I am using elastic search for autocompletion and also to correct spelling mistakes.I have this mapping for my field(for auto-completion).
**Mapping:**
"name": {
"type": "text",
"analyzer": "autocomplete"
}
Now i want to implement phrase suggester on this field.When i use this it is giving wrong result.Thats because of existing mapping i think.
**POST XYZ/_search**
{
"suggest": {
"text": "ipone 16",
"simple_phrase": {
"phrase": {
"field": "name",
"highlight": {
"pre_tag": "<em>",
"post_tag": "</em>"
}
}
}
}
}
**Results:**
"options": [
{
"text": "i ip ipo iphon iphone 1 16",
"highlighted": "i ip ipo <em>iphon iphone</em> 1 16",
"score": 1.6111489e-8
},
{
"text": "i ip ipo iphon iphon 1 16",
"highlighted": "i ip ipo <em>iphon iphon</em> 1 16",
"score": 1.4219211e-8
},
{
"text": "i ip ipo ipho iphone 1 16",
"highlighted": "i ip ipo <em>ipho iphone</em> 1 16",
"score": 1.3510152e-8
},
{
"text": "i ip ipo ipho iphon 1 16",
"highlighted": "i ip ipo <em>ipho iphon</em> 1 16",
"score": 1.1923397e-8
},
{
"text": "i ip ipo iron iphone 1 16",
"highlighted": "i ip ipo <em>iron iphone</em> 1 16",
"score": 6.443544e-9
}
]
**From the document i should use this for phrase suggester.**
"mappings": {
"test": {
"properties": {
"title": {
"type": "text",
"fields": {
"trigram": {
"type": "text",
"analyzer": "trigram"
},
"reverse": {
"type": "text",
"analyzer": "reverse"
}
}
}
}
**How can i use two different mapping on same filed?**
As your results are not tokenized properly the problem could be from
your aurocomplete analyzer. please provide your _settings to see the
defination for your analyzers.
Do Your query on name.trigram.
After solving this problem it's good to prune your result using collate
You can write a query like this. Please provide output for this query.
It's also good to have your trigram analyzer settings (tokenizer, char mappers and token filters)
{
"suggest": {
"text": "noble prize",
"simple_phrase": {
"phrase": {
"field": "name_suggest.trigram",
"size": 1,
"gram_size": 3,
"direct_generator": [
{
"field": "name_suggest.trigram",
"suggest_mode": "always"
}
],
"collate": {
"query": {
"inline": {
"match": {
"title": "{{suggestion}}"
}
}
},
"prune": true
},
"highlight": {
"pre_tag": "<em>",
"post_tag": "</em>"
}
}
}
}
}
Related
I have a use case where I need to find the latest data based on some fields.
The fields are:
category.name
category.type
createdAt
For example: search for the newest data where category.name = 'John G.' AND category.type = 'A'. I expect the data with ID = 1 where it matches the criteria and is the newest one based on createdAt field ("createdAt": "2022-04-18 19:09:27.527+0200")
The problem is that category.* is a nested field and I can't aggs/collapse these fields because ES doesn't support it.
Mapping:
PUT data
{
"mappings": {
"properties": {
"createdAt": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss.SSSZ"
},
"category": {
"type": "nested",
"properties": {
"name": {
"type": "text",
"analyzer": "keyword"
}
}
},
"approved": {
"type": "text",
"analyzer": "keyword"
}
}
}
}
Data:
POST data/_create/1
{
"category": [
{
"name": "John G.",
"level": "A"
},
{
"name": "Chris T.",
"level": "A"
}
],
"createdBy": "John",
"createdAt": "2022-04-18 19:09:27.527+0200",
"approved": "no"
}
POST data/_create/2
{
"category": [
{
"name": "John G.",
"level": "A"
},
{
"name": "Chris T.",
"level": "A"
}
],
"createdBy": "Max",
"createdAt": "2022-04-10 10:09:27.527+0200",
"approved": "no"
}
POST data/_create/3
{
"category": [
{
"name": "Rick J.",
"level": "B"
}
],
"createdBy": "Rick",
"createdAt": "2022-03-02 02:09:27.527+0200",
"approved": "no"
}
I'm looking for either a search query that can handle that in an acceptable performant way, or a new object design without nested type where I could take advantage of aggs/collapse feature.
Any suggestion will be really appreciated.
