I have an sql query like
select student_name,roll_number
from
mytable
where
(course = 'CCNA' or course = 'MCSE') and course NOT Like '%network%'
How can i create an equivalent nested boolean query in elasticsearch?
Below query might help you, This query responds with records which course does not contain a "network" keyword and course has a value "ccna" or "mcse".
I have not considered a case sensitiveness feature here and assumed that you have a default mapping.
POST study-doc*/_search
{
"query": {
"bool": {
"must": [
{
"bool": {
"should": [
{
"term": {
"course": {
"value": "ccna"
}
}
},{
"term": {
"course": {
"value": "msce"
}
}
}
]
}},
{
"bool": {
"must": [
{
"wildcard": {
"course.keyword": {
"value": "^((?!network).)*$"
}
}
}
]
}
}
]
}
}
}
Related
I have to fetch data from API which use ElasticSearch.
The conditions of data fetching are firstname should start with given string and company status should be active,
so I have used the below query
"span_first": {
"match": {
"span_term": {
"employee.firstname": "tas"
}
},
"end": 1
}
to match firstname and now i need to filter the data from companyStatus,
"bool": {
"must": [
{
"match": {
"employee.companyStatus": "Active"
}
}
]
}
I'm trying to plug the above bool query into the span_first query
but I have no idea how to do it,
Can someone help me to create the query, sorry if this is a dumb question,
I'm totally new to Elasticsearch.
You can try to use Term Query for filter status and Match Query for search terms.
GET edx_test/_search
{
"query": {
"bool": {
"filter": [
{
"term": {
"employee.companyStatus": "Active"
}
}
],
"must": [
{
"match": {
"employee.firstname": "tas"
}
}
]
}
}
}
Read more:
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html
If both the span_first and match query must be true then you can have both the queries in a must clause like below:
GET test_index/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"employee.companyStatus": "Active"
}
},
{
"span_first": {
"match": {
"span_term": {
"employee.firstname": "tas"
}
},
"end": 1
}
}
]
}
}
}
Thanks for the answer in advance.
I am running a query
SELECT key
FROM records_index
WHERE
(product_nested_field.code = '1234' and product_nested_field.codeset = 'category1' OR product_nested_field.code = '444' and product_nested_field.codeset = 'category1')
AND (role_name IN ('user', 'admin'))
GROUP BY records_uuid
In records_index I have record with two products
[
{codeset: category1, code:444},
{codeset: category2, code:1234}
]
The problem is that query does find a specified record.
such behavior is expected for "type": "object" but why I am getting that result for product_nested_field of type nested?
when I translate SQL to JSON I am getting
{
"bool": {
"must": [
{
"bool": {
"must": [
{
"nested": {
"query": {
"term": {
"product_nested_field.codeset": {
"value": "category1"
}
}
}
}
}
]
}
},
{
"bool": {
"must": [
{
"bool": {
"should": [
{
"nested": {
"query": {
"term": {
"product_nested_field.code": {
"value": "1234"
}
}
}
}
},
{
"nested": {
"query": {
"term": {
"product_nested_field.code": {
"value": "444"
}
}
}
}
}
]
}
}
]
}
}
],
"adjust_pure_negative": true,
"boost": 1.0
}
}
why elastic moves product_nested_field.codeset = 'category1' into separate nested query.
Was wondering if there's a big difference in performance between these two queries which get the same results
{
"query": {
"bool": {
"must": [
"bool": {
"must": [
{
"term": {
"color": "red"
}
},
{
"term": {
"fruit": "strawberry"
}
}
]
}
}
}
}
}
and
{
"query": {
"bool": {
"must": [
{
"term": {
"color": "red"
}
},
{
"term": {
"fruit": "strawberry"
}
}
]
}
}
}
The execution plan of both queries is exactly the same. Add ?explain=true to your URL so you can see how both queries are "explained".
The performance improvement would come from using filter instead of must provided you don't need scoring but only yes/no filtering, i.e.:
{
"query": {
"bool": {
"filter": [ <-- change this
{
"term": {
"color": "red"
}
},
{
"term": {
"fruit": "strawberry"
}
}
]
}
}
}
Is there any library in ElasticSearch or other open-source, that transforms the boolean query into a ElasticSearch query?
With the typical boolean query expressions (AND, OR, "", *, ?) to transform into the "json" query for ElasticSearch and create the "musts", "shoulds", etc...
I mean, for example, to transform this:
(city = 'New York' AND state = 'NY') AND ((businessName='Java' and businessName='Shop') OR (category='Java' and category = 'Shop'))
into this:
{
"query": {
"match_all": {}
},
"filter": {
"bool": {
"must": [
{
"term": {
"city": "New york"
}
},
{
"term": {
"state": "NY"
}
},
{
"bool": {
"should": [
{
"bool": {
"must": [
{
"term": {
"businessName": "Java"
}
},
{
"term": {
"businessName": "Shop"
}
}
]
}
},
{
"bool": {
"must": [
{
"term": {
"category": "Java"
}
},
{
"term": {
"category": "Shop"
}
}
]
}
}
]
}
}
]
}
}
}
There's a Python library called luqum that does exactly what you need.
That library will parse the Lucene expression into an abstract syntax tree. You can then use that tree and generate the Elasticsearch JSON DSL equivalent query.
(I use elasticsearch version 2.3.3)
I am doing a simple match query on a text field but now want to give more weight to documents having true in a given boolean field.
My current query is something like
{
"query": {
"match": {
"title": "QUICK!"
}
}
Is that possible?
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "QUICK!"
}
}
],
"should": [
{
"term": {
"my_boolean_field": {
"value": true
}
}
}
]
}
}
}