I want to search text inside fields.
I tried to fix my problem from this documentation
One of my index contains items which structure is the following:
{
url: "https://exampleurl.com"
username: "some_username"
}
Here is my querys:
"query": {
"multi_match": {
"query": keyword,
"type": "phrase",
"fields": [ "username", "url" ]
}
}
Also bool query:
"query": {
"bool": {
"must": {
"multi_match": {
"query": keyword,
"type": "phrase",
"fields": [ "username", "url" ]
}
},
}
}
"query": {
"bool": {
"must": [{
"match": {
"username": keyword,
}
}, {
"match": {
"url": keyword
}
}]
}
}
But result is a empty array
please try the below query.
Create Index
PUT test
{
"settings" : {
"number_of_shards" : 1
},
"mappings" : {
"properties" : {
"url" : { "type" : "text" },
"username" : { "type" : "text" }
}
}
}
Insert Document
PUT test/_doc/1
{
"url" : "https://exampleurl.com",
"username" : "Arjun Das"
}
Search
GET test/_search
{
"query": {
"multi_match": {
"query": "http",
"type": "best_fields",
"fields": [ "username", "url" ],
"fuzziness":"2"
}
}
}
Related
I have tried this query:
body = {
"query": {
"bool": {
"must_not": [{
"match": {
"script": "doc['updated_time'].value == doc['created_time'].value"
}
}]
}
}
}
And my indexed document is:
"hits" : [
{
"_index" : "cam_canvas_update",
"_type" : "_doc",
"_id" : "101",
"_score" : 1.0,
"_source" : {
"created_time" : "2021-08-11T13:44:13.282406282Z",
"updated_time" : "2021-08-11T13:44:13.285397500Z",
"engagement" : "Ford",
"tag_set_2" : "Renew",
"tag_set_3" : "Disputed",
"instance_numbers" : 1,
"canvas_name" : "First",
"recordid" : "ford1",
"pf" : "C6000",
"tag_set_1" : "Sally",
"ldos_date" : "7/7/2018",
"architecture" : "webex"
}
]
I want to compare created_time and updated time of all documents
and as output need only updated documents.
Want to write csv only with that updated documents in elasticsearch.
You need to use filter and script in your query like below:
{
"query": {
"bool": {
"filter": [{
"script": {
"script": "doc['updated_time'].value != doc['created_time'].value"
}
}]
}
}
}
If you don't want milliseconds to be compared, you can use this script instead of previous version:
{
"query": {
"bool": {
"filter": [
{
"script": {
"script": {
"inline": "doc['updated_time'].value.getMillis()/1000 != doc['created_time'].value.getMillis()/1000",
"lang": "painless"
}
}
}
]
}
}
}
Please let me know if you have any problem with this query.
I have a elastic search index collection like below,
"_index":"test",
"_type":"abc",
"_source":{
"file_name":"xyz.ex"
"metadata":{
"format":".ex"
"profile":[
{"date_value" : "2018-05-30T00:00:00",
"key_id" : "1",
"type" : "date",
"value" : [ "30-05-2018" ]
},
{
"key_id" : "2",
"type" : "freetext",
"value" : [ "New york" ]
}
}
Now I need to search for document by matching key_id to its value. (key_id is some field whose value is stored in "value")
Ex. For key_id='1'field, if it's value = "30-05-2018" it should match the above document.
I tried mapping this as a nested object, But I am not able to write query to search with 2 or more key_id matching its respective value.
This is how I would do it. You need to AND together via bool/filter (or bool/must) two nested queries for each of the condition pair, since you want to match two different nested elements from the same parent document.
{
"query": {
"bool": {
"filter": [
{
"nested": {
"path": "metadata.profile",
"query": {
"bool": {
"filter": [
{
"term": {
"metadata.profile.f1": "a"
}
},
{
"term": {
"metadata.profile.f2": true
}
}
]
}
}
}
},
{
"nested": {
"path": "metadata.profile",
"query": {
"bool": {
"filter": [
{
"term": {
"metadata.profile.f1": "b"
}
},
{
"term": {
"metadata.profile.f2": false
}
}
]
}
}
}
}
]
}
}
}
I'd like to "translate" a string like:
A AND (C OR B) AND NOT D
into an Elasticsearch query like:
{
"query": {
"bool": {
"must": {
"term": {
"text": "A"
}
},
"must_not": {
"term": {
"text": "D"
}
},
"should": [
{
"term": {
"text": "B"
}
},
{
"term": {
"text": "C"
}
}
],
"minimum_should_match": 1,
"boost": 1
}
}
}
does exists some library which I can use ?
any help appreciated
Thanks!
ok according to:
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-query-string-query.html
I can do query like:
{
"query": {
"query_string" : {
"default_field" : "text",
"query" : (this AND (submitted OR flowers) AND NOT blight"
}
}
}
which works great.
