i have tried the multiple field query and it works fine. But I would like to know what other options are generally used to query multiple fields in elasticsearch?
Structured queries with multiple terms, for finding exact values, the same as SQL
https://www.elastic.co/guide/en/elasticsearch/guide/current/_finding_multiple_exact_values.html
"bool" : {
"must" : [
{ "term" : { "tags" : "search" } },
{ "term" : { "tag_count" : 1 } }
]
}
For example, consider following sql query,
SELECT product
FROM products
WHERE (price = 20 OR productID = "XHDK-A-1293-#fJ3")
AND (price != 30)
In these situations, you will need the bool filter. This is a compound filter that accepts other filters as arguments, combining them in various Boolean combinations.
The Query DSL would be,
GET /my_store/products/_search
{
"query" : {
"filtered" : {
"filter" : {
"bool" : {
"should" : [
{ "term" : {"price" : 20}},
{ "term" : {"productID" : "XHDK-A-1293-#fJ3"}}
],
"must_not" : {
"term" : {"price" : 30}
}
}
}
}
}
}
Follow the below link for documentation
https://www.elastic.co/guide/en/elasticsearch/guide/current/combining-filters.html
Related
Raising this question to know the order in which ES executes query clauses (must, should, filter, must_not) that are part of bool query. Sharing the sample query from ES docs -
{ "query": {
"bool" : {
"must" : {
"term" : { "user.id" : "kimchy" }
},
"filter": {
"term" : { "tags" : "production" }
},
"must_not" : {
"range" : {
"age" : { "gte" : 10, "lte" : 20 }
}
},
"should" : [
{ "term" : { "tags" : "env1" } },
{ "term" : { "tags" : "deployed" } }
],
"minimum_should_match" : 1,
"boost" : 1.0
} } }
From the documentation it looks like query-clauses are joined using AND condition. For example, above search DSL's SQL counterpart would look like (rough translation) -
select * from user where user_id like 'kimchy' and tags in ('production') and not (10 <= range <= 20) and tags in ('env1', 'deployed');
I actually wasn't able to find official documentation around this, but did see some texts that ES query-evaluation heavily depends on certain cost approximations. Wondering how to map the ordering to SQL like syntax so, we can develop a clear mental picture when authoring ES queries. It also feels like ordering might have some affect for deeply nested boolean AND OR queries.
I need to search in elasticsearch like
select * from tablename where file.content='xyz' and filePermission.Id='abc'
What query I need to add. Is it possible to give a filter to search query? I have set file.content as a default field.
AND SQL queries can be written as a "must bool query":
{
"query" : {
"bool" : {
"must" : [
{ "match" : { "file.content":"xyz"} },
{ "match" : { "filePermission.Id" : "abc"} }
]
}
}
}
I am trying to find ElasticSearch query equivalent to IN \ NOT in SQL.
I know we can use QueryString query with multiple OR to get the same answer, but that ends up with lot of OR's.
Can anyone share the example?
Similar to what Chris suggested as a comment, the analogous replacement for IN is the terms filter (queries imply scoring, which may improve the returned order).
SELECT * FROM table WHERE id IN (1, 2, 3);
The equivalent Elasticsearch 1.x filter would be:
{
"query" : {
"filtered" : {
"filter" : {
"terms" : {
"id" : [1, 2, 3]
}
}
}
}
}
The equivalent Elasticsearch 2.x+ filter would be:
{
"query" : {
"bool" : {
"filter" : {
"terms" : {
"id" : [1, 2, 3]
}
}
}
}
}
The important takeaway is that the terms filter (and query for that matter) work on exact matches. It is implicitly an or operation, similar to IN.
If you wanted to invert it, you could use the not filter, but I would suggest using the slightly more verbose bool/must_not filter (to get in the habit of also using bool/must and bool).
{
"query" : {
"bool" : {
"must_not" : {
"terms" : {
"id" : [1, 2, 3]
}
}
}
}
}
Overall, the bool compound query syntax is one of the most important filters in Elasticsearch, as are the term (singular) and terms filters (plural, as shown).
