# Slow ElasticSearch queries and huge load
**URL:** https://discuss.elastic.co/t/slow-elasticsearch-queries-and-huge-load/9987
**Category:** Elasticsearch
**Created:** [December 7, 2012, 2:45pm UTC](https://discuss.elastic.co/t/slow-elasticsearch-queries-and-huge-load/9987 "2012-12-07T14:45:54Z")
**Posts on this page:** 5
**Page:** 1
### Author:  [@Piotr](https://discuss.elastic.co/u/Piotr)
#### Post date: [December 7, 2012, 2:45pm UTC](https://discuss.elastic.co/t/slow-elasticsearch-queries-and-huge-load/9987/1 "2012-12-07T14:45:54Z")
Hello,
I saw already some topics about the performance of ES here, but none of
them answered any of my questions. I would like to use ES for a search
engine. It looks really great how easy it is to create new nodes, connect
them together into clusters, make replicas etc. comparing to Solr or
Sphinx. I've created 3 nodes with 3 shards and 1 replica (+1 ElasticSearch
for balancing only). Each node is run with such JVM params:
-Xms5g -Xmx5g -Xss256k -Djava.awt.headless=true -XX:+UseParNewGC
-XX:+UseConcMarkSweepGC -XX:CMSInitiatingOccupancyFraction=75
-XX:+UseCMSInitiatingOccupancyOnly -XX:+HeapDumpOnOutOfMemoryError
-XX:+UseTLAB -XX:+CMSClassUnloadingEnabled -XX:+CMSPermGenSweepingEnabled
Machine has 16GB or RAM, 4 cores Intel i5 processor @ 3.40 GHz
There is only one index with one mapping which look like that:
{
"files" : {
"groups" : {
"\_source" : {
"enabled" : false
},
"properties" : {
"id" : {
"type" : "string",
"index" : "no",
"store" : "yes"
},
"clicks" : {
"type" : "integer"
},
"date\_added" : {
"type" : "long"
},
"desc" : {
"type" : "string",
"term\_vector" : "with\_positions\_offsets"
},
"extension\_attr" : {
"type" : "short"
},
"group\_id" : {
"type" : "long",
"store" : "yes"
},
"host" : {
"type" : "string",
"term\_vector" : "with\_positions\_offsets"
},
"hosting\_id" : {
"type" : "integer"
},
"name" : {
"type" : "string",
"boost" : 3.0,
"term\_vector" : "with\_positions\_offsets"
},
"size" : {
"type" : "integer"
},
"source\_title" : {
"type" : "string",
"term\_vector" : "with\_positions\_offsets"
},
"source\_url" : {
"type" : "string",
"term\_vector" : "with\_positions\_offsets"
}
}
}
}
}
In this index there are around 30M records for both ElasticSearch and
Sphinx Search. Whether Sphinx on the same machine and single node makes
response for a MATCH query like MATCH('test') takes around 0.14s then in
ElasticSearch it's 2,3s. I'm surprised of these results. I'm not sure if
it's normal time for a query which does not reside in cache. I'm thinking
if there's any possibility to tune ES.
--
---
### Author:  [@Piotr](https://discuss.elastic.co/u/Piotr)
#### Post date: [December 10, 2012, 7:49am UTC](https://discuss.elastic.co/t/slow-elasticsearch-queries-and-huge-load/9987/2 "2012-12-10T07:49:46Z")
Forgot to put the exact query:
{
"query": {
"custom\_score": {
"query": {
"query\_string": {
"default\_field": "\_all",
"default\_operator": "and",
"query": "test"
}
}
}
},
"fields": [
"group\_id",
"name",
"date\_added"
],
"from": 0,
"size": 50,
"sort": ,
"facets": {}
}
Is this normal to have responses around 2s for such a query?
W dniu piątek, 7 grudnia 2012 15:45:54 UTC+1 użytkownik Piotr napisał:
> Hello,
>
> I saw already some topics about the performance of ES here, but none of
> them answered any of my questions. I would like to use ES for a search
> engine. It looks really great how easy it is to create new nodes, connect
> them together into clusters, make replicas etc. comparing to Solr or
> Sphinx. I've created 3 nodes with 3 shards and 1 replica (+1 Elasticsearch
> for balancing only). Each node is run with such JVM params:
>
> -Xms5g -Xmx5g -Xss256k -Djava.awt.headless=true -XX:+UseParNewGC
> -XX:+UseConcMarkSweepGC -XX:CMSInitiatingOccupancyFraction=75
> -XX:+UseCMSInitiatingOccupancyOnly -XX:+HeapDumpOnOutOfMemoryError
> -XX:+UseTLAB -XX:+CMSClassUnloadingEnabled -XX:+CMSPermGenSweepingEnabled
>
> Machine has 16GB or RAM, 4 cores Intel i5 processor @ 3.40 GHz
>
> There is only one index with one mapping which look like that:
>
> {
> "files" : {
> "groups" : {
> "\_source" : {
> "enabled" : false
> },
> "properties" : {
> "id" : {
> "type" : "string",
> "index" : "no",
> "store" : "yes"
> },
> "clicks" : {
> "type" : "integer"
> },
> "date\_added" : {
> "type" : "long"
> },
> "desc" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> },
> "extension\_attr" : {
> "type" : "short"
> },
> "group\_id" : {
> "type" : "long",
> "store" : "yes"
> },
> "host" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> },
> "hosting\_id" : {
> "type" : "integer"
> },
> "name" : {
> "type" : "string",
> "boost" : 3.0,
> "term\_vector" : "with\_positions\_offsets"
> },
> "size" : {
> "type" : "integer"
> },
> "source\_title" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> },
> "source\_url" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> }
> }
> }
> }
> }
>
> In this index there are around 30M records for both Elasticsearch and
> Sphinx Search. Whether Sphinx on the same machine and single node makes
> response for a MATCH query like MATCH('test') takes around 0.14s then in
> Elasticsearch it's 2,3s. I'm surprised of these results. I'm not sure if
> it's normal time for a query which does not reside in cache. I'm thinking
> if there's any possibility to tune ES.