About your first question,
For example: search for the newest data where category.name = 'John G.' AND category.type = 'A'. I expect the data with ID = 1 where it matches the criteria and is the newest one based on createdAt field ("createdAt": "2022-04-18 19:09:27.527+0200")
I believe you can do something along those lines:
GET /72088168/_search
{
"query": {
"nested": {
"path": "category",
"query": {
"bool": {
"must": [
{
"match": {
"category.name": "John G."
}
},
{
"match": {
"category.level": "A"
}
}
]
}
}
}
},
"sort": [
{
"createdAt": {
"order": "desc"
}
}
],
"size":1
}
For the 2nd matter, it really depends on what you are aiming to do. could merge category.name and category.level in the same field. Such that you document would look like:
{
"category": ["John G. A","Chris T. A"],
"createdBy": "Max",
"createdAt": "2022-04-10 10:09:27.527+0200",
"approved": "no"
}
No more nested needed. Although I agree it feels like using tape to fix your issue.
I am having my data indexed in elastic search in version 7.11. This is my mapping i got when i directly added documents to my index.
{"properties":{"name":{"type":"text","fields":{"keyword":{"type":"keyword","ignore_above":256}}}
I havent added the keyword part but no idea where it came from.
I am running a wild card query on the same. But unable to get data for keywords with spaces.
{
"query": {
"bool":{
"should":[
{"wildcard": {"name":"*hello world*"}}
]
}
}
}
Have seen many answers related to not_analyzed . And i have tried updating {"index":"true"} in mapping but with no help. How to make the wild card search work in this version of elastic search
Tried adding the wildcard field
PUT http://localhost:9001/indexname/_mapping
{
"properties": {
"name": {
"type" :"wildcard"
}
}
}
And got following response
{
"error": {
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "mapper [name] cannot be changed from type [text] to [wildcard]"
}
],
"type": "illegal_argument_exception",
"reason": "mapper [name] cannot be changed from type [text] to [wildcard]"
},
"status": 400
}
Adding a sample document to match
{
"_index": "accelerators",
"_type": "_doc",
"_id": "602ec047a70f7f30bcf75dec",
"_score": 1.0,
"_source": {
"acc_id": "602ec047a70f7f30bcf75dec",
"name": "hello world example",
"type": "Accelerator",
"description": "khdkhfk ldsjl klsdkl",
"teamMembers": [
{
"userId": "karthik.r#gmail.com",
"name": "Karthik Ganesh R",
"shortName": "KR",
"isOwner": true
},
{
"userId": "anand.sajan#gmail.com",
"name": "Anand Sajan",
"shortName": "AS",
"isOwner": false
}
],
"sectorObj": [
{
"item_id": 14,
"item_text": "Cross-sector"
}
],
"geographyObj": [
{
"item_id": 4,
"item_text": "Global"
}
],
"technologyObj": [
{
"item_id": 1,
"item_text": "Artificial Intelligence"
}
],
"themeColor": 1,
"mainImage": "assets/images/Graphics/Asset 35.svg",
"features": [
{
"name": "Ideation",
"icon": "Asset 1007.svg"
},
{
"name": "Innovation",
"icon": "Asset 1044.svg"
},
{
"name": "Strategy",
"icon": "Asset 1129.svg"
},
{
"name": "Intuitive",
"icon": "Asset 964.svg"
},
],
"logo": {
"actualFileName": "",
"fileExtension": "",
"fileName": "",
"fileSize": 0,
"fileUrl": ""
},
"customLogo": {
"logoColor": "#B9241C",
"logoText": "EC",
"logoTextColor": "#F6F6FA"
},
"collaborators": [
{
"userId": "muhammed.arif#gmail.com",
"name": "muhammed Arif P T",
"shortName": "MA"
},
{
"userId": "anand.sajan#gmail.com",
"name": "Anand Sajan",
"shortName": "AS"
}
],
"created_date": "2021-02-18T19:30:15.238000Z",
"modified_date": "2021-03-11T11:45:49.583000Z"
}
}
You cannot modify a field mapping once created. However, you can create another sub-field of type wildcard, like this:
PUT http://localhost:9001/indexname/_mapping
{
"properties": {
"name": {
"type": "text",
"fields": {
"wildcard": {
"type" :"wildcard"
},
"keyword": {
"type" :"keyword",
"ignore_above":256
}
}
}
}
}
When the mapping is updated, you need to reindex your data so that the new field gets indexed, like this:
POST http://localhost:9001/indexname/_update_by_query
And then when this finishes, you'll be able to query on this new field like this:
{
"query": {
"bool": {
"should": [
{
"wildcard": {
"name.wildcard": "*hello world*"
}
}
]
}
}
}
I am using Elasticsearch 7.2.0 and i want to create search suggestion.
