The problem is any character sequence having boost operator "^(caret symbol)" does not returning any search results.
But as per the below elastic search documentation
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-query-string-query.html#_reserved_characters
&& || ! ( ) { } [ ] ^ " ~ * ? : \ characters can be escaped with \ symbol.
Have a requirement to do a contains search using n-gram analyser in elastic search.
Below is the mapping structure of the sample use case and the
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"nGram_analyzer": {
"filter": [
"lowercase",
"asciifolding"
],
"type": "custom",
"tokenizer": "ngram_tokenizer"
},
"whitespace_analyzer": {
"filter": [
"lowercase",
"asciifolding"
],
"type": "custom",
"tokenizer": "whitespace"
}
},
"tokenizer": {
"ngram_tokenizer": {
"token_chars": [
"letter",
"digit",
"punctuation",
"symbol"
],
"min_gram": "2",
"type": "nGram",
"max_gram": "20"
}
}
}
}
},
"mappings": {
"employee": {
"properties": {
"employeeName": {
"type": "string",
"analyzer": "nGram_analyzer",
"search_analyzer": "whitespace_analyzer"
}
}
}
}
}
Have a employee name like below with special characters included
xyz%^&*
Also the sample query used for the contains search as below
GET
{
"query": {
"bool": {
"must": [
{
"match": {
"employeeName": {
"query": "xyz%^",
"type": "boolean",
"operator": "or"
}
}
}
]
}
}
}
Even if we try to escape as "query": "xyz%\^" its errors out. So not able to search any character contains search having "^(caret symbol)"
Any help is greatly appreciated.
There is a bug in ngram tokenizer related to issue.
Essentially ^ is not considered either Symbol |Letter |Punctuation by ngram-tokenizer.
As a result it tokenizes the input on ^.
Example: (url encoded xyz%^):
GET <index_name>/_analyze?tokenizer=ngram_tokenizer&text=xyz%25%5E
The above result of analyze api shows there is no ^ as shown in the response below :
{
"tokens": [
{
"token": "xy",
"start_offset": 0,
"end_offset": 2,
"type": "word",
"position": 0
},
{
"token": "xyz",
"start_offset": 0,
"end_offset": 3,
"type": "word",
"position": 1
},
{
"token": "xyz%",
"start_offset": 0,
"end_offset": 4,
"type": "word",
"position": 2
},
{
"token": "yz",
"start_offset": 1,
"end_offset": 3,
"type": "word",
"position": 3
},
{
"token": "yz%",
"start_offset": 1,
"end_offset": 4,
"type": "word",
"position": 4
},
{
"token": "z%",
"start_offset": 2,
"end_offset": 4,
"type": "word",
"position": 5
}
]
}
Since '^' is not indexed therefore there are no matches
Related
I have one field in which I am storing values like O5467508 (Starting with alphabet "O")
Below is my query.
{"from":0,"size":10,"query":{"bool":{"must":[{"match":{"field_LIST_105":{"query":"o5467508","type":"phrase_prefix"}}},{"bool":{"must":[{"match":{"RegionName":"Virginia"}}]}}]}}}
it is giving me correct result, But when i am searching for only numeric value "5467508", query result is empty.
Thanks in advance.
One of the possible solution that could help you, use word_delimiter filter, with the option preserve_original, which will save original token.
Something like this:
{
"settings": {
"analysis": {
"analyzer": {
"so_analyzer": {
"type": "custom",
"tokenizer": "keyword",
"filter": [
"lowercase",
"my_word_delimiter"
]
}
},
"filter": {
"my_word_delimiter": {
"type": "word_delimiter",
"preserve_original": true
}
}
}
},
"mappings": {
"my_type": {
"properties": {
"field_LIST_105": {
"type": "text",
"analyzer": "so_analyzer"
}
}
}
}
}
I did a quick test of analysis, and this is the tokens that it give to me.
{
"tokens": [
{
"token": "o5467508",
"start_offset": 0,
"end_offset": 8,
"type": "word",
"position": 0
},
{
"token": "o",
"start_offset": 0,
"end_offset": 1,
"type": "word",
"position": 0
},
{
"token": "5467508",
"start_offset": 1,
"end_offset": 8,
"type": "word",
"position": 1
}
]
}
For more information - https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-word-delimiter-tokenfilter.html
I have a string property called summary that has analyzer set to trigrams and search_analyzer set to words.
