I am struggling to query for exact match. This field is identical in two fields in the document, within _id and within one field in the body.
So I can search either of these fields. Is there any way to configure the term query to support this? I've tried specifying whitespace analyzer but it doesn't seem to be a supported configuration for term queries.
Ive tried a few variations, but none of it has worked so far..
data: {
query: {
term: {
"_id":"4123-0000"
}
}
}
This doesn't return anything.
Issue is that as you are using default mapping, your _id field seems to be populated by you, which would have used text field which uses the standard analyzer and splits the tokens based on -, so your _id field is tokenized as below:
POST /_analyze
{
"text" : "4123-0000",
"analyzer" : "standard"
}
And tokens
{
"tokens": [
{
"token": "4123",
"start_offset": 0,
"end_offset": 4,
"type": "<NUM>",
"position": 0
},
{
"token": "0000",
"start_offset": 5,
"end_offset": 9,
"type": "<NUM>",
"position": 1
}
]
}
Now as you might be aware of that term query is not analyzed ie it uses the 4123-0000 as it is and tried to find in the inverted index, which is not available hence you don't get any result.
Solution, simply replace _id to _id.keyword to get the search result.
Related
While fetching records using IN clause, the below query is returning more than expected values.
List`<Object>` findAllByCameraIdIn(List`<String>` cameraIds);
I have records associated with two cameras in elastic db - [uk05-smoking-shelter-carpark, uk05-stairway-in]
If List cameraIds = ["uk05-smoking-shelter-carpark"], it's giving values associated with camera -> uk05-stairway-in also (both cameras), Any idea/suggestion why this is happing ?
Even if I'm making db call to filter the records, expected result should have been only 7, corresponding to uk05-smoking-shelter-carpark but it is giving me results for uk05-stairway-in also.
My Findings
When I replaced the - with _ for few records i.e., (uk05-smoking-shelter-carpark with uk05_smoking_shelter_carpark) in the cameraId, the query is working fine.
I believe the query starts searching for all the records with the given value but once it enconters - , it's ignoring all the letters after the - . Any suggestion or insights why it is like this?
Elasticsearch uses a standard analyzer if no analyzer is specified. Assuming cameraId field is of text type, so uk05-smoking-shelter-carpark will get tokenized into
{
"tokens": [
{
"token": "uk05",
"start_offset": 0,
"end_offset": 4,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "smoking",
"start_offset": 5,
"end_offset": 12,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "shelter",
"start_offset": 13,
"end_offset": 20,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "carpark",
"start_offset": 21,
"end_offset": 28,
"type": "<ALPHANUM>",
"position": 3
}
]
}
So when searching for "uk05-smoking-shelter-carpark" will match all the documents that have any of the tokens shown above.
If you want to return the documents that match exactly with the search query then you need to change the data type of cameraId to keyword type
OR if you have not explicitly defined any mapping then you need to add .keyword to the cameraId field. This uses the keyword analyzer instead of the standard analyzer (notice the ".keyword" after cameraId field).
It is better to use a term query if you are searching for an exact term match.
Search Query using match query
{
"query":{
"match":{
"cameraId.keyword":"uk05_smoking_shelter_carpark"
}
}
}
Search Query using term query
{
"query":{
"term":{
"cameraId.keyword":"uk05_smoking_shelter_carpark"
}
}
}
When you replace - with _, i.e "uk05_smoking_shelter_carpark", this will get tokenized into
GET /_analyze
{
"analyzer" : "standard",
"text" : "uk05_smoking_shelter_carpark"
}
Token generated will be
{
"tokens": [
{
"token": "uk05_smoking_shelter_carpark",
"start_offset": 0,
"end_offset": 28,
"type": "<ALPHANUM>",
"position": 0
}
]
}
In this case, the search query will only return the documents that match uk05_smoking_shelter_carpark
I have an index where some entries are like
{
"name" : " Stefan Drumm"
}
...
{
"name" : "Dr. med. Elisabeth Bauer"
}
The mapping of the name field is
{
"name": {
"type": "text",
"analyzer": "index_name_analyzer",
"search_analyzer": "search_cross_fields_analyzer"
}
}
When I use the below query
GET my_index/_search
{"size":10,"query":
{"bool":
{"must":
[{"match":{"name":{"query":"Stefan Drumm","operator":"AND"}}}]
,"boost":1.0}},
"min_score":0.0}
It returns the first document.
But when I try to get the second document using the query below
GET my_index/_search
{"size":10,"query":
{"bool":
{"must":
[{"match":{"name":{"query":"Dr. med. Elisabeth Bauer","operator":"AND"}}}]
,"boost":1.0}},
"min_score":0.0}
it is not returning anything.
Things I can't do
can't change the index
can't use the term query.
change the operator to 'OR', because in that case it will return multiple entries, which I don't want.
What I am doing wrong and how can I achieve this by modifying the query?
You have configured different analyzers for indexing and searching (index_name_analyzer and search_cross_fields_analyzer). If these analyzers process the input Dr. med. Elisabeth Bauer in an incompatible way, the search isn't going to match. This is described in more detail in Index and search analysis, as well as in Controlling Analysis.
You don't provide the definition of these two analyzers, so it's hard to guess from your question what they are doing. Depending on the analyzers, it may be possible to preprocess your query string (e.g. by removing .) before executing the search so that the search will match.
