# Enhancing perf for my cluster

**URL:** <https://discuss.elastic.co/t/enhancing-perf-for-my-cluster/19318>\
**Category:** Elasticsearch\
**Created:** [August 18, 2014, 10:29am UTC](https://discuss.elastic.co/t/enhancing-perf-for-my-cluster/19318 "2014-08-18T10:29:10Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![pbocto](https://avatars.discourse-cdn.com/v4/letter/p/4bbf92/32.png) [@pbocto](https://discuss.elastic.co/u/pbocto)\
**Post date:** [August 18, 2014, 10:29am UTC](https://discuss.elastic.co/t/enhancing-perf-for-my-cluster/19318/1 "2014-08-18T10:29:10Z")

</div>

Hi everyone !

I'm currently working on a tool with _ES and Twitter Streaming API_, in  
which I try to find interesting profiles on Twitter, based on what they  
tweet, RT and which of their interactions are shared/RT.

Anyway, I use ES to index and search among tweets. To do that, I get  
Twitter stream data and put in a _single index users & tweets (2 types)_,  
linked by the user id via un parent-child relation. Actually, I thought of  
my indexing a lot and it is the best way to do it.

- I need to update very often users (because i score them and because they  
update their profile quite often), so get the user nested in the tweet is  
not an option (too many replicas)
- I could put user's tweets directly in the user object but I would have  
huge objects and I don't really want that.

I work on a SoYouStart Server, 4c/4t 3.2GHz, 32Go RAM, 4To HDD.

My settings for the index are :

settings = {

> "index" : {
> 
> ```
> "number_of_replicas" : 0,
> 
> "refresh_interval" : '10s',
> 
> "routing.allocation.disable_allocation": False
> 
> },
> 
> ```
> 
> "analysis": {
> 
> ```
> "analyzer": {
> 
> "snowFrench":{
> 
> "type": "snowball",
> 
> "language": "French"
> 
> },
> 
> "snowEnglish":{
> 
> "type": "snowball",
> 
> "language": "English"
> 
> },
> 
> "snowGerman":{
> 
> "type": "snowball",
> 
> "language": "German"
> 
> },
> 
> "snowRussian":{
> 
> "type": "snowball",
> 
> "language": "Russian"
> 
> },
> 
> "snowSpanish":{
> 
> "type": "snowball",
> 
> "language": "Spanish"
> 
> },
> 
> "snowJapanese":{
> 
> "type": "snowball",
> 
> "language": "Japanese"
> 
> },
> 
> "edgeNGramAnalyzer":{
> 
> "tokenizer": "myEdgeNGram"
> 
> },
> 
> "name_analyzer": {
> 
> ```
> 
> "tokenizer": "whitespace",
> 
> "type": "custom",
> 
> "filter": ["lowercase", "multi\_words", "name\_filter"]
> 
> },
> 
> ```
> "city_analyzer" : {
> 
> "type" : "snowball",
> 
> "language" : "English"
> 
> }
> 
> },
> 
> "tokenizer" : {
> 
> "myEdgeNGram" : {
> 
> "type" : "edgeNGram",
> 
> "min_gram" : 2,
> 
> "max_gram" : 5
> 
> },
> 
> "name_tokenizer": {
> 
> ```
> 
> "type": "edgeNGram",
> 
> "max\_gram": 100,
> 
> "min\_gram": 4
> 
> }
> 
> ```
> },
> 
> "filter": {
> 
> ```
> 
> "multi\_words": {
> 
> "type": "shingle",
> 
> "min\_shingle\_size": 2,
> 
> "max\_shingle\_size": 10
> 
> },
> 
> "name\_filter": {
> 
> "type": "edgeNGram",
> 
> "max\_gram": 100,
> 
> "min\_gram": 4
> 
> }
> 
> }
> 
> ```
> }
> 
> ```
> 
> }

And my mappings are :