The following JSON structure gives me an error when doing a query:
{
"query": {
"function_score": {
"query": {
"bool": {
"should": [
{
"multi_match": {
"query": "BRCA1",
"fuzziness": "AUTO",
"fields": [
"Long_Name",
"Short_Name",
"Uniprot_ID^10",
"Genes^2",
"Diseases^2",
"Function",
"Domains"
]
}
},
{
"term": {
"Is_Reviewed": true
}
},
{
"term": {
"Has_Function": true
}
}
]
}
}
},
"field_value_factor": {
"field": "Number_Of_Structures"
}
},
"size": 100
}
The error is:
[function_score] malformed query, expected [END_OBJECT] but found [FIELD_NAME]
The bool query on its own works perfectly, but as soon as I use function_score, it stops working. I have tried to follow this example: https://www.elastic.co/guide/en/elasticsearch/guide/master/boosting-by-popularity.html
Any ideas as to what I am doing wrong would be much appreciated!
You must put field_value_factor one level higher, inside function_score:
{
"query": {
"function_score": {
"query": {
"bool": {
"should": [
{
"multi_match": {
"query": "BRCA1",
"fuzziness": "AUTO",
"fields": [
"Long_Name",
"Short_Name",
"Uniprot_ID^10",
"Genes^2",
"Diseases^2",
"Function",
"Domains"
]
}
},
{
"term": {
"Is_Reviewed": true
}
},
{
"term": {
"Has_Function": true
}
}
]
}
},
"field_value_factor": {
"field": "Number_Of_Structures"
}
}
},
"size": 100
}
I was doing search using elastic search using the code:
es.search(index="article-index", fields="url", body={
"query": {
"query_string": {
"query": "keywordstr",
"fields": [
"text",
"title",
"tags",
"domain"
]
}
}
})
Now I want to insert another parameter in the search scoring - "recencyboost".
I was told function_score should solve the problem
res = es.search(index="article-index", fields="url", body={
"query": {
"function_score": {
"functions": {
"DECAY_FUNCTION": {
"recencyboost": {
"origin": "0",
"scale": "20"
}
}
},
"query": {
{
"query_string": {
"query": keywordstr
}
}
},
"score_mode": "multiply"
}
}
})
It gives me error that dictionary {"query_string": {"query": keywordstr}} is not hashable.
1) How can I fix the error?
2) How can I change the decay function such that it give higher weight to higher recency boost?
You appear to have an extra query in your search (giving a total of three), which is giving you an unwanted top-level. You need to remove the top-level query and replace it with function_score as the top level key.
res = es.search(index="article-index", fields="url", body={"function_score": {
"query": {
{ "query_string": {"query": keywordstr} }
},
"functions": {
"DECAY_FUNCTION": {
"recencyboost": {
"origin": "0",
"scale": "20"
}
}
},
"score_mode": "multiply"
})
Note: score_mode defaults to "multiply", as does the unused boost_mode, so it should be unnecessary to supply it.
You cant use dictionary as a key in the dictionary. You are doing this in the following segment of the code:
"query": {
{"query_string": {"query": keywordstr}}
},
Following should work fine
"query": {
"query_string": {"query": keywordstr}
},
use it like this
query: {
function_score: {
query: {
filtered: {
query: {
bool: {
must: [
{
query_string: {
query: shop_search,
fields: [ 'shop_name']
},
boost: 2.0
},
{
query_string: {
query: shop_search,
fields: [ 'shop_name']
},
boost: 3.0
}
]
}
},
filter: {
// { term: { search_city: }}
}
},
exp: {
location: {
origin: { lat: 12.8748964,
lon: 77.6413239
},
scale: "10000m",
offset: "0m",
decay: "0.5"
}
}
// score_mode: "sum"
}