# How to improve AutoComplete performance? **URL:** \ **Category:** Elasticsearch\ **Created:** [December 10, 2012, 3:23am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009 "2012-12-10T03:23:52Z")\ **Posts on this page:** 14\ **Page:** 1
**Author:** ![zkidkid](https://avatars.discourse-cdn.com/v4/letter/z/fbc32d/32.png) [@zkidkid](https://discuss.elastic.co/u/zkidkid)\ **Post date:** [December 10, 2012, 3:23am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/1 "2012-12-10T03:23:52Z")
Hi, Currently I am making a autocomplete with ElasticSearch. My Config: index: analysis: filter: my\_gram\_filter: type: edgeNGram side: front min\_gram: 1 max\_gram: 10 tokenizer: my\_gram: type: edgeNGram side: front min\_gram: 2 max\_gram: 20 analyzer: default: tokenizer: standard filter: [asciifolding,lowercase] auto: type: custom tokenizer: my\_gram filter: [asciifolding,lowercase] auto2: type: custom tokenizer: standard filter: [standard,lowercase,asciifolding,my\_gram\_filter] Here is my mapping: { "song\_name":{ "properties" : { "id" : {"type": string}, "name": {"type": string, "index\_analyzer": auto2, "search\_analyzer": default} , "data": {"type": string, "index": not\_analyzed} } } } My server: Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz I have 5 index, with 5 milions records. I stress test it around 6k Request/Second. And the response would take from 2s-6s. Is anything there for me to increase the performance ? P/S: I have try to setup caching: indices.cache.filter.size: 3072mb index.cache.filter.max\_size: 1000000 index.cache.filter.expire: 5m index.cache.filter.type: resident index.cache.field.max\_size: 1000000 index.cache.field.expire: 5m And I check the cache status using bigdesk plugin/ I found that: Filter Size: 16mb Field Size: 0 Do the caching work right ? Thanks In Advance. -- ---
**Author:** ![mvg](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mvg/32/98890_2.png) [@mvg](https://discuss.elastic.co/u/mvg)\ **Post date:** [December 10, 2012, 11:40am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/2 "2012-12-10T11:40:31Z")
Hi, Can you share the actual query, that you use for the autocomplete? The field cache is used for sorting by field, faceting and in scripts. If these features aren't used then the cache size is 0. The filter cache is used for only filters, which can be specified in the search dsl. Only if your auto complete search request contains filters, then you can benefit from filter cache. Why did you actually set the `expire` and `max_size` option on both caches? A filter cache that has entries is good, because that will prevent unneeded disk io. The filter cache can manage itself pretty good. Also ES has a very good default `max_size` for the filter cache, which is 20% of the specified maximum heap size. Also how much memory did you allocate to ES via the ES\_HEAP\_SIZE environment variable? Martijn On 10 December 2012 04:23, kidkid [zkidkid@gmail.com](mailto:zkidkid@gmail.com) wrote: > Hi, > > Currently I am making a autocomplete with Elasticsearch. > > My Config: > > index: > > analysis: > filter: > my\_gram\_filter: > type: edgeNGram > side: front > min\_gram: 1 > max\_gram: 10 > tokenizer: > my\_gram: > type: edgeNGram > side: front > min\_gram: 2 > max\_gram: 20 > analyzer: > default: > tokenizer: standard > filter: [asciifolding,lowercase] > auto: > type: custom > tokenizer: my\_gram > filter: [asciifolding,lowercase] > auto2: > type: custom > tokenizer: standard > filter: [standard,lowercase,asciifolding,my\_gram\_filter] > > Here is my mapping: > > { > "song\_name":{ > "properties" : { > "id" : {"type": string}, > "name": {"type": string, "index\_analyzer": auto2, "search\_analyzer": > default} , > "data": {"type": string, "index": not\_analyzed} > } > } > } > > My server: > > Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz > Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz > Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz > > I have 5 index, with 5 milions records. > > I stress test it around 6k Request/Second. > And the response would take from 2s-6s. > > Is anything there for me to increase the performance ? > > P/S: I have try to setup caching: > > indices.cache.filter.size: 3072mb > index.cache.filter.max\_size: 1000000 > index.cache.filter.expire: 5m > index.cache.filter.type: resident > > index.cache.field.max\_size: 1000000 > index.cache.field.expire: 5m > > And I check the cache status using bigdesk plugin/ > I found that: > > Filter Size: 16mb > Field Size: 0 > > Do the caching work right ? > > Thanks In Advance. > > -- -- Met vriendelijke groet, Martijn van Groningen -- ---