> tweet\_mapping = {
> 
> "\_all" : {  
> "enabled" : False  
> },  
> "\_ttl" : {  
> "enabled" : True,  
> "default" : "400d"  
> },  
> "\_parent" : {  
> "type" : 'user'  
> },  
> "properties": {  
> "textfr": {  
> 'type': 'string',  
> '\_analyzer': 'snowFrench',  
> 'copy\_to': 'text'  
> },  
> "texten": {  
> 'type': 'string',  
> '\_analyzer': 'snowEnglish',  
> 'copy\_to': 'text'  
> },  
> "textde": {  
> 'type': 'string',  
> '\_analyzer': 'snowGerman',  
> 'copy\_to': 'text'  
> },  
> "textja": {  
> 'type': 'string',  
> '\_analyzer': 'snowJapanese',  
> 'copy\_to': 'text'  
> },  
> "textru": {  
> 'type': 'string',  
> '\_analyzer': 'snowRussian',  
> 'copy\_to': 'text'  
> },  
> "textes": {  
> 'type': 'string',  
> '\_analyzer': 'snowSpanish',  
> 'copy\_to': 'text'  
> },  
> "text": {  
> 'type': 'string',  
> 'null\_value': '',  
> 'index': 'analyzed',  
> 'store': 'yes'  
> },  
> "entities": {  
> 'type': 'object',  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'properties': {  
> "hashtags": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> "\_analyzer": "edgeNGramAnalyzer"  
> },  
> "mentions": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'long',  
> 'precision\_step': 64  
> }  
> }  
> },  
> "lang": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string'  
> },  
> "created\_at": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'date',  
> 'format' : 'dd-MM-YYYY HH:mm:ss'  
> }  
> }  
> }  
> user\_mapping = {  
> "\_all" : {  
> "enabled" : False  
> },  
> "\_ttl" : {  
> "enabled" : True,  
> "default" : "600d"  
> },  
> "properties": {  
> "lang": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string'  
> },  
> "name": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> "\_analyzer": "edgeNGramAnalyzer"  
> },  
> "screen\_name": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> "\_analyzer": "edgeNGramAnalyzer"  
> },  
> "descfr": {  
> 'type': 'string',  
> '\_analyzer': 'snowFrench',  
> 'copy\_to': 'description'  
> },  
> "descen": {  
> 'type': 'string',  
> '\_analyzer': 'snowEnglish',  
> 'copy\_to': 'description'  
> },  
> "descde": {  
> 'type': 'string',  
> '\_analyzer': 'snowGerman',  
> 'copy\_to': 'description'  
> },  
> "descja": {  
> 'type': 'string',  
> '\_analyzer': 'snowJapanese',  
> 'copy\_to': 'description'  
> },  
> "descru": {  
> 'type': 'string',  
> '\_analyzer': 'snowRussian',  
> 'copy\_to': 'description'  
> },  
> "desces": {  
> 'type': 'string',  
> '\_analyzer': 'snowSpanish',  
> 'copy\_to': 'description'  
> },  
> "description": {  
> 'type': 'string',  
> 'null\_value': '',  
> 'index': 'analyzed',  
> 'store': 'yes'  
> },  
> "created\_at": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'date',  
> 'format' : 'dd-MM-YYYY HH:mm:ss'  
> },  
> "profile\_image\_url": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string'  
> },  
> "analysis": {  
> 'type': 'object',  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'properties': {  
> "hashtags": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object'  
> },  
> "relations": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object'  
> },  
> "score": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object'  
> }  
> }  
> },  
> "location" : {  
> 'type': 'object',  
> 'index': 'analyzed',  
> 'store': 'yes',  
> "properties" : {  
> "search\_field": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'analyzer': 'city\_analyzer',  
> 'null\_value': ''  
> },  
> "name": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'null\_value': ''  
> },  
> "city": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object',  
> 'properties': {  
> 'name': {  
> 'boost': 3.0,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> },  
> 'full\_name': {  
> 'boost': 3.0,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': ['location.search\_field', 'location.name']  
> },  
> 'alternate\_names': {  
> 'boost': 2.0,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> }  
> }  
> },  
> "admin2": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object',  
> 'properties': {  
> 'name': {  
> 'boost': 1.5,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> },  
> 'full\_name': {  
> 'boost': 1.5,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': ['location.search\_field', 'location.name']  
> }  
> }  
> },  
> "admin1": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object',  
> 'properties': {  
> 'name': {  
> 'boost': 1.2,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> },  
> 'full\_name': {  
> 'boost': 1.2,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': ['location.search\_field', 'location.name']  
> }  
> }  
> },  
> "country": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object',  
> 'properties': {  
> 'name': {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': ['location.search\_field', 'location.name']  
> },  
> 'fips': {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> },  
> 'capital': {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string'  
> }  
> }  
> },  
> "location": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'geo\_point'  
> },  
> "population": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'long'  
> },  
> 'capital': {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'boolean'  
> }  
> }  
> }  
> }  
> }

Currently my cluster contains 60M docs (40M tweets, 20M users). I have only  
one node, no replicas, because if I create another node, no data will go in  
there... 😕

When I index user, I localize them with the string they put in their  
profile (actually geoloc in tweet is present 5% of the time so it's not  
very interesting). So I indexed (in another index) the biggest cities in  
the world and I assign a city for each user.

