# \[Scaling elastic server\] how much load can elastic search handle?

**URL:** <https://discuss.elastic.co/t/scaling-elastic-server-how-much-load-can-elastic-search-handle/17259>\
**Category:** Elasticsearch\
**Created:** [April 29, 2014, 1:02pm UTC](https://discuss.elastic.co/t/scaling-elastic-server-how-much-load-can-elastic-search-handle/17259 "2014-04-29T13:02:24Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![Abrar\_Sheikh](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/abrar_sheikh/32/46187_2.png) [@Abrar\_Sheikh](https://discuss.elastic.co/u/Abrar_Sheikh)\
**Post date:** [April 29, 2014, 1:02pm UTC](https://discuss.elastic.co/t/scaling-elastic-server-how-much-load-can-elastic-search-handle/17259/1 "2014-04-29T13:02:24Z")

</div>

Hi,

I have a single aws EC2 large instance with 7.5 GB ram and 100 GB harddrive  
dual core 2.6 GHz. My elastic instance on a average has around 10,000,000  
records. I use somewhat complex queries. I am calling elastic apis from my  
PHP code which is exposed as a rest service(needed to do some post  
processing of data). my question is how much load can my server handle and  
at what point do i shift to a multi node architecture. What effect does #  
of shards and replication have on performance. With my current system  
configuration how many queries per second(qps) can my elastic search  
handle?

Thanks and Regards,  
Abrar.

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**Author:** ![radu\_gheorghe](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/radu_gheorghe/32/556_2.png) [@radu\_gheorghe](https://discuss.elastic.co/u/radu_gheorghe)\
**Post date:** [April 29, 2014, 1:40pm UTC](https://discuss.elastic.co/t/scaling-elastic-server-how-much-load-can-elastic-search-handle/17259/2 "2014-04-29T13:40:48Z")

</div>

Hello Abrar,

The answer to your questions depends a lot on how your data and queries  
look like, how often you run them and how often new data is indexed. You  
could paste those details here, but I don't think anyone could give you a  
definite answer, maybe more of a guesstimate based on experience with  
similar patterns.

The best way to find out is to install some performance monitoring tool  
(there are many out there, you can find one by clicking the link in my  
signature) and start running tests with production-like data and queries.  
And then you'll see how much your machine can handle and where the  
bottlenecks are.

## Best regards, Radu

Performance Monitoring \* Log Analytics \* Search Analytics  
Solr & Elasticsearch Support \* [http://sematext.com/](http://sematext.com/)

On Tue, Apr 29, 2014 at 4:02 PM, Abrar Sheikh [abrar2002as@gmail.com](mailto:abrar2002as@gmail.com) wrote:

> Hi,
> 
> I have a single aws EC2 large instance with 7.5 GB ram and 100 GB  
> harddrive dual core 2.6 GHz. My elastic instance on a average has around  
> 10,000,000 records. I use somewhat complex queries. I am calling elastic  
> apis from my PHP code which is exposed as a rest service(needed to do some  
> post processing of data). my question is how much load can my server  
> handle and at what point do i shift to a multi node architecture. What  
> effect does # of shards and replication have on performance. With my  
> current system configuration how many queries per second(qps) can my  
> Elasticsearch handle?
> 
> Thanks and Regards,  
> Abrar.
> 
> --  
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> .  
> For more options, visit [https://groups.google.com/d/optout](https://groups.google.com/d/optout).

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**Author:** ![Abrar\_Sheikh](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/abrar_sheikh/32/46187_2.png) [@Abrar\_Sheikh](https://discuss.elastic.co/u/Abrar_Sheikh)\
**Post date:** [April 29, 2014, 2:05pm UTC](https://discuss.elastic.co/t/scaling-elastic-server-how-much-load-can-elastic-search-handle/17259/3 "2014-04-29T14:05:33Z")

</div>

Data that i am storing is a tweet response from twitter which flows in via  
a streaming API, so the inserts are quite fast (roughly 50-80 inserts/sec).

query look something like this  
{  
"query": {  
"filtered": {  
"filter": {  
"and": [{ //i have a range slider in the UI which  
selects tweets on rank range  
"range": {  
"rank": {  
"from": "500",  
"to": "1000",  
"include\_upper": true  
}  
}  
},  
{ //if there are custom query terms provided by the  
quer  
"query": {  
"terms": {  
"entities": ["searchString"],  
"minimum\_should\_match": # of search terms  
}  
}  
},  
{  
"missing": {  
"field": "in\_reply\_to\_status\_id",  
"existence": true,  
"null\_value": true  
}  
},  
{ //have a country field query  
"query": {  
"term": {  
"user.country\_new": "in"  
}  
}  
}]  
}  
}  
},  
"from": "0", //paging  
"size": "50",  
"sort": [{ //sorting  
"created\_at": {  
"order": "desc"  
}  
}],  
"aggregations": {  
"hashtags\_freq": [{ //get hashtag freqency aggr in  
result set  
"terms": {  
"field": "entities",  
"include": "(#[a-zA-Z][a-zA-Z0-9\_-]+)",  
"size": 0  
},  
"aggregations": {  
"unique\_users": {  
"terms": {  
"field": "user.screen\_name",  
"size": 0  
}  
}  
}  
}],  
"user\_tweet\_frequency": { //# of tweets by all the users in  
resultset  
"terms": {  
"field": "user.screen\_name",  
"size": 0  
}  
}  
}  
}

this query is fired by all the users that come to our site and it is called  
with varying values of rank range