For example i have these 3 movies titles:
Avengers: Infinity War Avengers: Infinity War Part 2 Avengers:
Age of Ultron
When i type "aven" should return suggestion like:
avengers
avengers infinity
avengers age
When i type "avengers inf"
avengers infinity war
avengers infinity war part 2
after lots of elasticsearch tutorials i have done this:
Check Cluster
PUT movies
{
"settings": {
"index": {
"analysis": {
"filter": {},
"analyzer": {
"keyword_analyzer": {
"filter": [
"lowercase",
"asciifolding",
"trim"
],
"char_filter": [],
"type": "custom",
"tokenizer": "keyword"
},
"edge_ngram_analyzer": {
"filter": [
"lowercase"
],
"tokenizer": "edge_ngram_tokenizer"
},
"edge_ngram_search_analyzer": {
"tokenizer": "lowercase"
},
"completion_analyzer": {
"tokenizer": "keyword",
"filter": "lowercase"
}
},
"tokenizer": {
"edge_ngram_tokenizer": {
"type": "edge_ngram",
"min_gram": 2,
"max_gram": 5,
"token_chars": [
"letter"
]
}
}
}
}
},
"mappings": {
"properties": {
"name": {
"type": "text",
"fields": {
"keywordstring": {
"type": "text",
"analyzer": "keyword_analyzer"
},
"edgengram": {
"type": "text",
"analyzer": "edge_ngram_analyzer",
"search_analyzer": "edge_ngram_search_analyzer"
},
"completion": {
"type": "completion"
}
},
"analyzer": "standard"
},
"completion_terms": {
"type": "text",
"fielddata": true,
"analyzer": "completion_analyzer"
}
}
}
}
whth the folowing docs:
POST movies/_doc/1
{
"name": "Spider-Man: Homecoming",
"completion_terms": [
"spider-man",
"homecomming"
]
}
POST movies/_doc/2
{
"name": "Ant-man and the Wasp",
"completion_terms": [
"ant-man",
"and",
"the",
"wasp"
]
}
POST movies/_doc/3
{
"name": "Avengers: Infinity War Part 2",
"completion_terms": [
"avangers",
"infinity",
"war",
"part",
"2"
]
}
POST movies/_doc/4
{
"name": "Captain Marvel",
"completion_terms": [
"captain",
"marvel"
]
}
POST movies/_doc/5
{
"name": "Black Panther",
"completion_terms": [
"black",
"panther"
]
}
POST movies/_doc/6
{
"name": "Avengers: Infinity War",
"completion_terms": [
"avangers",
"infinity",
"war"
]
}
POST movies/_doc/7
{
"name": "Thor: Ragnarok",
"completion_terms": [
"thor",
"ragnarok"
]
}
POST movies/_doc/8
{
"name": "Guardians of the Galaxy Vol 2",
"completion_terms": [
"guardians",
"of",
"the",
"galaxy",
"vol",
"2"
]
}
POST movies/_doc/9
{
"name": "Doctor Strange",
"completion_terms": [
"doctor",
"strange"
]
}
POST movies/_doc/10
{
"name": "Captain America: Civil War",
"completion_terms": [
"captain",
"america",
"civil",
"war"
]
}
POST movies/_doc/11
{
"name": "Ant-Man",
"completion_terms": [
"ant-man"
]
}
POST movies/_doc/12
{
"name": "Avengers: Age of Ultron",
"completion_terms": [
"avangers",
"age",
"of",
"ultron"
]
}
POST movies/_doc/13
{
"name": "Guardians of the Galaxy",
"completion_terms": [
"guardians",
"of",
"the",
"galaxy"
]
}
POST movies/_doc/14
{
"name": "Captain America: The Winter Soldier",
"completion_terms": [
"captain",
"america",
"the",
"winter",
"solider"
]
}
POST movies/_doc/15
{
"name": "Thor: The Dark World",
"completion_terms": [
"thor",
"the",
"dark",
"world"
]
}
POST movies/_doc/16
{
"name": "Iron Man 3",
"completion_terms": [
"iron",
"man",
"3"
]
}
POST movies/_doc/17
{
"name": "Marvel’s The Avengers",
"completion_terms": [
"marvels",
"the",
"avangers"
]
}
POST movies/_doc/18
{
"name": "Captain America: The First Avenger",
"completion_terms": [
"captain",
"america",
"the",
"first",
"avanger"
]
}
POST movies/_doc/19
{
"name": "Thor",
"completion_terms": [
"thor"
]
}
POST movies/_doc/20
{
"name": "Iron Man 2",
"completion_terms": [
"iron",
"man",
"2"
]
}
POST movies/_doc/21
{
"name": "The Incredible Hulk",
"completion_terms": [
"the",
"incredible",
"hulk"
]
}
POST movies/_doc/22
{
"name": "Iron Man",
"completion_terms": [
"iron",
"man"
]
}
and the query
POST movies/_search
{
"suggest": {
"movie-suggest-fuzzy": {
"prefix": "avan",
"completion": {
"field": "name.completion",
"fuzzy": {
"fuzziness": 1
}
}
}
}
}
My query return full title not pieces.
