I am getting results from following Elastic Search query:
"query": {
"bool": {
"should": [
{"match_phrase_prefix": {"title": keyword}},
{"match_phrase_prefix": {"second_title": keyword}}
]
}
}
The result is good, but I want to change the order of the result so that the results with matching title comes top.
Any help would be appreciated!!!
I was able to reproduce the issue with sample data and My solution is using a query time boost, as index time boost is deprecated from the Major version of ES 5.
Also, I've created sample data in such a manner, that without boost both the sample data will have a same score, hence there is no guarantee that one which has match comes first in the search result, this should help you understand it better.
1. Index Mapping
{
"mappings": {
"properties": {
"title": {
"type": "text"
},
"second_title" :{
"type" :"text"
}
}
}
}
2. Index Sample docs
a)
{
"title": "opster",
"second_title" : "Dimitry"
}
b)
{
"title": "Dimitry",
"second_title" : "opster"
}
Search query
{
"query": {
"bool": {
"should": [
{
"match_phrase_prefix": {
"title": {
"query" : "dimitry",
"boost" : 2.0 <-- Notice the boost in `title` field
}
}
},
{
"match_phrase_prefix": {
"second_title": {
"query" : "dimitry"
}
}
}
]
}
}
}
Output
"hits": [
{
"_index": "60454337",
"_type": "_doc",
"_id": "1",
"_score": 1.3862944,
"_source": {
"title": "Dimitry", <-- Dimitry in title field has doube score
"second_title": "opster"
}
},
{
"_index": "60454337",
"_type": "_doc",
"_id": "2",
"_score": 0.6931472,
"_source": {
"title": "opster",
"second_title": "Dimitry"
}
}
]
Let me know if you have any doubt understanding it.
Related
I want to perform a search query on different indexes with different search queries and unify the results.
I know there is a multi-target syntax, which allows me to perform specific query over multiple indexes.
What I want is different query for each index and then perform something like UNION (SQL).
Is there a way to achieve that?
You can use the _index metadata field. This will help you to query on multiple indexes with different queries
Adding a working example with index data, search query and search result
Index Data
POST /index1/_doc/1
{
"name":"foo"
}
POST /index2/_doc/1
{
"name":"bar"
}
Search Query:
{
"query": {
"bool": {
"should": [
{
"bool": {
"must": [
{
"match": {
"name": "foo"
}
},
{
"term": {
"_index": "index1"
}
}
]
}
},
{
"bool": {
"must": [
{
"match": {
"name": "bar"
}
},
{
"term": {
"_index": "index2"
}
}
]
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "index1",
"_type": "_doc",
"_id": "1",
"_score": 1.287682,
"_source": {
"name": "foo"
}
},
{
"_index": "index2",
"_type": "_doc",
"_id": "1",
"_score": 1.287682,
"_source": {
"name": "bar"
}
}
]
I have a search index of filenames containing over 100,000 entries that share about 500 unique variations of the main filename field. I have recently made some modifications to certain filename values that are being generated from my data. I was wondering if there is a way to link certain queries to return an exact match. In the following query:
"query": {
"bool": {
"must": [
{
"match": {
"filename": "foo-bar"
}
}
],
}
}
how would it be possible to modify the index and associate the results so that above query will also match results foo-bar-baz, but not foo-bar-foo or any other variation?
Thanks in advance for your help
You can use a term query instead of a match query. Perfect to use on a keyword:
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html
Adding a working example with index data and search query. (Using the default mapping)
Index Data:
{
"fileName": "foo-bar"
}
{
"fileName": "foo-bar-baz"
}
{
"fileName": "foo-bar-foo"
}
Search Query:
{
"query": {
"bool": {
"should": [
{
"match": {
"fileName.keyword": "foo-bar"
}
},
{
"match": {
"fileName.keyword": "foo-bar-baz"
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "test",
"_type": "_doc",
"_id": "1",
"_score": 0.9808291,
"_source": {
"fileName": "foo-bar"
}
},
{
"_index": "test",
"_type": "_doc",
"_id": "2",
"_score": 0.9808291,
"_source": {
"fileName": "foo-bar-baz"
}
}
]
Im using Elasticsearch 7.1 and i have defined the format in my index mappings as below :
"ManufacturerDate": {
"type": "date",
"format": "yyyy-MM-dd'T'HH:mm:ss.SSS'ZZ'|| yyyy-MM-dd'T'HH:mm:ss.SSS'ZZ'||yyyy-MM-dd'T'HH:mm:ss.SSSXXX"
}
But im getting date parsing error when searching against the date - "2020-07-09T00:12:22.011-00:00". The format yyyy-MM-dd'T'HH:mm:ss.SSSXXX is already defined as one of the accepted formats.
The error is
Failed to parse date field [2020-07-09T00:12:22.011-00:00] with format [yyyy-MM-dd'T'HH:mm:ss.SSS'ZZ'||yyyy-MM-dd'T'HH:mm:ss.SSS'ZZ'||yyyy-MM-dd'T'HH:mm:ss.SSSXXX]:
Can anyone please help?
