I read about match and multiword queries but it seems that I need to do something a bit different.
Let's say I have following query: "this is a test" and I want to find that query in one field called "text". I want to get objects which match some of that query (doesn't matter how many words) but only those objects which query value contains every word of text field.
Example for query: "this is a test". I want get those objects:
obj1: {"text":"this is a test"}
obj2: {"text":"this is a"}
obj3 : { "text" : "is a" }
obj4 : { "text" : "test" }
But if obj has something more in text field it will not be returned for example:
obj5: {"text":"this is a test and something more"}
Is it possible to achieve this using Elasticsearch?
It's kind of a hack, but I was able to get it to work with a script filter:
POST /test_index/_search
{
"query": {
"match": {
"text": "this is a test"
}
},
"filter": {
"script": {
"script": "for(val in doc[\"text\"].values){ if(!(val in terms)){ return false; }}; return true;",
"params": {
"terms": ["this", "is", "a", "test"]
}
}
}
}
I thought there would be a better way to do this, but wasn't immediately able to come up with one. Using scripting can be problematic in production, unless your ES cluster is behind an auth wall of some kind.
Anyway, here's the code I used to test it:
http://sense.qbox.io/gist/3929abc89d71ebf724e6121b1b5ba6da54501088
Related
I have added a document like this to my index
POST /analyzer3/books
{
"title": "The other day I went with my mom to the pool and had a lot of fun"
}
And then I do queries like this
GET /analyzer3/_analyze
{
"analyzer": "english",
"text": "\"The * day I went with my * to the\""
}
And it successfully returns the previously added document.
My idea is to have quotes so that the query becomes exact, but also wildcards that can replace any word. Google has this exact functionality, where you can search queries like this, for instance "I'm * the university" and it will return page results that contain texts like I'm studying in the university right now, etc.
However I want to know if there's another way to do this.
My main concern is that this doesn't seem to work with other languages like Japanese and Chinese. I've tried with many analyzers and tokenizers to no avail.
Any answer is appreciated.
Exact matches on the tokenized fields are not that straightforward. Better save your field as keyword if you have such requirements.
Additionally, keyword data type support wildcard query which can help you in your wildcard searches.
So just create a keyword type subfield. Then use the wildcard query on it.
Your search query will look something like below:
GET /_search
{
"query": {
"wildcard" : {
"title.keyword" : "The * day I went with my * to the"
}
}
}
In the above query, it is assumed that title field has a sub-field named keyword of data type keyword.
More on wildcard query can be found here.
If you still want to do exact searches on text data type, then read this
Elasticsearch doesn't have Google like search out of the box, but you can build something similar.
Let's assume when someone quotes a search text what they want is a match phrase query. Basically remove the \" and search for the remaining string as a phrase.
PUT test/_doc/1
{
"title": "The other day I went with my mom to the pool and had a lot of fun"
}
GET test/_search
{
"query": {
"match_phrase": {
"title": "The other day I went with my mom to the pool and had a lot of fun"
}
}
}
For the * it's getting a little more interesting. You could just make multiple phrase searches out of this and combine them. Example:
GET test/_search
{
"query": {
"bool": {
"must": [
{
"match_phrase": {
"title": "The"
}
},
{
"match_phrase": {
"title": "day I went with my"
}
},
{
"match_phrase": {
"title": "to the"
}
}
]
}
}
}
Or you could use slop in the phrase search. All the terms in your search query have to be there (unless they are being removed by the tokenizer or as stop words), but the matched phrase can have additional words in the phrase. Here we can replace each * with 1 other words, so a slop of 2 in total. If you would want more than 1 word in the place of each * you will need to pick a higher slop:
GET test/_search
{
"query": {
"match_phrase": {
"title": {
"query": "The * day I went with my * to the",
"slop": 2
}
}
}
}
Another alternative might be shingles, but this is a more advanced concept and I would start off with the basics for now.
Is it possible to search within the results that I get from elasticsearch?
To achieve that currently I need to run & wait for two searches on elasticsearch: the first search is
{ "match": { "title": "foo" } }
It takes 5 seconds and returns 500 docs etc.. And then a second search
{
"bool": {
"must": [
{ "match": { "title": "foo" } },
{ "match": { "title": "bar" } }
]
}
}
It takes another 5 seconds and returns 200 docs, which basically has nothing to do with the first search from elasticsearch's perspective.
