I built an ElasticSearch index using a custom analyzer which uses letter tokenizer and lower_case and word_delimiter token filters. Then I tried searching for documents containing underscore-separated sub-words, e.g. abc_xyz, using only one of the sub-words, e.g. abc, but it didn't come back with any result. When I tried the full-word, i.e. abc_xyz, it did find the document.
Then I changed the document to have dash-separated sub-words instead, e.g. abc-xyz and tried to search by sub-words again and it worked.
To try to understand what is going on, I thought I would check the terms generated for my documents using _termvector service, and the result was identical for both, the underscore-separated sub-words and the dash-separated sub-words, so really I expect the result of searching to be identical in both cases.
Any idea what I could be doing wrong?
If it helps, this is the settings I used for my index:
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"cmt_value_analyzer": {
"tokenizer": "letter",
"filter": [
"lowercase",
"my_filter"
],
"type": "custom"
}
},
"filter": {
"my_filter": {
"type": "word_delimiter"
}
}
}
}
},
"mappings": {
"alertmodel": {
"properties": {
"name": {
"analyzer": "cmt_value_analyzer",
"term_vector": "with_positions_offsets_payloads",
"type": "string"
},
"productId": {
"type": "double"
},
"productName": {
"analyzer": "cmt_value_analyzer",
"term_vector": "with_positions_offsets_payloads",
"type": "string"
},
"link": {
"analyzer": "cmt_value_analyzer",
"term_vector": "with_positions_offsets_payloads",
"type": "string"
},
"updatedOn": {
"type": "date"
}
}
}
}
}
Related
Main question
The user is looking for a name and enters the part of the it, let's say au, and the document with the text paul is found.
I would like to have the doc highlighted like p<em>au</em>l.
How can I achieve it if I have a complex search query (combination of match, prefix, wildcard to rule relevance)?
Sub question
When do highlight settings from documentation for type, boundary_scanner and boundary_chars come into play? As per my tests described below, these settings don't change highlighted part.
Try 1: Wildcard query with default analyzer
PUT myindex
{
"mappings": {
"properties": {
"name": {
"type": "text",
"term_vector": "with_positions_offsets"
}
}
}
}
POST myindex/_doc/1
{
"name": "paul"
}
GET myindex/_search
{
"query": {
"wildcard": {"name": "*au*"}
},
"highlight": {
"fields": {
"name": {}
},
"type": "fvh",
"boundary_scanner": "chars",
"boundary_chars": "abcdefghijklmnopqrstuvwxyz.,!? \t\n"
}
}
This kind of search returns highlight <em>paul</em> but I need to get p<em>au</em>l.
Try 2: Match query with NGRAM analyzer
This one works as described in SO question: Highlighting part of word in elasticsearch
PUT myindexngram
{
"settings": {
"analysis": {
"tokenizer": {
"ngram_tokenizer": {
"type": "nGram",
"min_gram": "2",
"max_gram": "3",
"token_chars": [
"letter",
"digit"
]
}
},
"analyzer": {
"index_ngram_analyzer": {
"type": "custom",
"tokenizer": "ngram_tokenizer",
"filter": [
"lowercase"
]
},
"search_term_analyzer": {
"type": "custom",
"tokenizer": "keyword",
"filter": "lowercase"
}
}
}
},
"mappings": {
"properties": {
"name": {
"type": "text",
"analyzer": "index_ngram_analyzer",
"term_vector": "with_positions_offsets"
}
}
}
}
POST myindexngram/_doc/1
{
"name": "paul"
}
GET myindexngram/_search
{
"query": {
"match": {"name": "au"}
},
"highlight": {
"fields": {
"name": {}
}
}
}
This highlights p<em>au</em>l as desired but:
Highlighting depends on the query type, so combining match and wildcard will again result in <em>paul</em>.
Highlighting is not affected at all on type, boundary_scanner and boundary_chars settings.
Elastic version 7.13.4
Response from Elasticsearch team:
A highlighter works on terms, so only full terms can be highlighted - whatever are the terms in your index. In your second example, au could be highlighted, because it it a term in the index, which is not the case for your first example.
There is also an option to define your own highlight_query that could be different from the main query, but this could lead to unpredictable highlights.
https://discuss.elastic.co/t/configure-highlighted-part/295164
I have a bunch of categories with translations in my category field. I have defined language analyzers for the fields in my index so I can search for them. But it doesnt find the singular version of my words. wasmachine in titles.title-nl is singular of wasmachines but not found. What am I missing?