Something other you should know : _I use Python and PyES lib to work_.

_SO. Let's talk about the problem :_

My goal is to sort users by pertinence in their tweets. To do that, I  
analyze the user's profile, timeline and the tweets in which they are  
mentioned (RT, messages).  
So what happens in my script ?

I have a REST API based on Django REST Framework and a frontend with  
AngularJS

1/ I type a keyword (for ex : java, python, nodejs) and a location (not  
required, for ex: paris)  
2/ I use count API to find every user that speaks about "java" in "paris"  
3/ Then I get the 20 first results of this query.  
4/ I do a multi\_search query to get users' timeline and mentions  
5/ I score them  
6/ When they're scored, AngularJS displays the sorted results and send  
another request to the API to score the page 2, until there's no more page  
available.

The queries I do are :  
1/ To get users :

> {
> 
> ```
> 'query': {
> 
> 'bool': {
> 
> 'should': [
> 
> {
> 
> 'multi_match': {
> 
> 'use_dis_max': True,
> 
> 'query': 'java',
> 
> 'type': 'boolean',
> 
> 'operator': 'or',
> 
> 'fields': [
> 
> 'name',
> 
> 'screen_name',
> 
> 'description'
> 
> ]
> 
> }
> 
> },
> 
> {
> 
> 'has_child': {
> 
> 'query': {
> 
> 'match': {
> 
> 'text': {
> 
> 'operator': 'or',
> 
> 'query': 'java',
> 
> 'type': 'boolean'
> 
> }
> 
> }
> 
> },
> 
> 'type': 'tweet'
> 
> }
> 
> }
> 
> ],
> 
> 'minimum_number_should_match': 1,
> 
> 'must': [
> 
> {
> 
> 'function_score': {
> 
> 'query': {
> 
> 'match': {
> 
> 'location.search_field': {
> 
> 'operator': 'or',
> 
> 'query': 'paris',
> 
> 'type': 'boolean'
> 
> }
> 
> }
> 
> },
> 
> 'functions': [
> 
> {
> 
> 'script_score': {
> 
> 'script': "_score * 
> 
> ```
> 
> > (doc['capital'].value == 'T' ? 2 : 1)"
> 
> ```
> }
> 
> },
> 
> {
> 
> 'script_score': {
> 
> 'script': "_score * 
> 
> ```
> 
> > doc['search\_field'].values.size()"
> 
> ```
> }
> 
> }
> 
> ]
> 
> }
> 
> }
> 
> ]
> 
> }
> 
> },
> 
> 'from': 20,
> 
> 'size': 20
> 
> ```
> 
> }

2/ To get timelines and mentions:

{

> ```
> 'query': {
> 'match': {
> 'entities.mentions': {
> 'operator': 'or',
> 'query': 'userID',
> 'type': 'boolean'
> }
> }
> },
> '_source': True
> 
> ```
> 
> }

and

{

> ```
> 'query': {
> 
> 'has_parent': {
> 
> 'query': {
> 
> 'match': {
> 
> 'id': {
> 
> 'operator': 'or',
> 
> 'query': 'userID',
> 
> 'type': 'boolean'
> 
> }
> 
> }
> 
> },
> 
> 'type': 'user'
> 
> }
> 
> },
> 
> '_source': True
> 
> ```
> 
> }

BUT. Scoring one page can take from a few seconds to several minutes !!! I  
don't think it's normal, right ? I profiled my script and this is it : ES  
requests take toooooo long. Usually it's something like 10-20sec (and it's  
still too long), but sometimes it can take up to 90sec...

I studied quite well ES, I think I understand many things but here, I don't  
know what can I do to change that.... Any ideas ? Thanks !

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---

<div class="post-metadata">

**Author:** ![pbocto](https://avatars.discourse-cdn.com/v4/letter/p/4bbf92/32.png) [@pbocto](https://discuss.elastic.co/u/pbocto)\
**Post date:** [August 18, 2014, 4:41pm UTC](https://discuss.elastic.co/t/enhancing-perf-for-my-cluster/19318/2 "2014-08-18T16:41:37Z")

</div>

Hey guys,

Finally i changed all my queries to constantscorequeries. It's way better,  
but still, certain pages take a lot of time running... I don't understand  
why, and i don't have anything in my ES logs...

