I have a database with entries like
title: This is my awesome title
abstract: A more detailed descriptions of what [...]
I would like to build an Elasticsearch query that matches the above document with, e.g.,
awe detai
In words: A multi_match phrase_prefix query with multiple search terms. (This is intended to be used as a search-as-you-type feature.)
I see how you can combine multi_match and phrase_prefix, but it's unclear to me how to do this for multiple search terms.
Any hints?
Well there is few ways to do that
POST stack/autocomplete/1
{
"title": "This is my awesome title",
"abstract": "A more detailed descriptions of what"
}
Then you can search using query string with star but problem here is that you need to append asterix to query
POST stack/autocomplete/_search
{
"query": {
"query_string": {
"fields": [
"title",
"abstract"
],
"query": "awe* detai*"
}
}
}
If you want to match on user query then you can use like that
POST stack/autocomplete/_search
{
"query": {
"multi_match": {
"fields": [
"title",
"abstract"
],
"query": "awesome tit",
"type": "phrase_prefix"
}
}
}
One more option to consider would be to use nGram with query string so you will not need to modify user query "awe* detai*"
Related
How can we configure elastic search so that it only returns results which matches all the words in the search query. The documents indexed have data having multiple fields and so the words of search query may match different fields of data but all the words must get matched in the result ?
you can query string query feature to search for results
sample search query
GET /_search
{
"query": {
"query_string": {
"query": "(content:this OR name:this) AND (content:that OR name:that)"
}
}
}
In this query content and name is the field name, this is the search criteria
you can build search query similar to that.
I think you're looking for a multi_match query together with and operator. This is the link to docs: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-multi-match-query.html and it seems that cross_fieldsis query type you're looking for. I'd read more on that page, but this is probably what you are looking for:
GET /_search
{
"query": {
"multi_match" : {
"query": "Will Smith",
"type": "cross_fields",
"fields": [ "first_name", "last_name" ],
"operator": "and"
}
}
}
I have a pretty complex query and now I want to boost some documents that fulfill some criteria. I have the following simplified document structure and I try to give some documents a boost based on the id, genre, tag.
{
"id": 123,
"genres": ["ACTION", "DRAMA"],
"tags": ["For kids", "Romantic", "Nature"]
}
What I want to do is for example
id: 123 boost: 5
genres: ACTION boost: 3
tags: Romantic boost: 0.2
and boost all documents that are contained in my query and fit the criteria but I don't want to filter them out. So query clause boosting is not of any help I guess.
Edit: To make if easier to understand what I want to achieve (not sure if it is possible with elasticsearch, no is also a valid answer).
I want to search with a query and get a result set. In this set I want to boost some documents. But I don't want to enlarge the result set or filter it. The boost should be independent from the query.
For example I search for a specific tag and want to boost all documents with category 'ACTION' in the result set. But I don't want all documents with category 'ACTION' in the result set and also I don't want only documents with the specific tag AND category 'ACTION'.
I think you need to have Dynamic boosting during query time.
The first matches the id title with boost and second one matches the 'genders' ACTION.
{
"query": {
"bool": {
"should": [
{
"match": {
"title": {
"query": "id",
"boost": 5
}
}
},
{
"match": {
"content": "Action"
}
}
]
}
}
}
If you want to have multi_match match based on your query:
{
"multi_match" : {
"query": "some query terms here",
"fields": [ "id^5", "genders^3", "tags^0.2" ]
}
}
Note: the ^5 means boost for the title.
Edit:
Maybe you are asking for different types of multi_match queries (at least for ES 5.x) from the ES reference guide:
best_fields
(default) Finds documents which match any field, but uses
the _score from the best field. See best_fields.
most_fields
Finds documents which match any field and combines the _score from
each field. See most_fields.
cross_fields
Treats fields with the same analyzer as though they were one big
field. Looks for each word in any field. See cross_fields.
phrase
Runs a match_phrase query on each field and combines the _score from
each field. See phrase and phrase_prefix.
phrase_prefix
Runs a match_phrase_prefix query on each field and combines the _score
from each field. See phrase and phrase_prefix.
