My knowledge of Elasticsearch is a bit limited, so what I want to do might not even be possible.
Say I have an ecommerce where I want to be able to freely search on the article names and other fields, but I also want to search on exact article codes aswell. Is this possible in the same query?
Example:
"articlecode": "v400",
"name": "Earplugs for humans"
}
{
"articlecode": "b6655",
"name": "Hammer 400"
}
So can a query be written that combines both multimatch and terms? So that If I search for '400' I get 2 results, but if I search for v400 I just get one result as it is an exact match on the "articlecode"-field.
Below is our current query, where i have an ngram on the "name" field and where I use the term-keyword on the language-field.
{
"size": 10,
"query": {
"bool": {
"must": {
"multi_match": {
"query": "v400",
"fields": [
"articlecode^10",
"name^7"
]
}
},
"filter": {
"term": {
"IdLang.keyword": "sv"
}
}
}
}
}
Have you ever thought of using query_string instead of multi_match? Then you can use wildcard in your search:
{
"size": 10,
"query": {
"bool": {
"must": {
"query_string": {
"query": "*v400",
"fields": [
"articlecode^10",
"name^7"
]
}
}
}
}
}
If you want to search with 400 anywhere in the 2 fields, you can do *400*, or only leading or trailing, depending on what you want.
Related
How do I pass a list as query string to match_phrase query?
This works:
{"match_phrase": {"requestParameters.bucketName": {"query": "xxx"}}},
This does not:
{
"match_phrase": {
"requestParameters.bucketName": {
"query": [
"auditloggingnew2232",
"config-bucket-123",
"web-servers",
"esbck-essnap-1djjegwy9fvyl",
"tempexpo",
]
}
}
}
match_phrase simply does not support multiple values.
You can either use a should query:
GET _search
{
"query": {
"bool": {
"should": [
{
"match_phrase": {
"requestParameters.bucketName": {
"value": "auditloggingnew2232"
}
}
},
{
"match_phrase": {
"requestParameters.bucketName": {
"value": "config-bucket-123"
}
}
}
]
},
...
}
}
or, as #Val pointed out, a terms query:
{
"query": {
"terms": {
"requestParameters.bucketName": [
"auditloggingnew2232",
"config-bucket-123",
"web-servers",
"esbck-essnap-1djjegwy9fvyl",
"tempexpo"
]
}
}
}
that functions like an OR on exact terms.
I'm assuming that 1) the bucket names in question are unique and 2) that you're not looking for partial matches. If that's the case, plus if there are barely any analyzers set on the field bucketName, match_phrase may not even be needed! terms will do just fine. The difference between term and match_phrase queries is nicely explained here.
Some background info: In the bellow example user searched for "HTML CSS". I split each word from the search string and created the SQL query seen bellow.
Now I am trying to make an elastic search query that has the same logic as the following SQL query:
SELECT
title, description
FROM `classes`
WHERE
(`title` LIKE '%html%' AND `title` LIKE '%css%') OR
(description LIKE '%html%' AND description LIKE '%css%')
Currently, half way there but can't seem to get it right yet.
{
"query": {
"bool": {
"must": [
{
"term": {
"title": "html"
}
},
{
"term": {
"title": "css"
}
}
]
}
},
"_source": [
"title"
],
"size": 30
}
Now I need to find how to add follow logic
OR (description LIKE '%html%' AND description LIKE '%css%')
One important point is that I need to only fetch documents that have both words in either title or disruption. I don't want to fetch documents that have only 1 word.
I will update questions as I find more info.
Update: The chosen answer also provides a way to boost scoring based on the field.
Can you try following query. You can use should for making or operation
{
"query": {
"bool": {
"should": [
{
"bool": {
"must": [
{
"match": { // Go for term if your field is analyzed
"title": {
"query": "html css",
"operator": "and",
"boost" : 2
}
}
}
]
}
},
{
"bool": {
"must": [
{
"match": {
"description": {
"query": "html css",
"operator": "and"
}
}
}
]
}
}
],
"minimum_number_should_match": 1
}
},
"_source": [
"title",
"description"
]
}
Hope this helps!!
I feel most appropriate query to be used in this case is multi_match.
multi_match query is convenient way of running the same query on
multiple fields.
So your query can be written as:
GET /_search
{
"_source": ["title", "description"],
"query": {
"multi_match": {
"query": "html css",
"fields": ["title^2", "description"],
"operator":"and"
}
}
}
_source filters the dataset so that only fields mentioned in array
will be displayed in results.
^2 denotes boosting title field with the number 2
operator:and makes sure that all terms in query must be matched
in either fields
From the elasticsearch 5.2 doc:
One option is to use the nested datatype instead of the object datatype.
More details here: https://www.elastic.co/guide/en/elasticsearch/reference/5.2/nested.html
Hope this helps
I have data on ElasticSearch index that looks like this
{
"title": "cubilia",
"people": [
"Ling Deponte",
"Dana Madin",
"Shameka Woodard",
"Bennie Craddock",
"Sandie Bakker"
]
}
Is there a way for me to do a search for all the people whos name starts with
"ling" (should be case insensitive) and get distinct terms properly cased "Ling Deponte" not "ling deponte"?
I am find with changing mappings on the index in any way.
Edit does what I want but is really bad query:
{
"size": 0,
"aggs": {
"person": {
"filter": {
"bool":{
"should":[
{"regexp":{
"people.raw":"(.* )?[lL][iI][nN][gG].*"
}}
]}
},
"aggs": {
"top-colors": {
"terms": {
"size":10,
"field": "people.raw",
"include":
{
"pattern": ["(.* )?[lL][iI][nN][gG].*"]
}
}
}
}
}
}
}
people.raw is not_analyzed
Yes, and you can do it without a regular expression by taking advantage of Elasticsearch's full text capabilities.