Demo document
"_source" : {
"google_id" : 2706,
"titles" : [
{
"title-en" : "laundry appliances",
"title-de" : "waschen & trocknen",
"title-fr" : "appareils de blanchisserie",
"title-nl" : "wasmachines"
}
]
}
Way I mapped them
PUT categories/_mapping/category
{
"dynamic": false,
"properties": {
"titles.title-nl": {
"type": "text",
"analyzer": "dutch"
},
"titles.title-en": {
"type": "text",
"analyzer": "english"
},
"titles.title-de": {
"type": "text",
"analyzer": "german"
},
"titles.title-fr": {
"type": "text",
"analyzer": "french"
}
}
}
The way I search for them
GET categories/_search
{
"size": 4,
"query": {
"multi_match": {
"query": "wasmachines",
"fields": ["titles.title-de","titles.title-en", "titles.title-fr", "titles.title-nl"]
}
}
}
The problem is that the default dutch analyzer doesn't know how to stem the word wasmachines, you will need to recreate your index with a custom analyzer using a stemmer_override.
Looking in the elastic documentation you can do the following to recreate the dutch analyzer and tell that wasmachines should be stemmed to wasmachine, just put wasmachine => wasmachines inside the rules for the stemmer_override
PUT categories/
{
"settings": {
"analysis": {
"filter": {
"dutch_stop": {
"type": "stop",
"stopwords": "_dutch_"
},
"dutch_keywords": {
"type": "keyword_marker",
"keywords": ["voorbeeld"]
},
"dutch_stemmer": {
"type": "stemmer",
"language": "dutch"
},
"dutch_override": {
"type": "stemmer_override",
"rules": [
"fiets=>fiets",
"bromfiets=>bromfiets",
"wasmachine=>wasmachines",
"ei=>eier",
"kind=>kinder"
]
}
},
"analyzer": {
"rebuilt_dutch": {
"tokenizer": "standard",
"filter": [
"lowercase",
"dutch_stop",
"dutch_keywords",
"dutch_override",
"dutch_stemmer"
]
}
}
}
}
}
You will also need to use that new analyzer in your mapping:
PUT categories/_mapping/category
{
"dynamic": false,
"properties": {
"titles.title-nl": {
"type": "text",
"analyzer": "rebuilt_dutch"
},
"titles.title-en": {
"type": "text",
"analyzer": "english"
},
"titles.title-de": {
"type": "text",
"analyzer": "german"
},
"titles.title-fr": {
"type": "text",
"analyzer": "french"
}
}
}
After that you will be able to search for wasmachine and get the documents that have wasmachines.
I have elasticsearch type I mapped as below,
mappings": {
"jardata": {
"properties": {
"groupID": {
"index": "not_analyzed",
"type": "string"
},
"artifactID": {
"index": "not_analyzed",
"type": "string"
},
"directory": {
"type": "string"
},
"jarFileName": {
"index": "not_analyzed",
"type": "string"
},
"version": {
"index": "not_analyzed",
"type": "string"
}
}
}
}
I am using index of directory as analyzed since I want give only the last folder and get the results, But when I want to search a specific directory I need to give the whole path since there can be same folder in two paths. The problem here is since it is analyzed it will all data instead the specific one I want.
The problem here is I want to act it like both analyzed and not_analyzed. is there a way for that?
Let's say you have the following document indexed:
{
"directory": "/home/docs/public"
}
The standard analyzer is not enough in your case as it will create following terms while indexing:
[home, docs, public]
Note that it misses [/home/docs/public] token - characters like "/" etc. are acting as separators here.
One solution could be to use NGram tokenizer with punctuation character class in token_chars list. Elasticsearch would treat "/" as it would be a letter or digit. This would allow to search with following tokens:
[/hom, /home, ..., /home/docs/publi, /home/docs/public, ..., /docs/public, etc...]
Index mapping:
{
"settings": {
"analysis": {
"analyzer": {
"ngram_analyzer": {
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "ngram",
"min_gram": 4,
"max_gram": 18,
"token_chars": [
"letter",
"digit",
"punctuation"
]
}
}
}
},
"mappings": {
"jardata": {
"properties": {
"directory": {
"type": "string",
"analyzer": "ngram_analyzer"
}
}
}
}
}
Now both search queries:
{
"query": {
"bool" : {
"must" : {
"term" : {
"directory": "/docs/private"
}
}
}
}
}
and
{
"query": {
"bool" : {
"must" : {
"term" : {
"directory": "/home/docs/private"
}
}
}
}
}
will give the indexed document in result.
One thing you have to consider is the maximum length of the token that is specified in "max_gram" setting. In case of directory paths it could be necessary to have it longer.