**Author:** ![zkidkid](https://avatars.discourse-cdn.com/v4/letter/z/fbc32d/32.png) [@zkidkid](https://discuss.elastic.co/u/zkidkid)\ **Post date:** [December 10, 2012, 11:53am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/3 "2012-12-10T11:53:57Z")
Hi Martijn, Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz 30Gb Ram has allocated by setting ES\_HEAP\_SIZE. My Query is text query and phrase query. TextQueryBuilder tq = QueryBuilders.textPhraseQuery(field, query); tq.operator(TextQueryBuilder.Operator.AND); tq.analyzer("default"); TextQueryBuilder tq = QueryBuilders.textQuery(field, query); tq.operator(TextQueryBuilder.Operator.AND); tq.analyzer("default"); the data is random around 4 words, each word has about 3-6 characters. I have checked via bigdesk plugin and found that ES just use about 30% of allocated memory. do you have any way to increase my suggest performance ? I have take a look on suggest plugin but It's not help much. Regards. On Monday, December 10, 2012 6:40:31 PM UTC+7, Martijn v Groningen wrote: > Hi, > > Can you share the actual query, that you use for the autocomplete? > > The field cache is used for sorting by field, faceting and in scripts. > If these features aren't used then the cache size is 0. > The filter cache is used for only filters, which can be specified in > the search dsl. Only if your auto complete search request contains > filters, then you can benefit from filter cache. > > Why did you actually set the `expire` and `max_size` option on both > caches? A filter cache that has entries is good, because that will > prevent unneeded disk io. The filter cache can manage itself pretty > good. Also ES has a very good default `max_size` for the filter cache, > which is 20% of the specified maximum heap size. Also how much memory > did you allocate to ES via the ES\_HEAP\_SIZE environment variable? > > Martijn > > On 10 December 2012 04:23, kidkid \<[zki...@gmail.com](mailto:zki...@gmail.com) \\> wrote: > > > Hi, > > > > Currently I am making a autocomplete with Elasticsearch. > > > > My Config: > > > > index: > > > > analysis: > > filter: > > my\_gram\_filter: > > type: edgeNGram > > side: front > > min\_gram: 1 > > max\_gram: 10 > > tokenizer: > > my\_gram: > > type: edgeNGram > > side: front > > min\_gram: 2 > > max\_gram: 20 > > analyzer: > > default: > > tokenizer: standard > > filter: [asciifolding,lowercase] > > auto: > > type: custom > > tokenizer: my\_gram > > filter: [asciifolding,lowercase] > > auto2: > > type: custom > > tokenizer: standard > > filter: [standard,lowercase,asciifolding,my\_gram\_filter] > > > > Here is my mapping: > > > > { > > "song\_name":{ > > "properties" : { > > "id" : {"type": string}, > > "name": {"type": string, "index\_analyzer": auto2, "search\_analyzer": > > default} , > > "data": {"type": string, "index": not\_analyzed} > > } > > } > > } > > > > My server: > > > > Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > 2.40GHz > > Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > 2.40GHz > > Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > 2.40GHz > > > > I have 5 index, with 5 milions records. > > > > I stress test it around 6k Request/Second. > > And the response would take from 2s-6s. > > > > Is anything there for me to increase the performance ? > > > > P/S: I have try to setup caching: > > > > indices.cache.filter.size: 3072mb > > index.cache.filter.max\_size: 1000000 > > index.cache.filter.expire: 5m > > index.cache.filter.type: resident > > > > index.cache.field.max\_size: 1000000 > > index.cache.field.expire: 5m > > > > And I check the cache status using bigdesk plugin/ > > I found that: > > > > Filter Size: 16mb > > Field Size: 0 > > > > Do the caching work right ? > > > > Thanks In Advance. > > > > -- > > -- > Met vriendelijke groet, > > Martijn van Groningen -- ---