"filter": {
"words_splitter": {
"type": "word_delimiter",
"preserve_original": "true"
},
"english_words_filter": {
"type": "stop",
"stop_words": "_english_"
},
"trigrams_filter": {
"type": "ngram",
"min_gram": "2",
"max_gram": "20"
}
},
"analyzer": {
"words": {
"filter": [
"lowercase",
"words_splitter",
"english_words_filter"
],
"type": "custom",
"tokenizer": "whitespace"
},
"trigrams": {
"filter": [
"lowercase",
"words_splitter",
"trigrams_filter",
"english_words_filter"
],
"type": "custom",
"tokenizer": "whitespace"
}
}
I need that query strings given in input like React and HTML (or React, html) are being matched to documents that contain in the summary the words React, reactjs, react.js, html, html5. As more matching keywords they have, an higher score they have (I would expect lower scores on documents that have just a word matching not even at 100%, ideally).
The thing is, I guess at the moment react.js is split in both react and js since I get all the documents that contain js as well. On the other hand, Reactjs returns nothing. I also think to need words_splitter in order to ignore the comma.
You can solve the problem with names like react.js with a keyword marker filter and by defining the analyzer so that it uses the keyword filter. This will prevent react.js from being split into react and js tokens.
Here is an example configuration for the filter:
"filter": {
"keywords": {
"type": "keyword_marker",
"keywords": [
"react.js",
]
}
}
And the analyzer:
"analyzer": {
"main_analyzer": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"keywords",
"synonym_filter",
"german_stop",
"german_stemmer"
]
}
}
You can see whether your analyzer behaves as required using the analyze command:
GET /<index_name>/_analyze?analyzer=main_analyzer&text="react.js is a nice library"
This should return the following tokens where react.js is not tokenized:
{
"tokens": [
{
"token": "react.js",
"start_offset": 1,
"end_offset": 9,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "is",
"start_offset": 10,
"end_offset": 12,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "a",
"start_offset": 13,
"end_offset": 14,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "nice",
"start_offset": 15,
"end_offset": 19,
"type": "<ALPHANUM>",
"position": 3
},
{
"token": "library",
"start_offset": 20,
"end_offset": 27,
"type": "<ALPHANUM>",
"position": 4
}
]
}
For the words that are similar but not exactly the same as: React.js and Reactjs you could use a synonym filter. Do you have a fixed set of keywords that you want to match?
I found a solution.
Basically I'm going to define the word_delimiter filter with catenate_all active
"words_splitter": {
"catenate_all": "true",
"type": "word_delimiter",
"preserve_original": "true"
}
giving it to the words analyzer with a keyword tokenizer
"words": {
"filter": [
"words_splitter"
],
"type": "custom",
"tokenizer": "keyword"
}
Calling http://localhost:9200/sample_index/_analyze?analyzer=words&pretty=true&text=react.js I get the following tokens:
{
"tokens": [
{
"token": "react.js",
"start_offset": 0,
"end_offset": 8,
"type": "word",
"position": 0
},
{
"token": "react",
"start_offset": 0,
"end_offset": 5,
"type": "word",
"position": 0
},
{
"token": "reactjs",
"start_offset": 0,
"end_offset": 8,
"type": "word",
"position": 0
},
{
"token": "js",
"start_offset": 6,
"end_offset": 8,
"type": "word",
"position": 1
}
]
}
Using Elasticsearch 2.2, as a simple experiment, I want to remove the last character from any word that ends with the lowercase character "s". For example, the word "sounds" would be indexed as "sound".