It's a great question and shows you have done a lot of research to get it to work, but you are unnecessary making it complex(by trying to handle it completely in ES), I was having exactly the same use-case and solved it using the combination of application side logic with ES.
What you actually need is match query on (n-1) terms and prefix query on the nth search term as you mentioned, in case of aven as its the first and nth term, prefix query would be on it and in case of avengers inf search term, avengers would be on match query and prefix would be on inf term.
I just indexed the documents given by you and tried both the search terms mentioned and it works:
Index creation
{
"mappings": {
"properties": {
"name": {
"type": "text"
}
}
}
}
Index 3 docs
{
"name" : "Avengers: Age of Ultron"
},
{
"name" : "Avengers: Infinity War Part 2"
},
{
"name" : "Avengers: Infinity War"
}
Search query
{
"query": {
"bool": {
"must": [
{
"match": { --> Note match queries on (n-1) terms
"name": "avengers"
}
},
{
"prefix": { --> Prefix query on nth term
"name": "ag"
}
}
]
}
}
}
Basically in your application code, you need to split the search terms based on whitespace and then construct the bool query with match clause on (n-1) terms and prefix query on the nth term.
Note you don't even need to use the edge n-gram analyzer and other complex things while indexing, which would save lot of spaces in your index, but you might wanna put a character limit on prefix query as it might be costly when searching in millions of docs as its not a token to token match as its there in match query.
I am using elasticsearch 5.5.2
I am trying phrase suggester and NOT able to configure it to return the exact suggestion that is in the index already. My index settings, type mappings and phrase suggest query are given below. Please help.
My index settings and type mappings are
PUT test
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"trigram_analyzer": {
"type": "custom",
"tokenizer": "standard",
"filter": ["shingle"]
}
},
"filter": {
"shingle": {
"type": "shingle",
"min_shingle_size": 2,
"max_shingle_size": 3
}
}
}
}
},
"mappings": {
"test": {
"properties": {
"title": {
"type": "text",
"fields": {
"trigram": {
"type": "text",
"analyzer": "trigram_analyzer"
}
}
}
}
}
}
}
Indexed document using
POST test/test?refresh=true
{"title": "noble prize"}
The phrase suggester I am using
POST test/_search
{
"suggest": {
"text": "nobe priz",
"simple_phrase": {
"phrase": {
"field": "title.trigram",
"size": 1,
"gram_size": 3,
"direct_generator": [ {
"field": "title.trigram",
"suggest_mode": "always"
} ],
"highlight": {
"pre_tag": "<em>",
"post_tag": "</em>"
}
}
}
}
}
The result I am getting is
"suggest": {
"simple_phrase": [
{
"text": "nobe priz",
"offset": 0,
"length": 9,
"options": [
{
"text": "noble priz",
"highlighted": "<em>noble</em> priz",
"score": 0.09049256
}
]
}
]
}
My question is, for the search text - 'nobe priz' - why I am NOT getting 'noble prize' as the suggestion. Instead why I am just getting 'noble priz'?
If we see, 'noble prize' is the document I have saved.
And if I increase the value of size to '2', then also I am NOT getting 'noble prize' as one of the suggestions.
With size as 2, for the search text 'nobe priz' I am getting the below response
"suggest": {
"simple_phrase": [
{
"text": "nobe priz",
"offset": 0,
"length": 9,
"options": [
{
"text": "noble priz",
"highlighted": "<em>nobel</em> priz",
"score": 0.09049256
},
{
"text": "nobe prize",
"highlighted": "nobe <em>prize</em>",
"score": 0.09049256
}
]
}
]
}
What should I do to get 'noble prize' as the suggestion?