Now the average time for search 20 users and their mentions/timeline +  
scoring them is about 4s (and almost 4s for the search).  
But when it takes time, it's still 60s for 1 page !!!

I tried reading the explain data i can't get after the query but there's no  
response time. How can I find a way to understand why certain queries take  
so much time ?

Thanks !

Le lundi 18 août 2014 12:29:10 UTC+2, Pierrick Boutruche a écrit :

> Hi everyone !
> 
> I'm currently working on a tool with _ES and Twitter Streaming API_, in  
> which I try to find interesting profiles on Twitter, based on what they  
> tweet, RT and which of their interactions are shared/RT.
> 
> Anyway, I use ES to index and search among tweets. To do that, I get  
> Twitter stream data and put in a _single index users & tweets (2 types)_,  
> linked by the user id via un parent-child relation. Actually, I thought of  
> my indexing a lot and it is the best way to do it.
> 
> - I need to update very often users (because i score them and because they  
> update their profile quite often), so get the user nested in the tweet is  
> not an option (too many replicas)
> - I could put user's tweets directly in the user object but I would have  
> huge objects and I don't really want that.
> 
> I work on a SoYouStart Server, 4c/4t 3.2GHz, 32Go RAM, 4To HDD.
> 
> My settings for the index are :
> 
> settings = {
> 
> "index" : {
> 
> ```
> "number_of_replicas" : 0,
> 
> "refresh_interval" : '10s',
> 
> "routing.allocation.disable_allocation": False
> 
> },
> 
> ```
> 
> "analysis": {
> 
> ```
> "analyzer": {
> 
> "snowFrench":{
> 
> "type": "snowball",
> 
> "language": "French"
> 
> },
> 
> "snowEnglish":{
> 
> "type": "snowball",
> 
> "language": "English"
> 
> },
> 
> "snowGerman":{
> 
> "type": "snowball",
> 
> "language": "German"
> 
> },
> 
> "snowRussian":{
> 
> "type": "snowball",
> 
> "language": "Russian"
> 
> },
> 
> "snowSpanish":{
> 
> "type": "snowball",
> 
> "language": "Spanish"
> 
> },
> 
> "snowJapanese":{
> 
> "type": "snowball",
> 
> "language": "Japanese"
> 
> },
> 
> "edgeNGramAnalyzer":{
> 
> "tokenizer": "myEdgeNGram"
> 
> },
> 
> "name_analyzer": {
> 
> ```
> 
> "tokenizer": "whitespace",
> 
> "type": "custom",
> 
> "filter": ["lowercase", "multi\_words", "name\_filter"]
> 
> },
> 
> ```
> "city_analyzer" : {
> 
> "type" : "snowball",
> 
> "language" : "English"
> 
> }
> 
> },
> 
> "tokenizer" : {
> 
> "myEdgeNGram" : {
> 
> "type" : "edgeNGram",
> 
> "min_gram" : 2,
> 
> "max_gram" : 5
> 
> },
> 
> "name_tokenizer": {
> 
> ```
> 
> "type": "edgeNGram",
> 
> "max\_gram": 100,
> 
> "min\_gram": 4
> 
> }
> 
> ```
> },
> 
> "filter": {
> 
> ```
> 
> "multi\_words": {
> 
> "type": "shingle",
> 
> "min\_shingle\_size": 2,
> 
> "max\_shingle\_size": 10
> 
> },
> 
> "name\_filter": {
> 
> "type": "edgeNGram",
> 
> "max\_gram": 100,
> 
> "min\_gram": 4
> 
> }
> 
> }
> 
> ```
> }
> 
> ```
> 
> }
> 
> And my mappings are :
> 
> tweet\_mapping = {
> 
> "\_all" : {  
> "enabled" : False  
> },  
> "\_ttl" : {  
> "enabled" : True,  
> "default" : "400d"  
> },  
> "\_parent" : {  
> "type" : 'user'  
> },  
> "properties": {  
> "textfr": {  
> 'type': 'string',  
> '\_analyzer': 'snowFrench',  
> 'copy\_to': 'text'  
> },  
> "texten": {  
> 'type': 'string',  
> '\_analyzer': 'snowEnglish',  
> 'copy\_to': 'text'  
> },  
> "textde": {  
> 'type': 'string',  
> '\_analyzer': 'snowGerman',  
> 'copy\_to': 'text'  
> },  
> "textja": {  
> 'type': 'string',  
> '\_analyzer': 'snowJapanese',  
> 'copy\_to': 'text'  
> },  
> "textru": {  
> 'type': 'string',  
> '\_analyzer': 'snowRussian',  
> 'copy\_to': 'text'  
> },  
> "textes": {  
> 'type': 'string',  
> '\_analyzer': 'snowSpanish',  
> 'copy\_to': 'text'  
> },  
> "text": {  
> 'type': 'string',  
> 'null\_value': '',  
> 'index': 'analyzed',  
> 'store': 'yes'  
> },  
> "entities": {  