**Author:** ![mvg](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mvg/32/98890_2.png) [@mvg](https://discuss.elastic.co/u/mvg)\ **Post date:** [December 10, 2012, 12:16pm UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/4 "2012-12-10T12:16:10Z")
Hi kidkid, Since you're using queries for auto suggest the filter cache won't help you improve your performance. I see that you allocated all your memory to ES, this isn't recommended and actually bad for performance. ES utilizes the OS file system cache a lot. By allocating a lot of memory to ES's heap space, the file system cache doesn't have much memory to do its job. A healthy memory balance for ES is to around 50% of the memory ES' heap space and leave the other 50% to the OS. Queries in ES rely a lot on the filesystem cache. Since you only utilize ~30% of the heap space I would allocate 15GB of memory to ES' heap space on server1 and around 12GB of memory to ES' heap space on server2 and server3. I think this will improve your performance. In your code I see the variable `field` being used. What actual field is this variable referring to? Martijn On 10 December 2012 12:53, kidkid [zkidkid@gmail.com](mailto:zkidkid@gmail.com) wrote: > Hi Martijn, > > Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz > Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz > Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ 2.40GHz > > 30Gb Ram has allocated by setting ES\_HEAP\_SIZE. > > My Query is text query and phrase query. > > TextQueryBuilder tq = QueryBuilders.textPhraseQuery(field, query); > tq.operator(TextQueryBuilder.Operator.AND); > tq.analyzer("default"); > > TextQueryBuilder tq = QueryBuilders.textQuery(field, query); > tq.operator(TextQueryBuilder.Operator.AND); > tq.analyzer("default"); > > the data is random around 4 words, each word has about 3-6 characters. > > I have checked via bigdesk plugin and found that ES just use about 30% of > allocated memory. > > do you have any way to increase my suggest performance ? > > I have take a look on suggest plugin but It's not help much. > > Regards. > > On Monday, December 10, 2012 6:40:31 PM UTC+7, Martijn v Groningen wrote: > > > Hi, > > > > Can you share the actual query, that you use for the autocomplete? > > > > The field cache is used for sorting by field, faceting and in scripts. > > If these features aren't used then the cache size is 0. > > The filter cache is used for only filters, which can be specified in > > the search dsl. Only if your auto complete search request contains > > filters, then you can benefit from filter cache. > > > > Why did you actually set the `expire` and `max_size` option on both > > caches? A filter cache that has entries is good, because that will > > prevent unneeded disk io. The filter cache can manage itself pretty > > good. Also ES has a very good default `max_size` for the filter cache, > > which is 20% of the specified maximum heap size. Also how much memory > > did you allocate to ES via the ES\_HEAP\_SIZE environment variable? > > > > Martijn > > > > On 10 December 2012 04:23, kidkid [zki...@gmail.com](mailto:zki...@gmail.com) wrote: > > > > > Hi, > > > > > > Currently I am making a autocomplete with Elasticsearch. > > > > > > My Config: > > > > > > index: > > > > > > analysis: > > > filter: > > > my\_gram\_filter: > > > type: edgeNGram > > > side: front > > > min\_gram: 1 > > > max\_gram: 10 > > > tokenizer: > > > my\_gram: > > > type: edgeNGram > > > side: front > > > min\_gram: 2 > > > max\_gram: 20 > > > analyzer: > > > default: > > > tokenizer: standard > > > filter: [asciifolding,lowercase] > > > auto: > > > type: custom > > > tokenizer: my\_gram > > > filter: [asciifolding,lowercase] > > > auto2: > > > type: custom > > > tokenizer: standard > > > filter: [standard,lowercase,asciifolding,my\_gram\_filter] > > > > > > Here is my mapping: > > > > > > { > > > "song\_name":{ > > > "properties" : { > > > "id" : {"type": string}, > > > "name": {"type": string, "index\_analyzer": auto2, "search\_analyzer": > > > default} , > > > "data": {"type": string, "index": not\_analyzed} > > > } > > > } > > > } > > > > > > My server: > > > > > > Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > > 2.40GHz > > > Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > > 2.40GHz > > > Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > > 2.40GHz > > > > > > I have 5 index, with 5 milions records. > > > > > > I stress test it around 6k Request/Second. > > > And the response would take from 2s-6s. > > > > > > Is anything there for me to increase