Please help.
I found the answer myself. Need to tell ES how many terms in the search text are misspelled using the parameter 'max_errors'. 'max_errors' can be given as a percentage value in the form of float or an absolute number.
"click below for ES documentation on Phrase suggester with max_errors parameter"
https://www.elastic.co/guide/en/elasticsearch/reference/master/search-suggesters-phrase.html
Accordingly I added 'max_errors' parameter value as 2 like below
POST test/_search
{
"suggest": {
"text": "nobe priz",
"simple_phrase": {
"phrase": {
"field": "title.trigram",
"size": 1,
"gram_size": 3,
"max_errors": 2,
"direct_generator": [ {
"field": "title.trigram",
"suggest_mode": "always"
} ],
"highlight": {
"pre_tag": "<em>",
"post_tag": "</em>"
}
}
}
}
}
And I got the exact matching phrase suggestion as below
"suggest": {
"simple_phrase": [
{
"text": "nobe priz",
"offset": 0,
"length": 9,
"options": [
{
"text": "noble prize",
"highlighted": "<em>noble prize</em>",
"score": 0.4833575
}
]
}
]
}
So with max_errors as 2, the suggestion 'noble prize' is getting returned.
Cheers :)
I have the following data to be indexed on ElasticSearch.
I want to implement an autocomplete feature, and highlight why a specific document matched a query.
This are the settings of my index:
{
"settings": {
"number_of_shards": 1,
"analysis": {
"filter": {
"autocomplete_filter": {
"type": "edge_ngram",
"min_gram": 1,
"max_gram": 15
}
},
"analyzer": {
"autocomplete": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"autocomplete_filter"
]
}
}
}
}
}
Index Analyzing
Splits text on word boundaries.
Removes pontuation.
Lowercases
Edge NGrams each token
So the Inverted Index looks like:
This is how i defined the mappings for a name field:
{
"index_type": {
"properties": {
"name": {
"type": "string",
"index_analyzer": "autocomplete",
"search_analyzer": "standard"
}
}
}
}
When I query:
GET http://localhost:9200/index/type/_search
{
"query": {
"match": {
"name": "soft"
}
},
"highlight": {
"fields" : {
"name" : {}
}
}
}
Search for: soft
Applying the Standard Tokenizer, the "soft" is the term, to find on the inverted index. This search matches the Documents: 1, 3, 4, 5, 6, 7 which is correct, but the highlighted part I would expect to be "soft" and not the whole word:
{
"hits": [
{
"_source": {
"name": "SoftwareRocks everytime"
},
"highlight": {
"name": [
"<em>SoftwareRocks</em> everytime"
]
}
},
{
"_source": {
"name": "Software AG"
},
"highlight": {
"name": [
"<em>Software</em> AG"
]
}
},
{
"_source": {
"name": "Software AG2"
},
"highlight": {
"name": [
"<em>Software</em> AG2"
]
}
},
{
"_source": {
"name": "Op Software AG good software better"
},
"highlight": {
"name": [
"Op <em>Software</em> AG good <em>software</em> better"
]
}
},
{
"_source": {
"name": "Op Software AG"
},
"highlight": {
"name": [
"Op <em>Software</em> AG"
]
}
},
{
"_source": {
"name": "is soft ware ok"
},
"highlight": {
"name": [
"is <em>soft</em> ware ok"
]
}
}
]
}
Search for: software ag
Applying the Standard Tokenizer, the "software ag" is transformed into "software" and "ag", to find on the inverted index. This search matches the Documents: 1, 3, 4, 5, 6, which is correct, but the highlighted part I would expect to be "software" and "ag" and not the whole word around "software" and "ag":
{
"hits": [
{
"_source": {
"name": "Software AG"
},
"highlight": {
"name": [
"<em>Software</em> <em>AG</em>"
]
}
},
{
"_source": {
"name": "Software AG2"
},
"highlight": {
"name": [
"<em>Software</em> <em>AG2</em>"
]
}
},
{
"_source": {
"name": "Op Software AG"
},
"highlight": {
"name": [
"Op <em>Software</em> <em>AG</em>"
]
}
},
{
"_source": {
"name": "Op Software AG good software better"
},
"highlight": {
"name": [
"Op <em>Software</em> <em>AG</em> good <em>software</em> better"
]
}
},
{
"_source": {
"name": "SoftwareRocks everytime"
},
"highlight": {
"name": [
"<em>SoftwareRocks</em> everytime"
]
}
}
]
}
I read the highlight documentation on elasticsearch, but I cannot understand how the highlighting is performed. For the two examples above I expect only the matched token on the inverted index to be highlighted and not the whole word.