GET /test/_search
{
"query": {
"match_phrase": {
"people": "Ling"
}
}
}
Note: This could also be match or match_phrase_prefix in this case. The match_phrase* queries imply an order of the values in the text. match simply looks for any of the values. Since you only have one value, it's pretty much irrelevant.
The problem is that you cannot limit the document responses to just that name because the search API returns documents. With that said, you can use nested documents and get the desired behavior via inner_hits.
You do not want to do wildcard prefixing whenever possible because it simply does not work at scale. To put it in SQL terms, that's like doing a full table scan; you effectively lose the benefit of the inverted index because it has to walk it entirely to find the actual start.
Combining the two should work pretty well though. Here, I use the query to widdle down results to what you are interested in, then I use your inner aggregation to only include based on the value.
{
"size": 0,
"query": {
"match_phrase": {
"people": "Ling"
}
}
"aggs": {
"person": {
"terms": {
"size":10,
"field": "people.raw",
"include": {
"pattern": ["(.* )?[lL][iI][nN][gG].*"]
}
}
}
}
}
Hi Please find the query it may help for your request
GET skills/skill/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"bool": {
"must": [
{
"wildcard": {
"skillNames.raw": "jav*"
}
}
]
}
}
}
}
}
My intention is to find documents starting with the "jav"
I've setup an index that has many types representing user data such as a ShoppingList, Playlist, etc. Each type has an "identity_id" field for the user's unique identifier. I use the following query to search across all types and fields for a user (for a search function in a website):
GET _search
{
"query": {
"filtered": {
"query": {
"match_phrase_prefix": {
"_all": "awesome"
}
},
"filter": {
"match": {
"identity_id": 1
}
}
}
}
}
My questions are:
Is there a way to give a higher score to matches on fields that have "name" in the field name? For example, the ShoppingList type will have a shopping_list_name field, and I want a match on that to be higher than its other fields.
Is the above way of doing a full text search for a particular user (query then filter) the most efficient way? What about creating an index per user?
How about this query that boosts certain fields:
{
"query": {
"function_score": {
"query": {
"multi_match": {
"query": "awesome",
"fields": [
"*_name",
"field*"
]
}
},
"functions": [
{
"weight": 2,
"filter": {
"multi_match": {
"query": "awesome",
"fields": [
"*_name"
]
}
}
},
{
"weight": 1,
"filter": {
"multi_match": {
"query": "awesome",
"fields": [
"field*"
]
}
}
}
]
}
}
}
What the query above does is to boost (weigth: 2) the *_name fields query and not do apply any boosting to fields called field*.
Is the above way of doing a full text search for a particular user (query then filter) the most efficient way? What about creating an index per user?
Regarding this ^ question, that's more complicated and you also need to consider how many users you have, the hardware resources the cluster has, structure of data, queries used etc.
I have a query that works fine when I need the property of a document
to match just one value.
However I also need to be able to search with must with two values.
So if a banana has id 1 and a lemon has id 2 and I search for yellow
I will get both if I have 1 and 2 in the must clause.
But if i have just 1 I will only get the banana.
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [
{ "match":
{ "fruit.color": "yellow" }}
],
"must" : [
{ "match": { "fruit.id" : "1" } }
]
}
}
}
I haven´t found a way to search with two values with must.
is that possible?
If the document "must" be returned only if the id is 1 or 2, that sounds like another should clause. If I'm understanding your question properly, you want documents with either id 1 OR id 2. Additionally, if the color is yellow, give it a higher score.
Here's one way you might achieve what you're looking for:
{
"query": {
"bool": {
"should": {
"match": {
"fruit.color": "yellow"
}
},
"must": {
"bool": {
"should": [
{
"match": {
"fruit.id": "1"
}
},
{
"match": {
"fruit.id": "2"
}
}
]
}
}
}
}
}
Here I put the two match queries in the should clause of a separate bool query. This achieves the OR behavior you are looking for.
Have another look at the Bool Query documentation and take note of the nuances of should. It behaves differently by default depending on whether or not there is a sibling must clause and whether or not the bool query is being executed in filter context.
Another key option that is adjustable and can help you achieve your expected results is the minimum_should_match parameter. Have a look at this documentation page.
Instead of a match query, you could simply try the terms query for ORing between multiple terms.
Match queries are generally used for analyzed fields. For exact matching, you should use term queries
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [
{ "match": { "fruit.color": "yellow" } }
],
"must" : [
{ "terms": { "fruit.id": ["1","2"] } }
]
}
}
}
term or terms query is the perfect way to fetch the exact text or id, using match query result in search inside the id or text
Ex:
id = '4'
id = '44'
Search using match query with id = 4 return both 4 & 44 since it matches 4 in both. This is where terms query come into play.
same search using terms query will return 4 only.
So the accepted is absolutely wrong. Use the #Rahul answer. Just one more thing you need to do, Instead of text you need to analyse the field as a keyword
Example for indexing a field both as a text and keyword (mapping is for flat level for nested change it accordingly).
{
"index_patterns": [ "test" ],
"mappings": {
"kb_mapping_doc": {
"_source": {
"enabled": true
},
"properties": {
"id": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
}
}
}
using #Rahul's answer doesn't worked because you might be analysed as a text.
id - access a text field
id.keyword - access a keyword field
it would be
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [{
"match": {
"color": "yellow"
}
}],
"must": [{
"terms": {
"id.keyword": ["1", "2"]
}
}]
}
}
}
So I would say accepted answer will return falsy results Please use #Rahul's answer with the corresponding mapping.