the performance ? > > > > > > P/S: I have try to setup caching: > > > > > > indices.cache.filter.size: 3072mb > > > index.cache.filter.max\_size: 1000000 > > > index.cache.filter.expire: 5m > > > index.cache.filter.type: resident > > > > > > index.cache.field.max\_size: 1000000 > > > index.cache.field.expire: 5m > > > > > > And I check the cache status using bigdesk plugin/ > > > I found that: > > > > > > Filter Size: 16mb > > > Field Size: 0 > > > > > > Do the caching work right ? > > > > > > Thanks In Advance. > > > > > > -- > > > > -- > > Met vriendelijke groet, > > > > Martijn van Groningen -- Met vriendelijke groet, Martijn van Groningen -- ---
**Author:** ![zkidkid](https://avatars.discourse-cdn.com/v4/letter/z/fbc32d/32.png) [@zkidkid](https://discuss.elastic.co/u/zkidkid)\ **Post date:** [December 10, 2012, 4:47pm UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/5 "2012-12-10T16:47:13Z")
Hi, 30Gb ram is memory I allocate for the ES. The server is 40Gb ram. It's a server for load test purpose only. field is "name" field which you could see in my mappings. Is anyway to caching or anything to improve the performance. Regards. On Monday, December 10, 2012 7:16:10 PM UTC+7, Martijn v Groningen wrote: > Hi kidkid, > > Since you're using queries for auto suggest the filter cache won't > help you improve your performance. > > I see that you allocated all your memory to ES, this isn't recommended > and actually bad for performance. > ES utilizes the OS file system cache a lot. By allocating a lot of > memory to ES's heap space, the file system > cache doesn't have much memory to do its job. A healthy memory balance > for ES is to around 50% of the memory > ES' heap space and leave the other 50% to the OS. Queries in ES rely a > lot on the filesystem cache. > > Since you only utilize ~30% of the heap space I would allocate 15GB of > memory to ES' heap space on server1 and around > 12GB of memory to ES' heap space on server2 and server3. I think this > will improve your performance. > > In your code I see the variable `field` being used. What actual field > is this variable referring to? > > Martijn > > On 10 December 2012 12:53, kidkid \<[zki...@gmail.com](mailto:zki...@gmail.com) \\> wrote: > > > Hi Martijn, > > > > Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > 2.40GHz > > Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > 2.40GHz > > Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > 2.40GHz > > > > 30Gb Ram has allocated by setting ES\_HEAP\_SIZE. > > > > My Query is text query and phrase query. > > > > TextQueryBuilder tq = QueryBuilders.textPhraseQuery(field, query); > > tq.operator(TextQueryBuilder.Operator.AND); > > tq.analyzer("default"); > > > > TextQueryBuilder tq = QueryBuilders.textQuery(field, query); > > tq.operator(TextQueryBuilder.Operator.AND); > > tq.analyzer("default"); > > > > the data is random around 4 words, each word has about 3-6 characters. > > > > I have checked via bigdesk plugin and found that ES just use about 30% > > of > > allocated memory. > > > > do you have any way to increase my suggest performance ? > > > > I have take a look on suggest plugin but It's not help much. > > > > Regards. > > > > On Monday, December 10, 2012 6:40:31 PM UTC+7, Martijn v Groningen > > wrote: > > > > > Hi, > > > > > > Can you share the actual query, that you use for the autocomplete? > > > > > > The field cache is used for sorting by field, faceting and in scripts. > > > If these features aren't used then the cache size is 0. > > > The filter cache is used for only filters, which can be specified in > > > the search dsl. Only if your auto complete search request contains > > > filters, then you can benefit from filter cache. > > > > > > Why did you actually set the `expire` and `max_size` option on both > > > caches? A filter cache that has entries is good, because that will > > > prevent unneeded disk io. The filter cache can manage itself pretty > > > good. Also ES has a very good default `max_size` for the filter cache, > > > which is 20% of the specified maximum heap size. Also how much memory > > > did you allocate to ES via the ES\_HEAP\_SIZE environment variable? > > > > > > Martijn > > > > > > On 10 December 2012 04:23, kidkid [zki...@gmail.com](mailto:zki...