Adding Working example with mapping and search query.
To know more about the Date data type refer to this documentation.
The search query mentioned below is for finding exact date type values.
To Return documents that contain terms within a provided range refer this
Mapping :
{
"mappings": {
"properties": {
"ManufacturerDate": {
"type": "date",
"format": "yyyy-MM-dd'T'HH:mm:ss.SSS'ZZ'||yyyy-MM-dd'T'HH:mm:ss.SSSXXX"
}
}
}
}
Search Query:
{
"query": {
"term": {
"ManufacturerDate": {
"value": "2020-07-09T00:12:22.011-00:00"
}
}
}
}'
Search Result:
"hits": [
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"ManufacturerDate": "2020-07-09T00:12:22.011-00:00"
}
}
]
Update 1:
You can even use Constant score query
Search query:
{
"query": {
"constant_score": {
"filter": {
"term": {
"ManufacturerDate": "2020-07-09T00:12:22.011-00:00"
}
},
"boost": 1.2
}
}
}
Search Result:
"hits": [
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_score": 1.2,
"_source": {
"ManufacturerDate": "2020-07-09T00:12:22.011-00:00"
}
}
]
Update 2: By changing the order of patterns the query works (Using ES version 7.2)
Mapping:
{
"mappings": {
"properties": {
"ManufacturerDate": {
"type": "date",
"format": "yyyy-MM-dd'T'HH:mm:ss.SSSXXX||yyyy-MM-dd'T'HH:mm:ss.SSS'ZZ'||yyyy-MM-dd'T'HH:mm:ss.SSS"
}
}
}
}
Index data:
{
"ManufacturerDate": "2020-07-09T00:12:22.011-00:00"
}
Search Query:
{
"query": {
"constant_score": {
"filter": {
"term": {
"ManufacturerDate": "2020-07-09T00:12:22.011-00:00"
}
},
"boost": 1.2
}
}
}
Search Result :
"hits": [
{
"_index": "my_index5",
"_type": "_doc",
"_id": "1",
"_score": 1.2,
"_source": {
"ManufacturerDate": "2020-07-09T00:12:22.011-00:00"
}
}
]
I have a fuzzy query with customized AUTO:10,20 fuzziness value.
{
"query": {
"match": {
"name": {
"query": "nike",
"fuzziness": "AUTO:10,20"
}
}
}
}
How to convert it to a query_string query? I tried nike~AUTO:10,20 but it is not working.
It's possible with query_strng as well, let me show using the same example as OP provided, both match_query provided by OP matches and query_string fetches the same document with same score.
And according to this and this ES docs, Elasticsearch supports AUTO:10,20 format, which is shown in my example as well.
Also
Index mapping
{
"mappings": {
"properties": {
"name": {
"type": "text"
}
}
}
}
Index some doc
{
"name" : "nike"
}
Search query using match with fuzziness
{
"query": {
"match": {
"name": {
"query": "nike",
"fuzziness": "AUTO:10,20"
}
}
}
}
And result
"hits": [
{
"_index": "so-query",
"_type": "_doc",
"_id": "1",
"_score": 0.9808292,
"_source": {
"name": "nike"
}
}
]
Query_string with fuzziness
{
"query": {
"query_string": {
"fields": ["name"],
"query": "nike",
"fuzziness": "AUTO:10,20"
}
}
}
And result
"hits": [
{
"_index": "so-query",
"_type": "_doc",
"_id": "1",
"_score": 0.9808292,
"_source": {
"name": "nike"
}
}
]
Lucene syntax only allows you to specify "fuzziness" with the tilde symbol "~", optionally followed by 0, 1 or 2 to indicate the edit distance.
Elasticsearch Query DSL supports a configurable special value for AUTO which then is used to build the proper Lucene query.
You would need to implement that logic on your application side, by evaluating the desired edit distance based on the length of your search term and then use <searchTerm>~<editDistance> in your query_string-query.
I'm trying to filter my elasticsearch index by specific fields, the "country" field to be exact. However, I keep getting loads of other results (other countries) back that are not exact.
Please could someone point me in the right direction.
I've tried the following searches:
GET http://127.0.0.1:9200/decision/council/_search
{
"query": {
"filtered": {
"filter": {
"term": {
"country": "Algeria"
}
}
}
}
}
Here is an example document:
{
"_index": "decision",
"_id": "54290140ec882c6dac5ae9dd",
"_score": 1,
"_type": "council",
"_source": {
"document": "DEV DOCUMENT"
"id": "54290140ec882c6dac5ae9dd",
"date_updated": 1396448966,
"pdf_file": null,
"reported": true,
"date_submitted": 1375894031,
"doc_file": null,
"country": "Algeria"
}
}
You can use the match_phrase query instead
POST http://127.0.0.1:9200/decision/council/_search
{
"query" : {
"match_phrase" : { "country" : "Algeria"}
}
}