I am trying to create a elastic search query for one of my Library projects. I am trying to use regex but I do not get any result. I am trying to enter the following regex query.
GET /manifestation_v1/_search
{
"query": {
"regexp": {
"bibliographicInformation.title": {
"value": "python access*"
}
}
}
}
access is a wildcard so i want to create a query which takes as python access* not python access
Can anyone help me out who already has some experience in kibana?
you can try wildcard query
{
"query": {
"wildcard": {
"bibliographicInformation.title": {
"value": "saba safavi*"
}
}
}
}
You need to run regex query on keyword field and use .* instead of *
ex.
GET /manifestation_v1/_search
{
"query": {
"regexp": {
"bibliographicInformation.title": {
"value": "python access.*"
}
}
}
}
Regex is slower , you can also try prefix query
{
"query": {
"prefix": {
"bibliographicInformation.title": {
"value": "python access"
}
}
}
}
If field is of nested type then you need to use nested query
Update
For "text" type , field is stored as tokens. i.e
"python access" is stored as ["python","access"]. You query is trying to match "phython access*" with each of these tokens individually. You need to query against keyword field , which is stored as single value "phython access".
Related
We are using elastic version 7.10.2. I want to compare two fields from a same document.Scripting is disabled in my organization.
Kindly help in building below query without using script.
Here my query is : nickname is null or nickname is empty or nickname is equal to firstname.
Hard part is how to build query to get the records which have nickname is equal to firstname
Relevant script query to be converted to normal query :
{
"query": {
"bool": {
"must": [{
"script": {
"script": {
"inline": "doc['nickname.keyword'].value==null || doc['nickname.keyword'].value =='' || doc['nickname.keyword'].value == doc['firstname.keyword'].value",
"lang": "painless",
}
}
}]
}
}
}
I see you are already comparing the nickname.keyword to your firstname also mentioned this is the hard part, for this why you need a script, you can simply use the search query on this keyword field and get the result you want.
You can use below term query for it.
{
"query": {
"term": {
"nickname.keyword": {
"value": "your-nickname", // provide your nickname as value
}
}
}
}
I am using elasticsearch 7 and I am trying to build up a search request in this way:
{
"query": {
"prefix": {
"document": {
"value": "/home/myfolder"
}
}
}
}
in order to find all folders starting with /home/myfolder ("document" element is stored like a path "/home/myfolder/file.txt". I am trying many ways but I didn't found any way to escape properly "/" character. In other links, people suggested to use "\/home/myfolder" or "/home/myfolder" but it does not work.
many thanks for any help
Since you are trying to match with the / use .keyword as below.
{
"query": {
"prefix": {
"document.keyword": {
"value": "/home/myfolder"
}
}
}
}
This is because when you dont use keyword, you are trying to match against an analyzed field and by default it removes the /.
Try running this and see how it breaks at each slash (/) to create the inverted index.
POST /_analyze
{
"text" :"/home/myfolder/document.txt"
}
I would like to do the Elasticsearch equivalent of the following SQL statement:
SELECT * FROM Users WHERE UserName NOT LIKE '%something%'
I don't care about efficiency or scoring... This only gets executed on occasion. I am using request body syntax.
Use a normal wildcard query, and negate it using a bool must_not query.
GET Users/_search
{
"query": {
"bool": {
"must_not": [{
"wildcard": {
"UserName": {
"value": "*something*"
}
}
}]
}
}
}
I'm not sure if your Users are your index in you Elastic - but this is the main idea anyway:
You could go with the regexp query by using Complement - "~" for negation:
GET Users/_search
{
"query": {
"regexp":{
"UserName": {
"value": ".*~(something).*"
}
}
}
}
For more useful reference, you can check here
P.S:
You will not get the best performance but it will do the job
My data has a field localities which is an array of strings.
"localities": [
"Mayur Vihar Phase 1",
"Paschim Vihar",
"Rohini",
"",
"Laxmi Nagar",
"Vasant Vihar",
"Dwarka",
"Karol Bagh",
"Inderlok" ]
What query should I write to filter the documents by a specific locality such as "Rohini"?
A simple match query will be enough (if you don't know the mapping of your localities field).
POST <your index>/_search
{
"query": {
"match": {
"localities": "Rohini"
}
}
}
If the localities field is set as a string type and index as not_analyzed, the best way to query this is to use a term filter, wrapped in a filtered query (you can't use directly filters) :
POST <your index>/_search
{
"query": {
"filtered": {
"filter": {
"term": {
"localities": "Rohini"
}
}
}
}
}
If you doesn't need the score, the second solution is the way to go as filters doesn't compute score, are faster and cached.
Check the documentation for information about analysis which is a very important subject in ElasticSearch, heavily influencing the way you query.
POST /_search
{
"query": {
"match": {
"localities": "Rohini"
}
}
}
Or you can simply query:
GET /_search?q=localities:Rohini
This query is returning fine only one item "steve_jobs".
{
"query": {
"constant_score": {
"filter": {
"term": {
"name":"steve_jobs"
}
}
}
}
}
So, now I want to get all people with name prefix steve_. So I try this:
{
"query": {
"constant_score": {
"filter": {
"term": {
"name": "steve_"
}
}
}
}
}
This is returning nothing. Why?
I'm confused about when to use term query / term filter / terms filter / querystring query.
What you need is Prefix Query.
If you are indexing your document like so:
POST /testing_nested_query/class/
{
"name": "my name is steve_jobs"
}
And you are using the default analyzer, then the problem is that the term steve_jobs will be indexed as one term. So your Term Query will never be able to find any docs matching the term steve as there is no term like in the index. Prefix Query helps you solve your problem by searching for a prefix in all the indexed terms.
You can solve the same problem by making your custom analyzers (read this and this) so that steve_jobs is stored as steve and jobs.