Instead of doing it this way, I'd like to offer a "search further within the result" option to my users. Hopefully with this option, users can make a search with more keyword provided based on the result returned from the first search.
So my scenario is that a user makes a first search with keyword "foo", and gets 500 results on the webpage, and then selects "search further within the result", to make a second search within the 500 results, and hope to get some refined results really quick.
How can I achive it? Thanks!
What you could do is use the IDS query. Collect all document IDs from the first request, and then post them with a new Bool query that includes an IDS query in a must clause next to the original query. You could efficiently collect the IDs in the first request using the Scroll API. Since you will return the second result sorted anyway, it does not make sense to do any sorting in the first request, so you can speed up the first request.
See:
Scroll API: https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-scroll.html
IDS Query: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-ids-query.html
post filter is a way to search inside an other search.
In your case :
GET _search
{
"query": {
"match": {
"title": "foo"
}
},
"post_filter": {
"match": {
"title": "bar"
}
}
}
post_filter will be executed on the query result.
I have a question about the Elasticsearch DSL.
I would like to do a full text search, but scope the searchable records to a specific array of database ids.
In SQL world, it would be the functional equivalent of WHERE id IN(1, 2, 3, 4).
I've been researching, but I find the Elasticsearch query DSL documentation a little cryptic and devoid of useful examples. Can anyone point me in the right direction?
Here is an example query which might work for you. This assumes that the _all field is enabled on your index (which is the default). It will do a full text search across all the fields in your index. Additionally, with the added ids filter, the query will exclude any document whose id is not in the given array.
{
"bool": {
"must": {
"match": {
"_all": "your search text"
}
},
"filter": {
"ids": {
"values": ["1","2","3","4"]
}
}
}
}
Hope this helps!
As discussed by Ali Beyad, ids field in the query can do that for you. Just to complement his answer, I am giving an working example. In case anyone in the future needs it.
GET index_name/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"field": "your query"
}
},
{
"ids" : {
"values" : ["0aRM6ngBFlDmSSLpu_J4", "0qRM6ngBFlDmSSLpu_J4"]
}
}
]
}
}
}
You can create a bool query that contains an Ids query in a MUST clause:
https://www.elastic.co/guide/en/elasticsearch/reference/2.0/query-dsl-ids-query.html
By using a MUST clause in a bool query, your search will be further limited by the Ids you specify. I'm assuming here by Ids you mean the _id value for your documents.
According to es doc, you can
Returns documents based on their IDs.
GET /_search
{
"query": {
"ids" : {
"values" : ["1", "4", "100"]
}
}
}
With elasticaBundle symfony 5.2
$query = new Query();
$IdsQuery = new Query\Ids();
$IdsQuery->setIds($id);
$query->setQuery($IdsQuery);
$this->finder->find($query, $limit);
You have two options.
The ids query:
GET index/_search
{
"query": {
"ids": {
"values": ["1, 2, 3"]
}
}
}
or
The terms query:
GET index/_search
{
"query": {
"terms": {
"yourNonPrimaryIdField": ["1", "2","3"]
}
}
}
The ids query targets the document's internal _id field (= the primary ID). But it often happens that documents contain secondary (and more) IDs which you'd target thru the terms query.
Note that if your secondary IDs contain uppercase chars and you don't set their field's mapping to keyword, they'll be normalized (and lowercased) and the terms query will appear broken because it only works with exact matches. More on this here: Only getting results when elasticsearch is case sensitive
I have a set of documents like
{
tags:['a','b','c']
// ... a bunch properties
}
As stated in the title: Is there a way to filter all documents containing any of given tags using Nest ?
For instance, the record above would match ['c','d']
Or should I build multiple "OR"s manually ?
elasticsearch 2.0.1:
There's also terms query which should save you some work. Here example from docs:
{
"terms" : {
"tags" : [ "blue", "pill" ],
"minimum_should_match" : 1
}
}
Under hood it constructs boolean should. So it's basically the same thing as above but shorter.
There's also a corresponding terms filter.
So to summarize your query could look like this:
{
"filtered": {
"query": {
"match": { "title": "hello world" }
},
"filter": {
"terms": {
"tags": ["c", "d"]
}
}
}
}
With greater number of tags this could make quite a difference in length.