> 'type': 'object',  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'properties': {  
> "hashtags": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> "\_analyzer": "edgeNGramAnalyzer"  
> },  
> "mentions": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'long',  
> 'precision\_step': 64  
> }  
> }  
> },  
> "lang": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string'  
> },  
> "created\_at": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'date',  
> 'format' : 'dd-MM-YYYY HH:mm:ss'  
> }  
> }  
> }  
> user\_mapping = {  
> "\_all" : {  
> "enabled" : False  
> },  
> "\_ttl" : {  
> "enabled" : True,  
> "default" : "600d"  
> },  
> "properties": {  
> "lang": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string'  
> },  
> "name": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> "\_analyzer": "edgeNGramAnalyzer"  
> },  
> "screen\_name": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> "\_analyzer": "edgeNGramAnalyzer"  
> },  
> "descfr": {  
> 'type': 'string',  
> '\_analyzer': 'snowFrench',  
> 'copy\_to': 'description'  
> },  
> "descen": {  
> 'type': 'string',  
> '\_analyzer': 'snowEnglish',  
> 'copy\_to': 'description'  
> },  
> "descde": {  
> 'type': 'string',  
> '\_analyzer': 'snowGerman',  
> 'copy\_to': 'description'  
> },  
> "descja": {  
> 'type': 'string',  
> '\_analyzer': 'snowJapanese',  
> 'copy\_to': 'description'  
> },  
> "descru": {  
> 'type': 'string',  
> '\_analyzer': 'snowRussian',  
> 'copy\_to': 'description'  
> },  
> "desces": {  
> 'type': 'string',  
> '\_analyzer': 'snowSpanish',  
> 'copy\_to': 'description'  
> },  
> "description": {  
> 'type': 'string',  
> 'null\_value': '',  
> 'index': 'analyzed',  
> 'store': 'yes'  
> },  
> "created\_at": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'date',  
> 'format' : 'dd-MM-YYYY HH:mm:ss'  
> },  
> "profile\_image\_url": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string'  
> },  
> "analysis": {  
> 'type': 'object',  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'properties': {  
> "hashtags": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object'  
> },  
> "relations": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object'  
> },  
> "score": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object'  
> }  
> }  
> },  
> "location" : {  
> 'type': 'object',  
> 'index': 'analyzed',  
> 'store': 'yes',  
> "properties" : {  
> "search\_field": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'analyzer': 'city\_analyzer',  
> 'null\_value': ''  
> },  
> "name": {  
> 'index': 'not\_analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'null\_value': ''  
> },  
> "city": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object',  
> 'properties': {  
> 'name': {  
> 'boost': 3.0,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> },  
> 'full\_name': {  
> 'boost': 3.0,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': ['location.search\_field', 'location.name']  
> },  
> 'alternate\_names': {  
> 'boost': 2.0,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> }  
> }  
> },  
> "admin2": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object',  
> 'properties': {  
> 'name': {  
> 'boost': 1.5,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': 'location.search\_field'  
> },  
> 'full\_name': {  
> 'boost': 1.5,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',  
> 'copy\_to': ['location.search\_field', 'location.name']  
> }  
> }  
> },  
> "admin1": {  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'object',  
> 'properties': {  
> 'name': {  
> 'boost': 1.2,  
> 'index': 'analyzed',  
> 'store': 'yes',  
> 'type': 'string',
> 
> ...

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---

<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, 1:07am UTC](https://discuss.elastic.co/t/enhancing-perf-for-my-cluster/19318/3 "2017-07-06T01:07:54Z")

</div>