On Tue, Apr 29, 2014 at 7:10 PM, Radu Gheorghe  
[radu.gheorghe@sematext.com](mailto:radu.gheorghe@sematext.com)wrote:

> Hello Abrar,
> 
> The answer to your questions depends a lot on how your data and queries  
> look like, how often you run them and how often new data is indexed. You  
> could paste those details here, but I don't think anyone could give you a  
> definite answer, maybe more of a guesstimate based on experience with  
> similar patterns.
> 
> The best way to find out is to install some performance monitoring tool  
> (there are many out there, you can find one by clicking the link in my  
> signature) and start running tests with production-like data and queries.  
> And then you'll see how much your machine can handle and where the  
> bottlenecks are.
> 
> ## Best regards, Radu
> 
> Performance Monitoring \* Log Analytics \* Search Analytics  
> Solr & Elasticsearch Support \* [http://sematext.com/](http://sematext.com/)
> 
> On Tue, Apr 29, 2014 at 4:02 PM, Abrar Sheikh [abrar2002as@gmail.com](mailto:abrar2002as@gmail.com)wrote:
> 
> > Hi,
> > 
> > I have a single aws EC2 large instance with 7.5 GB ram and 100 GB  
> > harddrive dual core 2.6 GHz. My elastic instance on a average has around  
> > 10,000,000 records. I use somewhat complex queries. I am calling elastic  
> > apis from my PHP code which is exposed as a rest service(needed to do some  
> > post processing of data). my question is how much load can my server  
> > handle and at what point do i shift to a multi node architecture. What  
> > effect does # of shards and replication have on performance. With my  
> > current system configuration how many queries per second(qps) can my  
> > Elasticsearch handle?
> > 
> > Thanks and Regards,  
> > Abrar.
> > 
> > --  
> > You received this message because you are subscribed to the Google Groups  
> > "elasticsearch" group.  
> > To unsubscribe from this group and stop receiving emails from it, send an  
> > email to [elasticsearch+unsubscribe@googlegroups.com](mailto:elasticsearch+unsubscribe@googlegroups.com).
> > 
> > To view this discussion on the web visit  
> > [https://groups.google.com/d/msgid/elasticsearch/49f1dbbe-42e6-445e-ba6e-b9d358d8908f%40googlegroups.com](https://groups.google.com/d/msgid/elasticsearch/49f1dbbe-42e6-445e-ba6e-b9d358d8908f%40googlegroups.com)[https://groups.google.com/d/msgid/elasticsearch/49f1dbbe-42e6-445e-ba6e-b9d358d8908f%40googlegroups.com?utm\_medium=email&utm\_source=footer](https://groups.google.com/d/msgid/elasticsearch/49f1dbbe-42e6-445e-ba6e-b9d358d8908f%40googlegroups.com?utm_medium=email&utm_source=footer)  
> > .  
> > For more options, visit [https://groups.google.com/d/optout](https://groups.google.com/d/optout).
> 
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> .
> 
> For more options, visit [https://groups.google.com/d/optout](https://groups.google.com/d/optout).

--  
Abrar Sheikh

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**Author:** ![Michael\_Salmon](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/michael_salmon/32/5330_2.png) [@Michael\_Salmon](https://discuss.elastic.co/u/Michael_Salmon)\
**Post date:** [April 29, 2014, 2:11pm UTC](https://discuss.elastic.co/t/scaling-elastic-server-how-much-load-can-elastic-search-handle/17259/4 "2014-04-29T14:11:21Z")

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I would suggest that you install something like bigdesk or marvel to check  
your usage, in particular heap, threads and file descriptors.

Every shard is a Lucene index and hence the more shards you have the more  
searches that you can do in parallel but you also need memory and file  
descriptors for every shard.

I don't believe that anyone could predict with any certainty how quick your  
searches will be as there are many variables. Try running your queries with  
one of the query browsers like sense and you will see how long the search  
took, it is in the took field of the reply.

On Tuesday, 29 April 2014 15:02:24 UTC+2, Abrar Sheikh wrote:

> Hi,
> 
> I have a single aws EC2 large instance with 7.5 GB ram and 100 GB  
> harddrive dual core 2.6 GHz. My elastic instance on a average has around  
> 10,000,000 records. I use somewhat complex queries. I am calling elastic  
> apis from my PHP code which is exposed as a rest service(needed to do some  
> post processing of data). my question is how much load can my server  
> handle and at what point do i shift to a multi node architecture. What  
> effect does # of shards and replication have on performance. With my  
> current system configuration how many queries per second(qps) can my  
> Elasticsearch handle?
> 
> Thanks and Regards,  
> Abrar.

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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 6, 2017, 1:32am UTC](https://discuss.elastic.co/t/scaling-elastic-server-how-much-load-can-elastic-search-handle/17259/5 "2017-07-06T01:32:42Z")

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