My index data is
{
"full_name":"Edwin Powell Hubble",
"job": "IT"
}
{
"full_name":"John Edwin",
"job": "Accountant"
}
{
"first_name":"Eric Petterson",
"job": "Accountant"
}
I am not sure if anyone could help me to build a query to get data that have full_name as Edwin. It tried with term query seem not really work.
Since full_name can be of any length and should be analyzed when indexed, I believe you have mapped the attribute as of type text.
For the same reason I also believe you will have requirements to return results as 'Edwin Powell Hubble' and 'John Edwin' when searched with 'Edwin' and return 'Edwin Powell Hubble' when search with 'Edwin Pow'
match_phrase_prefix should help you with these use cases.
GET /_search
{
"query": {
"match_phrase_prefix": {
"full_name": "Edwin"
}
}
}
You can use the match query to get data that have full_name as Edwin
{
"query": {
"match": {
"full_name": "edwin"
}
}
}
Term query works on exact text match, so you will not get any document for Edwin since there is no data in your sample index data that have a match for full_name as Edwin
Related
Below is the query part in Elastic GET API via command line inside openshift pod , i get all the match query as well as unmatch element in the fetch of 2000 documents. how can i limit to only the match element.
i want to specifically get {\"kubernetes.container_name\":\"xyz\"}} only.
any suggestions will be appreciated
-d ' {\"query\": { \"bool\" :{\"must\" :{\"match\" :{\"kubernetes.container_name\":\"xyz\"}},\"filter\" : {\"range\": {\"#timestamp\": {\"gte\": \"now-2m\",\"lt\": \"now-1m\"}}}}},\"_source\":[\"#timestamp\",\"message\",\"kubernetes.container_name\"],\"size\":2000}'"
For exact matches there are two things you would need to do:
Make use of Term Queries
Ensure that the field is of type keyword datatype.
Text datatype goes through Analysis phase.
For e.g. if you data is This is a beautiful day, during ingestion, text datatype would break down the words into tokens, lowercase them [this, is, a, beautiful, day] and then add them to the inverted index. This process happens via Standard Analyzer which is the default analyzer applied on text field.
So now when you query, it would again apply the analyzer at querying time and would search if the words are present in the respective documents. As a result you see documents even without exact match appearing.
In order to do an exact match, you would need to make use of keyword fields as it does not goes through the analysis phase.
What I'd suggest is to create a keyword sibling field for text field that you have in below manner and then re-ingest all the data:
Mapping:
PUT my_sample_index
{
"mappings": {
"properties": {
"kubernetes":{
"type": "object",
"properties": {
"container_name": {
"type": "text",
"fields":{ <--- Note this
"keyword":{ <--- This is container_name.keyword field
"type": "keyword"
}
}
}
}
}
}
}
}
Note that I'm assuming you are making use of object type.
Request Query:
POST my_sample_index
{
"query":{
"bool": {
"must": [
{
"term": {
"kubernetes.container_name.keyword": {
"value": "xyz"
}
}
}
]
}
}
}
Hope this helps!
I'm new to ElasticSearch. It seems pretty awesome, but I'm extremely confused by the JSON-based query language.
I am going to use ES as a document store. I am interested in making queries such "get all documents where age = 25", or "get all documents where name = 'john' and city = 'london'". However I have yet to understand how this can be done.
I can do this:
{
"query": {
"match": {
"age": "25"
}
}
}
But is this what I'm looking for? I think this would also return documents where age is "25 apples".
Please explain how one can issue such simpe queries against ES.
For age matching you can use term Query. Term Query looks for exact match.
{
"query": {
"term": {
"age": "25"
}
}
}
If you're afraid of the query DSL, you might be less afraid to use the query string mini-language (close to the Lucene query language) passed directly in the URI with the q= query string parameter, it might be a bit simpler to learn and event though it has some limitations, it allows you to go a long way.
For instance, in order to query all documents with age = 25, you 'd do it like this:
curl -XGET 'localhost:9200/_search?q=age:25'
For all documents with age between 25 and 30:
curl -XGET 'localhost:9200/_search?q=age:[25 TO 30]'
For all documents with age between 25 and 30 and the country US:
curl -XGET 'localhost:9200/_search?q=age:[25 TO 30] AND country:us'
To get all documents where (name = john and city = london).You can use following command:
GET /bank/account/_search?q=firstname:Rodriquez%20AND%20age:31
Or,You can also try Filters:
GET /demo/post/_search?pretty=true
{
"query": {
"filtered": {
"filter": {
"and": [
{
"term": {
"name": "john"
}
},
{
"term": {
"city": "london"
}
}
]
}
}
}
}
I have a question about the Elasticsearch DSL.
I would like to do a full text search, but scope the searchable records to a specific array of database ids.
In SQL world, it would be the functional equivalent of WHERE id IN(1, 2, 3, 4).
I've been researching, but I find the Elasticsearch query DSL documentation a little cryptic and devoid of useful examples. Can anyone point me in the right direction?
Here is an example query which might work for you. This assumes that the _all field is enabled on your index (which is the default). It will do a full text search across all the fields in your index. Additionally, with the added ids filter, the query will exclude any document whose id is not in the given array.
{
"bool": {
"must": {
"match": {
"_all": "your search text"
}
},
"filter": {
"ids": {
"values": ["1","2","3","4"]
}
}
}
}
Hope this helps!
As discussed by Ali Beyad, ids field in the query can do that for you. Just to complement his answer, I am giving an working example. In case anyone in the future needs it.
GET index_name/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"field": "your query"
}
},
{
"ids" : {
"values" : ["0aRM6ngBFlDmSSLpu_J4", "0qRM6ngBFlDmSSLpu_J4"]
}
}
]
}
}
}
You can create a bool query that contains an Ids query in a MUST clause:
https://www.elastic.co/guide/en/elasticsearch/reference/2.0/query-dsl-ids-query.html
By using a MUST clause in a bool query, your search will be further limited by the Ids you specify. I'm assuming here by Ids you mean the _id value for your documents.
According to es doc, you can
Returns documents based on their IDs.
GET /_search
{
"query": {
"ids" : {
"values" : ["1", "4", "100"]
}
}
}
With elasticaBundle symfony 5.2
$query = new Query();
$IdsQuery = new Query\Ids();
$IdsQuery->setIds($id);
$query->setQuery($IdsQuery);
$this->finder->find($query, $limit);
You have two options.
The ids query:
GET index/_search
{
"query": {
"ids": {
"values": ["1, 2, 3"]
}
}
}
or
The terms query:
GET index/_search
{
"query": {
"terms": {
"yourNonPrimaryIdField": ["1", "2","3"]
}
}
}
The ids query targets the document's internal _id field (= the primary ID). But it often happens that documents contain secondary (and more) IDs which you'd target thru the terms query.
Note that if your secondary IDs contain uppercase chars and you don't set their field's mapping to keyword, they'll be normalized (and lowercased) and the terms query will appear broken because it only works with exact matches. More on this here: Only getting results when elasticsearch is case sensitive
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.