Alternative solution is to use Whitespace tokenizer, that breaks the phrase into terms only on whitespaces, and NGram filter with following mapping:
{
"settings": {
"analysis": {
"filter": {
"ngram_filter": {
"type": "ngram",
"min_gram": 4,
"max_gram": 20
}
},
"analyzer": {
"my_analyzer": {
"type": "custom",
"tokenizer": "whitespace",
"filter": [
"lowercase",
"ngram_filter"
]
}
}
}
},
"mappings": {
"jardata": {
"properties": {
"directory": {
"type": "string",
"analyzer": "my_analyzer"
}
}
}
}
}
update the mapping of the directory field to contain raw field like this:
"directory": {
"type": "string",
"fields": {
"raw": {
"index": "not_analyzed",
"type": "string"
}
}
}
And modify your query to include directory.raw which will treat it like not_analyzed. Refer this.
I have a problem with ElasticSearch language analyzer. I am working on Lithuanian language, so I am using Lithuanian language analyzer. Analyzer works fine and I got all word cases I need. For example, I index Lithuania city "Klaipėda":
PUT /cities/city/1
{
"name": "Klaipėda"
}
Problem is that I also need to get a result, when I am searching "Klaipėda" only in Latin alphabet ("Klaipeda") and in all Lithuanian cases:
Nomanitive case: "Klaipeda"
Genitive case: "Klaipedos"
...
Locative case: "Klaipedoje"
"Klaipėda", "Klaipėdos", "Klaipėdoje" - works, but "Klaipeda", "Klaipedos", "Klaipedoje" - not.
My index:
PUT /cities
{
"mappings": {
"city": {
"properties": {
"name": {
"type": "string",
"analyzer": "lithuanian",
"fields": {
"folded": {
"type": "string",
"analyzer": "md_folded_analyzer"
}
}
}
}
}
},
"settings": {
"analysis": {
"analyzer": {
"md_folded_analyzer": {
"type": "lithuanian",
"tokenizer": "standard",
"filter": [
"lowercase",
"asciifolding",
"lithuanian_stop",
"lithuanian_keywords",
"lithuanian_stemmer"
]
}
}
}
}
}
and search query:
GET /cities/_search
{
"query": {
"multi_match" : {
"type": "most_fields",
"query": "klaipeda",
"fields": [ "name", "name.folded" ]
}
}
}
What I am doing wrong? Thanks for help.
The technique you are using here is so-called multi-fields. The limitation of the underlying name.folded field is that you can't perform search against it - you can perform only sorting by name.folded and aggregation.
To make a way round this I've come up with the following set-up:
Separate fields set-up (to eliminate duplicates - just specify copy_to):
curl -XPUT http://localhost:9200/cities -d '
{
"mappings": {
"city": {
"properties": {
"name": {
"type": "string",
"analyzer": "lithuanian",
"copy_to": "folded",
},
"folded": {
"type": "string",
"analyzer": "md_folded_analyzer"
}
}
}
}
}'
Change the type of your analyzer to custom as it described here, because otherwise the asciifolding is not got into the config. And more important - asciifolding should go after all stemming / stop-words in Lithuanian language, because after folding the word can miss desired sense.
curl -XPUT http://localhost:9200/my_cities -d '
{
"settings": {
"analysis": {
"filter": {
"lithuanian_stop": {
"type": "stop",
"stopwords": "_lithuanian_"
},
"lithuanian_stemmer": {
"type": "stemmer",
"language": "lithuanian"
}
},
"analyzer": {
"md_folded_analyzer": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"lithuanian_stop",
"lithuanian_stemmer",
"asciifolding"
]
}
}
}
}
}
Sorry I've eliminated lithuanian_keywords - it requires additional set-up, which I missed here. But I hope you've got the idea.
I use elasticsearch ngram
"analysis": {
"filter": {
"desc_ngram": {
"type": "ngram",
"min_gram": 3,
"max_gram": 8
}
},
"analyzer": {
"index_ngram": {
"type": "custom",
"tokenizer": "keyword",
"filter": [ "desc_ngram", "lowercase" ]
},
"search_ngram": {
"type": "custom",
"tokenizer": "keyword",
"filter": "lowercase"
}
}
}
And I have 2 objects here
{
"name": "Shana Calandra",
"username": "shacalandra",
},
{
"name": "Shana Launer",
"username": "shalauner",
},
And using this query
{
query: {
match: {
_all: "Shana"
}
}
}
When I search with this query, it returns me both documents, but I cant search by part of word here, for example I cant use "Shan" instead of "Shana" in query because it doesnt return anything.
Maybe my mapping is wrong, I cant understand problem is on mapping or on query
If you specify
"mappings": {
"test": {
"_all": {
"index_analyzer": "index_ngram",
"search_analyzer": "search_ngram"
},
for your mapping of _all field then it will work. _all has its own analyzers and I suspect you used the analyzers just for name and username and not for _all.