able to improve on it and move it to start providing "index" level stats on top of node level focused stats that it provides today. One of the things we will do then is to provide a nice visualization of the segments each shard has, so people can decide what good values can eb set (all can eb set in realtime on a live index), or even when to issue optimization calls more easily.

On Monday, February 20, 2012 at 7:58 AM, Jack Levin wrote:

> Hello all, I thought I would share some stats on how we are using  
> Elasticsearch.
> 
> At yfrog, we are indexing corpus of tweets that users use in  
> conjunction with photos uploaded to twitter from mobile and web. Our  
> total index is about 950 million docs. We run 500 shards across 12  
> servers, which are 8 core x 16GB, and some are 12 core x 32GB boxes.  
> Routing allows us to provide timeline search (per user), so that each  
> user's data is always in one shard. Here is a screenshot btw:  
> [http://a.yfrog.com/img703/8096/xil.png](http://a.yfrog.com/img703/8096/xil.png)
> 
> Each shard is about 1G large, which makes total data to be about 1TB  
> with 50% of being replicated (e.g. 1 replica). The other interesting  
> parts is that each server runs with 4x2TB disks, with ZFS over them.  
> So far we have had no issues with ZFS on linux, and servers have had  
> definite performance improvement.
> 
> We are currently indexing 3ml new docs per day (new tweets). So far  
> the challenges have been to keep file descriptors low, we are  
> basically running with ulimit -n 256000. Merging down to appropriate  
> number of segments under shard is always a must, but that  
> significantly taxes CPU, and slows down bulk indexing should we ever  
> try to re-index the whole corpus.
> 
> On the other hand, as you can see from the screenshot the read search  
> performance is just awesome, you can try some searches yourself at  
> [ImageShack - Best place for all of your image hosting and image sharing needs](http://yfrog.com/user/TechCrunch/profile)
> 
> -Jack

---

<div class="post-metadata">

**Author:** ![Nick\_Dimiduk](https://avatars.discourse-cdn.com/v4/letter/n/c77e96/32.png) [@Nick\_Dimiduk](https://discuss.elastic.co/u/Nick_Dimiduk)\
**Post date:** [March 1, 2012, 7:11pm UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753/6 "2012-03-01T19:11:08Z")

</div>

Hi Jack,

Thanks for sharing! I'm curious: can you provide any throughput  
numbers? Ie, how many concurrent user requests you're able to serve  
from this cluster and rough latency numbers. Do you use the geospatial  
capacities at all?

Thanks,  
Nick

On Feb 19, 9:58 pm, Jack Levin [magn...@gmail.com](mailto:magn...@gmail.com) wrote:

> Hello all, I thought I would share some stats on how we are using  
> Elasticsearch.
> 
> At yfrog, we are indexing corpus of tweets that users use in  
> conjunction with photos uploaded to twitter from mobile and web. Our  
> total index is about 950 million docs. We run 500 shards across 12  
> servers, which are 8 core x 16GB, and some are 12 core x 32GB boxes.  
> Routing allows us to provide timeline search (per user), so that each  
> user's data is always in one shard. Here is a screenshot btw:[http://a.yfrog.com/img703/8096/xil.png](http://a.yfrog.com/img703/8096/xil.png)
> 
> Each shard is about 1G large, which makes total data to be about 1TB  
> with 50% of being replicated (e.g. 1 replica). The other interesting  
> parts is that each server runs with 4x2TB disks, with ZFS over them.  
> So far we have had no issues with ZFS on linux, and servers have had  
> definite performance improvement.
> 
> We are currently indexing 3ml new docs per day (new tweets). So far  
> the challenges have been to keep file descriptors low, we are  
> basically running with ulimit -n 256000. Merging down to appropriate  
> number of segments under shard is always a must, but that  
> significantly taxes CPU, and slows down bulk indexing should we ever  
> try to re-index the whole corpus.
> 
> On the other hand, as you can see from the screenshot the read search  
> performance is just awesome, you can try some searches yourself athttp://yfrog.com/user/TechCrunch/profile
> 
> -Jack

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [July 6, 2017, 3:37am UTC](https://discuss.elastic.co/t/some-es-stats-at-yfrog-com/6753/7 "2017-07-06T03:37:39Z")

</div>