More at: ES 5.4 ElasticSearch reference
I found a solution and it was pretty simple. I use a boosting query. I now just nest the different boosting criteria with and my original query is now the base query.
https://www.elastic.co/guide/en/elasticsearch/reference/2.3/query-dsl-boosting-query.html
For example:
{
"query": {
"boosting": {
"positive": {
"boosting": {
"positive": {
"match": {
"director": "Spielberg"
}
},
"negative": {
"term": {
"genres": "DRAMA"
}
},
"negative_boost": 1.3
}
},
"negative": {
"term": {
"tags": "Romantic"
}
},
"negative_boost": 1.2
}
}
}
{
"title" : "That Uselessly Amazing Title",
"author" : "Someone you have never heard of",
"url" : "http://www.theuselessweb.com",
"summary" : "a collection of useless websites",
"tag" : ["useless","maybe useful"]
}
Say I have a schema that looks like the one shown above. The user asks the application to show something "useless".
How do I write a query that will look through the title, summary, and tags for the word "useless" as a fuzzy search?
From the docs Fuzzy match Query
GET /my_index/my_type/_search
{
"query": {
"multi_match": {
"fields": [ "summary", "title", "tag" ],
"query": "useless",
"fuzziness": "AUTO"
}
}
}
This query works because it's using a multi_match query
Fuzziness works only with the basic match and multi_match queries. It
doesn’t work with phrase matching, common terms, or cross_fields
matches.
Otherwise you'll have to combine several fuzzyqueries inside a bool Query
I'm wanting to find an exact phrase (for instance, "the quick brown fox") across mutliple fields in a document.
Right now, I'm using something like this:
{
"query": {
"filtered": {
"query": {
"multi_match": {
"fields": [
"subject",
"comments"
],
"query": "the quick brown fox"
}
},
"filters": {
"and": [
{
"term": {
"priority": "high"
}
}
...more ands
]
}
}
}
}
Question is, how can I do this correctly. Right now I'm getting the best match first, which tends to be the entire phrase, but I'm getting a load of almost matches too.
If you are using an ElasticSearch cluster with version >= 1.1.0, you could set the mode of your multi-match query to phrase :
...
"query": {
"multi_match": {
"fields": [
"subject",
"comments"
],
"query": "the quick brown fox",
"type": "phrase"
}
...
It will replace the match query generated for each field by a match_phrase one, which will return only the documents containing the full phrase (you can find details in the documentation)
how are you analyzing the subject/comments fields? if you want exact match, you'll need to use the keyword tokenizer for both index/search.
In my ElasticSearch instance, I have two types in a single index. Think of them as "Profile" and "ProfileMetadata". There may be many ProfileMetadata items pointing to a single Profile.
Profile contains basic user info. Say firstname. ProfileMetadata contains metadata for the user, say "Tags".
What I want to be able to do, is run a single query that may look like the following. "Firstname NOT tag". The user would type this into the search bar. It would be a single search bar to search across both types at once.
The two queries are below :
Profile Query
GET _search
{
"query": {
"filtered": {
"query": {
"query_string": {
"fields": [
"PersonalDetail.FirstName",
"PersonalDetail.LastName",
"PersonalDetail.Email"
],
"query": "John Smith NOT tag"
}
}
}
}
}
ProfileMetadata Query
GET _search
{
"query": {
"filtered": {
"query": {
"has_child":
{
"type": "ProfileMetadata",
"query":
{
"query_string": {
"fields": [
"Tags"
],
"query": "John Smith NOT Tag"
}
}
}
}
}
}
}
Is there any way to combine these queries, so that we get all John Smiths without that particular tag. I am using NEST in C#, and at the moment I am taking both of these queries (In NEST form), and using an OR between them, which isn't working as I need it to. So I'm trying to break it down into pure ES form first.
Maybe you could use only the second query, it will return all the matching parent document and then pass a filter on it representing your first query.
In this way you would not have to do a OR between two queries and might gain in performance with only one query+ filter.