--
---
### Author:  [@otisg](https://discuss.elastic.co/u/otisg)
#### Post date: [December 10, 2012, 10:34pm UTC](https://discuss.elastic.co/t/slow-elasticsearch-queries-and-huge-load/9987/3 "2012-12-10T22:34:22Z")
There could be many reasons for this and one would have to dig in. The
most basic thing that comes to mind is that on this 1 server you likely
have 5 index shards (default), which is pointless and adds overhead. Make
it 1, reindex, and then try. I'd love to see the before and after
comparison.
## Otis
ELASTICSEARCH Performance Monitoring - [Sematext Monitoring | Infrastructure Monitoring Service](http://sematext.com/spm/index.html)
Search Analytics - [Cloud Monitoring Tools & Services | Sematext](http://sematext.com/search-analytics/index.html)
On Friday, December 7, 2012 9:45:54 AM UTC-5, Piotr wrote:
> Hello,
>
> I saw already some topics about the performance of ES here, but none of
> them answered any of my questions. I would like to use ES for a search
> engine. It looks really great how easy it is to create new nodes, connect
> them together into clusters, make replicas etc. comparing to Solr or
> Sphinx. I've created 3 nodes with 3 shards and 1 replica (+1 Elasticsearch
> for balancing only). Each node is run with such JVM params:
>
> -Xms5g -Xmx5g -Xss256k -Djava.awt.headless=true -XX:+UseParNewGC
> -XX:+UseConcMarkSweepGC -XX:CMSInitiatingOccupancyFraction=75
> -XX:+UseCMSInitiatingOccupancyOnly -XX:+HeapDumpOnOutOfMemoryError
> -XX:+UseTLAB -XX:+CMSClassUnloadingEnabled -XX:+CMSPermGenSweepingEnabled
>
> Machine has 16GB or RAM, 4 cores Intel i5 processor @ 3.40 GHz
>
> There is only one index with one mapping which look like that:
>
> {
> "files" : {
> "groups" : {
> "\_source" : {
> "enabled" : false
> },
> "properties" : {
> "id" : {
> "type" : "string",
> "index" : "no",
> "store" : "yes"
> },
> "clicks" : {
> "type" : "integer"
> },
> "date\_added" : {
> "type" : "long"
> },
> "desc" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> },
> "extension\_attr" : {
> "type" : "short"
> },
> "group\_id" : {
> "type" : "long",
> "store" : "yes"
> },
> "host" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> },
> "hosting\_id" : {
> "type" : "integer"
> },
> "name" : {
> "type" : "string",
> "boost" : 3.0,
> "term\_vector" : "with\_positions\_offsets"
> },
> "size" : {
> "type" : "integer"
> },
> "source\_title" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> },
> "source\_url" : {
> "type" : "string",
> "term\_vector" : "with\_positions\_offsets"
> }
> }
> }
> }
> }
>
> In this index there are around 30M records for both Elasticsearch and
> Sphinx Search. Whether Sphinx on the same machine and single node makes
> response for a MATCH query like MATCH('test') takes around 0.14s then in
> Elasticsearch it's 2,3s. I'm surprised of these results. I'm not sure if
> it's normal time for a query which does not reside in cache. I'm thinking
> if there's any possibility to tune ES.
--
---
### Author:  [@karmi](https://discuss.elastic.co/u/karmi)
#### Post date: [December 11, 2012, 9:16am UTC](https://discuss.elastic.co/t/slow-elasticsearch-queries-and-huge-load/9987/4 "2012-12-11T09:16:08Z")
> In this index there are around 30M records for both Elasticsearch and
> Sphinx Search.
> Whether Sphinx on the same machine and single node makes response for a
> MATCH query like MATCH('test') takes around 0.14s then in Elasticsearch
> it's 2,3s.
> I'm surprised of these results. I'm not sure if it's normal time for a
> query which does not reside in cache.
First, it's important to understand if you're interested in numbers for a
"cold" system, or a "warmed up" system, where Elasticsearch and OS caches
are filled and used. Usually, the "cold" numbers are not of much use as a
guideline for production use; note, that recent Elasticsearch versions come
with a Warmer API [1](http://www.elasticsearch.org/guide/reference/api/admin-indices-warmers.html).
Second, just send the same request repeatedly, and observe if the `took`
time and the response time is decreasing and how much. Observe
Elasticsearch with a tool such as Paramedic or BigDesk to visually check
the amount of memory needed, CPU, etc.
Third, as Otis hints, Elasticsearch by default splits your index into 5
shards (in effect, separate Lucene indices). It may be a contributing
factor, try to create the index with one shard only and no replicas:
```
curl -X PUT localhost:9200/my-index/_settings -d '{ "index" :
```
{"number\_of\_shards": 1, "number\_of\_replicas": 0} }'
Last, Elasticsearch can log slow queries [2](http://www.elasticsearch.org/guide/reference/index-modules/slowlog.html), when you start testing more
complex queries, it may be useful for you to see the `took` time for each
query.
Karel
--
---
### Author:  [@system](https://discuss.elastic.co/u/system)
#### Post date: [July 6, 2017, 3:00am UTC](https://discuss.elastic.co/t/slow-elasticsearch-queries-and-huge-load/9987/5 "2017-07-06T03:00:23Z")