I'm defining my analyzer like this:
{
"template": "document-index-template",
"settings": {
"number_of_shards": 1,
"analysis": {
"filter": {
"sFilter": {
"type": "pattern_replace",
"pattern": "([a-zA-Z]+)([s]( |$))",
"replacement": "$2"
}
},
"analyzer": {
"tight": {
"type": "standard",
"filter": [
"sFilter",
"lowercase"
]
}
}
}
}
}
Then when I analyze the term "sounds of silences" using this request:
<index>/_analyze?analyzer=tight&text=sounds%20of%20silences
I get:
{
"tokens": [
{
"token": "sounds",
"start_offset": 0,
"end_offset": 6,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "of",
"start_offset": 7,
"end_offset": 9,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "silences",
"start_offset": 10,
"end_offset": 18,
"type": "<ALPHANUM>",
"position": 2
}
]
}
I am expecting "sounds" to be "sound" and "silences" to be "silence"
The above analyzer setting is invalid .I think what you intended to use is an analyzer of type custom with tokenizer set to standard
Example:
{
"settings": {
"number_of_shards": 1,
"analysis": {
"filter": {
"sFilter": {
"type": "pattern_replace",
"pattern": "([a-zA-Z]+)s$",
"replacement": "$1"
}
},
"analyzer": {
"tight": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"sFilter"
]
}
}
}
}
}
I'm using Elasticsearch 2.2.0 and I'm trying to use the lowercase + asciifolding filters on a field.
This is the output of http://localhost:9200/myindex/
{
"myindex": {
"aliases": {},
"mappings": {
"products": {
"properties": {
"fold": {
"analyzer": "folding",
"type": "string"
}
}
}
},
"settings": {
"index": {
"analysis": {
"analyzer": {
"folding": {
"token_filters": [
"lowercase",
"asciifolding"
],
"tokenizer": "standard",
"type": "custom"
}
}
},
"creation_date": "1456180612715",
"number_of_replicas": "1",
"number_of_shards": "5",
"uuid": "vBMZEasPSAyucXICur3GVA",
"version": {
"created": "2020099"
}
}
},
"warmers": {}
}
}
And when I try to test the folding custom filter using the _analyze API, this is what I get as an output of http://localhost:9200/myindex/_analyze?analyzer=folding&text=%C3%89sta%20est%C3%A1%20loca
{
"tokens": [
{
"end_offset": 4,
"position": 0,
"start_offset": 0,
"token": "Ésta",
"type": "<ALPHANUM>"
},
{
"end_offset": 9,
"position": 1,
"start_offset": 5,
"token": "está",
"type": "<ALPHANUM>"
},
{
"end_offset": 14,
"position": 2,
"start_offset": 10,
"token": "loca",
"type": "<ALPHANUM>"
}
]
}
As you can see, the returned tokens are: Ésta, está, loca instead of esta, esta, loca. What's going on? it seems that this folding analyzer is being ignored.
Looks like a simple typo when you are creating your index.
In your "analysis":{"analyzer":{...}} block, this:
"token_filters": [...]
Should be
"filter": [...]
Check the documentation for confirmation of this. Because your filter array wasn't named correctly, ES completely ignored it, and just decided to use the standard analyzer. Here is a small example written using the Sense chrome plugin. Execute them in order:
DELETE /test
PUT /test
{
"analysis": {
"analyzer": {
"folding": {
"type": "custom",
"filter": [
"lowercase",
"asciifolding"
],
"tokenizer": "standard"
}
}
}
}
GET /test/_analyze
{
"analyzer":"folding",
"text":"Ésta está loca"
}
And the results of the last GET /test/_analyze:
"tokens": [
{
"token": "esta",
"start_offset": 0,
"end_offset": 4,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "esta",
"start_offset": 5,
"end_offset": 9,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "loca",
"start_offset": 10,
"end_offset": 14,
"type": "<ALPHANUM>",
"position": 2
}
]
I need it so that words with periods inside them are equal to the non-period variant.
I see there's a section in the docs about analyzers and token filters but I'm finding rather terse and am not sure how to go about it.
Use a char filter to eliminate the dots, like this for example:
PUT /no_dots
{
"settings": {
"analysis": {
"char_filter": {
"my_mapping": {
"type": "mapping",
"mappings": [
".=>"
]
}
},
"analyzer": {
"my_no_dots_analyzer": {
"tokenizer": "standard",
"char_filter": [
"my_mapping"
]
}
}
}
},
"mappings": {
"test": {
"properties": {
"text": {
"type": "string",
"analyzer": "my_no_dots_analyzer"
}
}
}
}
}
And to test it GET /no_dots/_analyze?analyzer=my_no_dots_analyzer&text=J.J Abrams returns:
{
"tokens": [
{
"token": "JJ",
"start_offset": 0,
"end_offset": 3,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "Abrams",
"start_offset": 4,
"end_offset": 10,
"type": "<ALPHANUM>",
"position": 2
}
]
}