@gmail.com) wrote: > > > > > > > Hi, > > > > > > > > Currently I am making a autocomplete with Elasticsearch. > > > > > > > > My Config: > > > > > > > > index: > > > > > > > > analysis: > > > > filter: > > > > my\_gram\_filter: > > > > type: edgeNGram > > > > side: front > > > > min\_gram: 1 > > > > max\_gram: 10 > > > > tokenizer: > > > > my\_gram: > > > > type: edgeNGram > > > > side: front > > > > min\_gram: 2 > > > > max\_gram: 20 > > > > analyzer: > > > > default: > > > > tokenizer: standard > > > > filter: [asciifolding,lowercase] > > > > auto: > > > > type: custom > > > > tokenizer: my\_gram > > > > filter: [asciifolding,lowercase] > > > > auto2: > > > > type: custom > > > > tokenizer: standard > > > > filter: [standard,lowercase,asciifolding,my\_gram\_filter] > > > > > > > > Here is my mapping: > > > > > > > > { > > > > "song\_name":{ > > > > "properties" : { > > > > "id" : {"type": string}, > > > > "name": {"type": string, "index\_analyzer": auto2, "search\_analyzer": > > > > default} , > > > > "data": {"type": string, "index": not\_analyzed} > > > > } > > > > } > > > > } > > > > > > > > My server: > > > > > > > > Server 1, 30Gb Ram, 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > > > 2.40GHz > > > > Server 2: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > > > 2.40GHz > > > > Server 3: 20Gb Ram 16 Core, Intel(R) Xeon(R) CPU E5620 @ > > > > 2.40GHz > > > > > > > > I have 5 index, with 5 milions records. > > > > > > > > I stress test it around 6k Request/Second. > > > > And the response would take from 2s-6s. > > > > > > > > Is anything there for me to increase the performance ? > > > > > > > > P/S: I have try to setup caching: > > > > > > > > indices.cache.filter.size: 3072mb > > > > index.cache.filter.max\_size: 1000000 > > > > index.cache.filter.expire: 5m > > > > index.cache.filter.type: resident > > > > > > > > index.cache.field.max\_size: 1000000 > > > > index.cache.field.expire: 5m > > > > > > > > And I check the cache status using bigdesk plugin/ > > > > I found that: > > > > > > > > Filter Size: 16mb > > > > Field Size: 0 > > > > > > > > Do the caching work right ? > > > > > > > > Thanks In Advance. > > > > > > > > -- > > > > > > -- > > > Met vriendelijke groet, > > > > > > Martijn van Groningen > > -- > Met vriendelijke groet, > > Martijn van Groningen -- ---
**Author:** ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)\ **Post date:** [December 10, 2012, 5:37pm UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/6 "2012-12-10T17:37:26Z")
Hi, just a question, why are you using min\_gram:1 ? Best regards, Jörg -- ---
**Author:** ![mvg](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mvg/32/98890_2.png) [@mvg](https://discuss.elastic.co/u/mvg)\ **Post date:** [December 10, 2012, 5:52pm UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/7 "2012-12-10T17:52:42Z")
> Hi, 30Gb ram is memory I allocate for the ES. The server is 40Gb ram. > It's a server for load test purpose only. > field is "name" field which you could see in my mappings. > Ok, if you lower the ES\_HEAP\_SIZE to 20GB, then this will improve your > queries performance. The filter cache won't help you here, since > you're using filters in your query (the code that you shared). -- ---
**Author:** ![zkidkid](https://avatars.discourse-cdn.com/v4/letter/z/fbc32d/32.png) [@zkidkid](https://discuss.elastic.co/u/zkidkid)\ **Post date:** [December 11, 2012, 2:23am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/8 "2012-12-11T02:23:55Z")
Ok I will try. But I notice that the server is work fine with 10Gb Ram Left. 😑 Is there other way to improve performance ? @Jorg Prante: Yeah, min\_gram to 1 so that I could suggest from 1 character. On Tuesday, December 11, 2012 12:52:42 AM UTC+7, Martijn v Groningen wrote: > > Hi, 30Gb ram is memory I allocate for the ES. The server is 40Gb ram. > > It's a server for load test purpose only. > > field is "name" field which you could see in my mappings. > > Ok, if you lower the ES\_HEAP\_SIZE to 20GB, then this will improve your > > queries performance. The filter cache won't help you here, since > > you're using filters in your query (the code that you shared). -- ---