You can investigate how analysis affects your search by using the _analyze API, as described in Testing analyzers. For your example, the commands
GET my_index/_analyze
{
"analyzer": "index_name_analyzer",
"text": "Dr. med. Elisabeth Bauer"
}
and
GET my_index/_analyze
{
"analyzer": "search_cross_fields_analyzer",
"text": "Dr. med. Elisabeth Bauer"
}
should show you how the two analyzers configured for your index treats the target string, which might provide you with a clue about what's wrong. The response will be something like
{
"tokens": [
{
"token": "dr",
"start_offset": 0,
"end_offset": 2,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "med",
"start_offset": 4,
"end_offset": 7,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "elisabeth",
"start_offset": 9,
"end_offset": 18,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "bauer",
"start_offset": 19,
"end_offset": 24,
"type": "<ALPHANUM>",
"position": 3
}
]
}
For the example output above, the analyzer has split the input into one token per word, lowercased each word, and discarded all punctuation.
My guess would be that index_name_analyzer preserves punctuation, while search_cross_fields_analyzer discards it, so that the tokens won't match. If this is the case, and you can't change the index configuration (as you state in your question), one other option would be to specify a different analyzer when running the query:
GET my_index/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "Dr. med. Elisabeth Bauer",
"operator": "AND",
"analyzer": "index_name_analyzer"
}
}
}
],
"boost": 1
}
},
"min_score": 0
}
In the query above, the analyzer parameter has been set to override the search analysis to use the same analyzer (index_name_analyzer) as the one used when indexing. What analyzer might make sense to use depends on your setup. Ideally, you should configure the analyzers to align so that you don't have to override at search time, but it sounds like you are not living in an ideal world.
I am running a terms query in elastic search version 7.2, when I have 4 characters in my query, it works and if I add or remove any characters it's not working.
Working query:
{
"query": {
"bool": {
"must": [{
"terms": {
"GEP_PN": ["6207"]
}
},
{
"match": {
"GEP_MN.keyword": "SKF"
}
}
]
}
}
}
Result :
Query that is failing :
Its not failing, its not finding the result for your search-term, please note that terms query are not analyzed as mention in the docs.
Returns documents that contain one or more exact terms in a provided
field.
Please provide the mapping of your index and if its using the text field and you are not using custom-analyzer it will use standard analyzer which would split tokens on -, hence your terms query is not matching the tokens present in inverted index.
Please see the analyze API o/p for your search-term, which explains the probable root-cause.
{
"text" : "6207-R"
}
Tokens
{
"tokens": [
{
"token": "6207",
"start_offset": 0,
"end_offset": 4,
"type": "<NUM>",
"position": 0
},
{
"token": "r",
"start_offset": 5,
"end_offset": 6,
"type": "<ALPHANUM>",
"position": 1
}
]
}
Using searchkick and see that a search for "animals" is returning results for "anime" because of their stem "anim". Does anyone have any suggestions on how to improve these results?
I see the in docs you can do something like
exclude_queries = {
"animals" => ["anime"],
}
Product.search query, exclude: exclude_queries[query]
But it seems like a lot of work to keep a running list for all of the bad ones like this.
Wondering if I need to change the stemmer?
Looks like instead of standard analyzer which doesn't stem the tokens somehow you are using the english analyzer which uses the stemmer, causing the stemmed tokens as shown below:
POST http://{{hostname}}:{{port}}/{{index-name}}/_analyze
{
"text" : "animals",
"analyzer" : "english"
}
{
"tokens": [
{
"token": "anim",
"start_offset": 0,
"end_offset": 5,
"type": "<ALPHANUM>",
"position": 0
}
]
}
The standard analyzer(Default on text field) generates non-stemmed tokens
{
"text" : "animals",
"analyzer" : "standard"
}
{
"tokens": [
{
"token": "animals",
"start_offset": 0,
"end_offset": 7,
"type": "<ALPHANUM>",
"position": 0
}
]
}
If you use standard analyzer you will not the stemmed form but then running will not produce run stemmed form to token and searching for running will not produce results for run, runs etc. Its a trade-off and according to your business requirements you need to choose and modify the analyzers.
I might try something like this. https://www.elastic.co/guide/en/elasticsearch/reference/master/mixing-exact-search-with-stemming.html
Update
Ankane at searchkick gem was kind enough to add a feature to help with this. As of 4.4.1 you can do this.
class Product < ApplicationRecord
searchkick stemmer_override: ["anime => anime"]
end
This will prevent "anime" from being stemmed to "anim". So it won't show up in the "animals" search results.
I can handle/extract the text from my PDF-Files, I don't know quite know if I am going the right way about how to store my content in Elasticsearch.
My PDF-Texts are mostly German - with letters like "ö", "ä", etc.
In order to store EVERY character of the content, I "escape" necessary characters and encode them properly to JSON so I can store them.
For example:
I want to store the following (PDF) text:
Öffentliche Verkehrsmittel. TestPath: C:\Windows\explorer.exe
I convert and upload it to Elasticsearch like this:
{"text":"\\u00D6ffentliche Verkehrsmittel. TestPath: C:\\\\Windows\\\\explorer.exe"}
My question is: Is this the right way to store documents like this?
Elasticsearch comes up with a wide range of inbuilt language-specific analyzer and if you are creating the text field and storing your data, by default standard analyzer is used. which you change like below:
{
"mappings": {
"properties": {
"title.german" :{
"type" :"text",
"analyzer" : "german"
}
}
}
}
You can also check the tokens generated by language analyzer in your case german using analyze API
{
"text" : "Öffentliche",
"analyzer" : "german"
}
And generated token
{
"tokens": [
{
"token": "offentlich",
"start_offset": 0,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 0
}
]
}
Tokens for Ö
{
"text" : "Ö",
"analyzer" : "german"
}
{
"tokens": [
{
"token": "o",
"start_offset": 0,
"end_offset": 1,
"type": "<ALPHANUM>",
"position": 0
}
]
}
Note:- it converted it to plain text, so now whether you search for Ö or ö it will come in the search result, as the same analyzer is applied at query time if you use the match query.