Remove stopwords while querying using GET Request in Elasticsearch - elasticsearch

Question

I'm trying to implement Stop Token Filter in an index of Elasticsearch. I've following code taken from here.
PUT /test1
{
"settings": {
"analysis": {
"filter": {
"my_stop": {
"type": "stop",
"stopwords": "_english_"
}
}
}
}
}
I have my data stored in JSON format and have a field named as Ingredients which contains stopped words. I want to search through the whole index (containing almost 80k records) about the top 100 most appeared values in Ingredients tag. The query I'm using to retrieve the results is
GET test1/_search?size=0&pretty
{
"aggs": {
"genres": {
"terms": {
"field": "Ingredients",
"size": 100,
"exclude": "[0-9].*"
}
}
}
}
I need to exclude Numbers from it for which I'm using exclude.
But applying the above query using Kibana it doesn't remove the Stop Words and keeps them displayed while querying response.
As per the documentation, it should remove the stopped words but it isn't doing that. I'm unable to find the cause as I'm a newbie in Elasticsearch. Please help me figure it out.
I'm using elasticsearch-7.3.1 and Kibana-7.3.1.
I'm working over it for about two days but none of the methods is working. Thanks! Any help would be really appreciated.
If I try it using this way, it works but while putting the GET request as per the method defined above, it doesn't work at all.
POST test1/_analyze
{
"analyzer": "my_stop",
"text": "House of Dickson<br> corp"
}
My Mapping
{
"recipe_test" : {
"aliases" : { },
"mappings" : {
"properties" : {
"Author" : {
"properties" : {
"additionalInfo" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"description" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"eval" : {
"type" : "boolean"
},
"url" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"value" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
},
"Category" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Channel" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Cousine" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Ingredients" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
},
"fielddata" : true
},
"Keywords" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"MakingMethod" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Publication" : {
"properties" : {
"additionalInfo" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"eval" : {
"type" : "boolean"
},
"published" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"url" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"value" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
},
"Rating" : {
"properties" : {
"bestRating" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"ratingCount" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"ratingValue" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"worstRating" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
},
"Servings" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Timings" : {
"properties" : {
"cookTime" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"prepTime" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"totalTime" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
},
"Title" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"description" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"recipe_url" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
},
"settings" : {
"index" : {
"number_of_shards" : "1",
"provided_name" : "recipe_test",
"creation_date" : "1567443878756",
"analysis" : {
"filter" : {
"english_stop" : {
"type" : "stop",
"stopwords" : "_english_"
}
},
"analyzer" : {
"rebuilt_stop" : {
"filter" : [
"asciifolding",
"lowercase",
"english_stop"
],
"tokenizer" : "standard"
}
}
},
"number_of_replicas" : "1",
"uuid" : "K-FrOyc6QlWokGQoN6HxCg",
"version" : {
"created" : "7030199"
}
}
}
}
}
My Example Data
{
"recipe_url": "http1742637/bean-and-pesto-mash",
"Channel": "waqas",
"recipe_id":"31",
"Title": "Bean & pesto mash",
"Rating": {
"ratingValue": "4.625",
"bestRating": "5",
"worstRating": "1",
"ratingCount": "8"
},
"Timings": {
"cookTime": "PT5M",
"prepTime": "PT5M",
"totalTime": "PT10M"
},
"Author": {
"eval": false,
"value": "dfgkkdfgdfgfmes",
"url": "https://www.example.com/",
"additionalInfo": "Recipe from Good Food magazine, ",
"description": "Substitute potatoes with pulses for a healthy alternative mash with a chunky texture",
"published": "November 2011"
},
"Publication": {
"eval": false,
"value": "",
"url": "",
"additionalInfo": "",
"published": ""
},
"Nutrition": "per serving",
"NutritionContents": {
"kcal": "183",
"fat": "5g",
"saturates": "1g",
"carbs": "25g",
"sugars": "3g",
"fibre": "7g",
"protein": "11g",
"salt": "0.84g"
},
"SkillLevel": "Easy",
"Ingredients": [
"drizzle", "Asparagus" , "Asparagus" , "Asparagus" , "Asparagus" , "Asparagus" , "Asparagus" , "Asparagus" , "Asparagus" , "Asparagus"
],
"MakingMethod": [
"Heat the oil in a large saucepan. Add the beans and cook for 3-4 mins until hot through. Lightly mash with a potato masher for a chunky texture. Stir through the pesto and season. To serve, drizzle with a little olive oil, if you like."
],
"Keywords": [
"Cannellini bean",
"Cannellini beans",
"Mash",
"Beans",
"Super healthy",
"Pulses",
"5-a-day",
"Low fat",
"Diet",
"Dieting",
"Side dish",
"Bangers and mash",
"Sausage and mash",
"Texture",
"Fireworks",
"Pesto",
"Easy",
"Vegetarian",
"Healthy",
"Bonfire Night"
],
"Category": [
"Side dish",
"Dinner"
],
"Cousine": "British",
"Servings": "Serves 4"
}

Answer 1

There is no easy way on how to do this.
Option 1
Enable fielddata on the text field on which you applied the correct analyzer. Something like this:
{
"settings": {
"analysis": {
"filter": {
"english_stop": {
"type": "stop",
"stopwords": "_english_"
}
},
"analyzer": {
"rebuilt_stop": {
"filter": [
"asciifolding",
"lowercase",
"english_stop"
],
"tokenizer": "standard"
}
}
}
},
"mappings": {
"properties": {
"Ingredients": {
"type": "text",
"analyzer": "rebuilt_stop",
"fielddata": true
}
}
}
}
And then you run your terms aggregation.
Drawbacks: it could use a lot of memory because of fielddata usage.
Option 2
Use term vectors API. Since you are interested in the most used "values"/"terms" in Ingredients field you could call this API on one document in the index and have the total term frequency for each term in that specific document. The drawback: you need to specify a certain document ID and only the terms in that document will be reported back.
Something like this:
GET /test/_termvectors/1
{
"fields" : ["Ingredients"],
"offsets" : false,
"payloads" : false,
"positions" : false,
"term_statistics" : true,
"field_statistics" : false
}
Option 3
Probably the ugliest one. Something around these lines: Elasticsearch: index a field with keyword tokenizer but without stopwords
Advantage: is not using fielddata (heap memory). Drawback: you'd have to define the stopwords manually in the char_filter definition.