Can anyone help how to highlight only the passed value?
Update
So, in seems that on ElasticSearch website, the autocomplete on the server side is similar to my implementation. However it seems that they highlight the matched query on the client.
If they do like this, I started to think that there is not a proper solution to do it on ElasticSearch side, so I implemented the highlight feature on server side instead of on client side(as they seem to do).
My implementation on server side(using PHP) is:
public function search($term)
{
$params = [
'index' => $this->getIndexName(),
'type' => $this->getIndexType(),
'body' => [
'query' => [
'match' => [
'name' => $term
]
]
]
];
$results = $this->client->search($params);
$hits = $results['hits']['hits'];
$data = [];
$wrapBefore = '<strong>';
$wrapAfter = '</strong>';
foreach ($hits as $hit) {
$data[] = [
$hit['_source']['id'],
$hit['_source']['name'],
preg_replace("/($term)/i", "$wrapBefore$1$wrapAfter", strip_tags($hit['_source']['name']))
];
}
return $data;
}
Outputs what I aimed with this question:
I added a bounty to see if there is a solution at ElasticSearch level to achive what I described above.
As of now with latest version of elastic this is not possible as highligh documentation don't refer any settings or query for this. I checked elastic autocomplete example in browser console under xhr requests tab and found the response for "att" autocomplete response for keyword as follows.
url - https://search.elastic.co/suggest?q=att
{
"current_page": 1,
"last_page": 4,
"total_hits": 49,
"hits": [
{
"tags": [],
"url": "/elasticon/tour/2016/jp/not-attending",
"section": "Elasticon",
"title": "Not <em>Attending</em> - JP"
},
{
"section": "Elasticon",
"title": "<em>Attending</em> from Training - JP",
"tags": [],
"url": "/elasticon/tour/2016/jp/attending-training"
},
{
"tags": [],
"url": "/elasticon/tour/2016/jp/attending-keynote",
"title": "<em>Attending</em> from Keynote - JP",
"section": "Elasticon"
},
{
"tags": [],
"url": "/elasticon/tour/2016/not-attending",
"section": "Elasticon",
"title": "Thank You - Not <em>Attending</em>"
},
{
"tags": [],
"url": "/elasticon/tour/2016/attending",
"section": "Elasticon",
"title": "Thank You - <em>Attending</em>"
},
{
"section": "Blog",
"title": "What It's Like to <em>Attend</em> Elastic Training",
"tags": [],
"url": "/blog/what-its-like-to-attend-elastic-training"
},
{
"tags": "Elasticsearch",
"url": "/guide/en/elasticsearch/plugins/5.0/mapper-attachments-highlighting.html",
"section": "Docs/",
"title": "Highlighting <em>attachments</em>"
},
{
"title": "<em>attachments</em> » email",
"section": "Docs/",
"tags": "Logstash",
"url": "/guide/en/logstash/5.0/plugins-outputs-email.html#plugins-outputs-email-attachments"
},
{
"section": "Docs/",
"title": "Configuring Email <em>Attachments</em> » Actions",
"tags": "Watcher",
"url": "/guide/en/watcher/2.4/actions.html#configuring-email-attachments"
},
{
"url": "/guide/en/watcher/2.4/actions.html#hipchat-action-attributes",
"tags": "Watcher",
"title": "HipChat Action <em>Attributes</em> » Actions",
"section": "Docs/"
},
{
"title": "Slack Action <em>Attributes</em> » Actions",
"section": "Docs/",
"tags": "Watcher",
"url": "/guide/en/watcher/2.4/actions.html#slack-action-attributes"
}
],
"aggs": {
"sections": [
{
"Elasticon": 5
},
{
"Blog": 1
},
{
"Docs/": 43
}
],
"top_tags": [
{
"XPack": 14
},
{
"Elasticsearch": 12
},
{
"Watcher": 9
},
{
"Logstash": 4
},
{
"Clients": 3
},
{
"Shield": 1
}
]
}
}
But on frontend they are showing "att" only highlighted on in the autosuggest results. Hence they are handling the highlight stuff on browser layer.