**Author:** ![zkidkid](https://avatars.discourse-cdn.com/v4/letter/z/fbc32d/32.png) [@zkidkid](https://discuss.elastic.co/u/zkidkid)\ **Post date:** [December 11, 2012, 11:30am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/9 "2012-12-11T11:30:51Z")
Hi, I have set up the server and I allocate ES for 50% of ram. The result is not improve much. Currently with single request, 1-10 req/sec, I get the suggest response at 5-10(ms) All I want that I could get result at 10-50(ms) when 1-2k req/sec. So what should I do ? More ram or more server or ??? Currently I have 5 index, each index has 1M record and I suggest in 5 indexes. Should I tried for 1 index only ? I see the document for store in memory but If the server down -\> I need to reindex it again. Thanks. -- ---
**Author:** ![mvg](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mvg/32/98890_2.png) [@mvg](https://discuss.elastic.co/u/mvg)\ **Post date:** [December 11, 2012, 12:18pm UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/10 "2012-12-11T12:18:45Z")
How many nodes are using for your tests right now? Does each index has 5 shards? The easy way to improve your response times is to add more nodes. Adding more RAM would give your filesystem cache more space. This allows the OS the cache more index files. What type of disk are you using? Using SSD can improve your response times by many times. Martijn On 11 December 2012 12:30, kidkid [zkidkid@gmail.com](mailto:zkidkid@gmail.com) wrote: > Hi, > > I have set up the server and I allocate ES for 50% of ram. > The result is not improve much. > > Currently with single request, 1-10 req/sec, I get the suggest response at > 5-10(ms) > > All I want that I could get result at 10-50(ms) when 1-2k req/sec. > So what should I do ? More ram or more server or ??? > > Currently I have 5 index, each index has 1M record and I suggest in 5 > indexes. > Should I tried for 1 index only ? > > I see the document for store in memory but If the server down -\> I need to > reindex it again. > > Thanks. -- Met vriendelijke groet, Martijn van Groningen -- ---
**Author:** ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)\ **Post date:** [December 11, 2012, 9:38pm UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/11 "2012-12-11T21:38:54Z")
You should reconsider your decision, nobody can work with suggestions based on just one character, there are too many or unusable alternatives. min\_gram 2 or 3 will put some relief on your system, and make suggestions more performant. Best regards, Jörg On Tuesday, December 11, 2012 3:23:55 AM UTC+1, kidkid wrote: > @Jorg Prante: Yeah, min\_gram to 1 so that I could suggest from 1 character. -- ---
**Author:** ![zkidkid](https://avatars.discourse-cdn.com/v4/letter/z/fbc32d/32.png) [@zkidkid](https://discuss.elastic.co/u/zkidkid)\ **Post date:** [December 12, 2012, 2:27am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/12 "2012-12-12T02:27:42Z")
@Martijn v Groningen How many nodes are using for your tests right now? Does each index has 5 shards? -\> I have 3 nodes on 3 servers. Each severs I setup for 5 primary shards and 2 replicas shards. The easy way to improve your response times is to add more nodes. -\> It's is hard to require more node, I just have only 5M record. Adding more RAM would give your filesystem cache more space. This allows the OS the cache more index files. -\> Server and ES don't use up Ram. What type of disk are you using? Using SSD can improve your response times by many times. -\> HDD, SSD is too expensive here. Thanks for your suggest, but with 5M, I could put it on into RAM, so I really don't know why it's too slow 😑 @Jörg Prante : I set min\_gram = 1 so that I could suggest : hello w -- ---
**Author:** ![zkidkid](https://avatars.discourse-cdn.com/v4/letter/z/fbc32d/32.png) [@zkidkid](https://discuss.elastic.co/u/zkidkid)\ **Post date:** [December 12, 2012, 4:21am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/13 "2012-12-12T04:21:04Z")
Hi , I have set up to 3 nodes to bring it up to memory, and 1 node for holding data. index.number\_of\_shards: 5 index.number\_of\_replicas: 0 index.store.type: memory index.gateway.type: none gateway.type: fs gateway.fs.location: /path/data The request just about 200 req/s. With the same query I got many difference response time., 7ms, 32ms, 150ms. Is anyway to make the response time just around 50ms ? Thanks. > -- ---
**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, 3:00am UTC](https://discuss.elastic.co/t/how-to-improve-autocomplete-performance/10009/14 "2017-07-06T03:00:11Z")