1 terms
you can use terms term query in ElasticSearch that will act as IN
terms query is used to check if the value matches any of the provided values from Array.
2 must_not
must_not can be used as NOT in ElasticSearch.
ex.
GET my_index/my_type/_search
{
"query" : {
"bool" : {
"must":[
{
"terms": {
"id" : ["1234","12345","123456"]
}
},
{
"bool" : {
"must_not" : [
{
"match":{
"id" : "123"
}
}
]
}
}
]
}
}
}
exists
Also if it helps you can also use "exists" query to check if the field exists or not.
for ex,
check if the field exists
"exists" : {
"field" : "mobileNumber"
}
check if a field does not exist
"bool":{
"must_not" : [
{
"exists" : {
"field" : "mobileNumber"
}
}
]
}
I saw what you requested.
And I wrote the source code as below.
I hope this helps you solve your problem.
sql query :
select * from tablename where fieldname in ('AA','BB');
elastic search :
{
query :{
bool:{
must:[{
"script": {
"script":{
"inline": "(doc['fieldname'].value.toString().substring(0,2).toUpperCase() in ['AA','BB']) == true"
}
}
}],
should:[],
must_not:[]
}
}
}
I'm new using Elastic Search, and i never used Lucene too.
I build this query:
{
"query" : {
"wildcard" : { "referer" : "*.domain.com*" }
},
"filter" : {
"query" : {
"term" : { "first" : "1" }
}
},
"facets" : {
"site_id" : {
"terms" : {
"field" : "site",
"size" : "70"
}
}
}
}
The wildcard is working great, but the term filter was ignored, what i did wrong?
I need to filter the results with both wildcard and term
Thanks!
Assuming what you are trying to do is applying the filter on the wildcard query results,
you can use a FilteredQuery. However, your case might fit better for a filter.
You use a query filter. Instead of that you may directly use a TermFilter in a FilteredQuery rather than making a filter out of a TermQuery. TermFilter should be faster as it directly uses the TermsEnum.
Note that results of Filters are cached in a FilterCache and Filters are faster because they do not do any scoring of documents. In your case, even though the filter part of the FilteredQuery will work fast, but the wildcard query will be unnecessarily do scoring. You may try to use an AND Filter to club both queryfilter(wildcard query) and term filter instead of a FilteredQuery.
To make just the filter work as required by you, try something like below. (Not tried myself)
{
"filtered" : {
"query" : {
"wildcard" : { "referer" : "*.domain.com*" }
},
"filter" : {
"term" : { "first" : "1" }
}
},
"facets" : {
"site_id" : {
"terms" : {
"field" : "site",
"size" : "70"
}
}
}
}
I would like to have multiple levels of filters to derive a result set using NEST API in Elastic Search. Is it possible to query the results of another filter...? If yes can I do that in multiple levels?
My requirement is like a User is allowed to select / unselect options of various fields.
Example: There are totally 1000 documents in my index 'people'. There may be 3 ListBoxs, 1) City 2) Favourite Food 3) Favourite Colour. If user selects a city it filters out 600 documents. Out of those 600 documents I would like to filter Favourite food, which may result with some 300 documents. Now further I would like to filter with resp. to favourite movie to retrieve 50 documents out of previously derived 300 documents.
You don't need to query within filters to achieve what you want. Just use filtered queries, http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/query-dsl-filtered-query.html, and provide several filters. In your instance I would assume you would do something like this for your first query:
{
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : [
{
"term" : {
"city" : "some city"
}
}
]
}
}
}
You would then return the results from that and display them. You'd then let them select the next filter and do the following:
{
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : [
{
"term" : {
"city" : "some city"
}
},
{
"term" : {
"food" : "some food"
}
}
]
}
}
}
You'd then rinse and repeat for the 3 filter param:
{
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : [
{
"term" : {
"city" : "some city"
}
},
{
"term" : {
"food" : "some food"
}
},
{
"term" : {
"colour" : "some colour"
}
}
]
}
}
}
I haven't tested this, but the principle is sound and will work.