Edit: The bitset stuff below is maybe an interesting read, but the answer itself is a bit dated. Some of this functionality is changing around in 2.x. Also Slawek points out in another answer that the terms query is an easy way to DRY up the search in this case. Refactored at the end for current best practices. —nz
You'll probably want a Bool Query (or more likely Filter alongside another query), with a should clause.
The bool query has three main properties: must, should, and must_not. Each of these accepts another query, or array of queries. The clause names are fairly self-explanatory; in your case, the should clause may specify a list filters, a match against any one of which will return the document you're looking for.
From the docs:
In a boolean query with no must clauses, one or more should clauses must match a document. The minimum number of should clauses to match can be set using the minimum_should_match parameter.
Here's an example of what that Bool query might look like in isolation:
{
"bool": {
"should": [
{ "term": { "tag": "c" }},
{ "term": { "tag": "d" }}
]
}
}
And here's another example of that Bool query as a filter within a more general-purpose Filtered Query:
{
"filtered": {
"query": {
"match": { "title": "hello world" }
},
"filter": {
"bool": {
"should": [
{ "term": { "tag": "c" }},
{ "term": { "tag": "d" }}
]
}
}
}
}
Whether you use Bool as a query (e.g., to influence the score of matches), or as a filter (e.g., to reduce the hits that are then being scored or post-filtered) is subjective, depending on your requirements.
It is generally preferable to use Bool in favor of an Or Filter, unless you have a reason to use And/Or/Not (such reasons do exist). The Elasticsearch blog has more information about the different implementations of each, and good examples of when you might prefer Bool over And/Or/Not, and vice-versa.
Elasticsearch blog: All About Elasticsearch Filter Bitsets
Update with a refactored query...
Now, with all of that out of the way, the terms query is a DRYer version of all of the above. It does the right thing with respect to the type of query under the hood, it behaves the same as the bool + should using the minimum_should_match options, and overall is a bit more terse.
Here's that last query refactored a bit:
{
"filtered": {
"query": {
"match": { "title": "hello world" }
},
"filter": {
"terms": {
"tag": [ "c", "d" ],
"minimum_should_match": 1
}
}
}
}
Whilst this an old question, I ran into this problem myself recently and some of the answers here are now deprecated (as the comments point out). So for the benefit of others who may have stumbled here:
A term query can be used to find the exact term specified in the reverse index:
{
"query": {
"term" : { "tags" : "a" }
}
From the documenation https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html
Alternatively you can use a terms query, which will match all documents with any of the items specified in the given array:
{
"query": {
"terms" : { "tags" : ["a", "c"]}
}
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-terms-query.html
One gotcha to be aware of (which caught me out) - how you define the document also makes a difference. If the field you're searching in has been indexed as a text type then Elasticsearch will perform a full text search (i.e using an analyzed string).
If you've indexed the field as a keyword then a keyword search using a 'non-analyzed' string is performed. This can have a massive practical impact as Analyzed strings are pre-processed (lowercased, punctuation dropped etc.) See (https://www.elastic.co/guide/en/elasticsearch/guide/master/term-vs-full-text.html)
To avoid these issues, the string field has split into two new types: text, which should be used for full-text search, and keyword, which should be used for keyword search. (https://www.elastic.co/blog/strings-are-dead-long-live-strings)
For those looking at this in 2020, you may notice that accepted answer is deprecated in 2020, but there is a similar approach available using terms_set and minimum_should_match_script combination.
Please see the detailed answer here in the SO thread
You should use Terms Query
{
"query" : {
"terms" : {
"tags" : ["c", "d"]
}
}
}
My documents are indexed like this:
{
title: "stuff here",
description: "stuff here",
keywords: "stuff here",
score1: "number here",
score2: "number here"
}
I want to perform a query that:
Uses the title, description, and keywords fields for matching the text terms.
It doesn't have to be complete match. Eg. If someone searches "I have a big nose", and "nose" is in one of the document titles but "big" is not, then this document should still be returned.
Edit: I tried this query and it works. Can someone confirm if this is the right way to do it? Thanks.
{
query:{
'multi_match':{
'query': q,
'fields': ['title^2','description', 'keywords'],
}
}
}
Your way is definitely the way to go!
The multi_match query is usually the one that you want to expose to the end users, while the query_string is similar, but also more powerful and dangerous since it exposes the lucene query syntax. Rule of thumb: don't use query string if you don't need it.
Also, searching on multiple fields is easy just providing the list of fields you want to search on, as you did, without the need for a bool query.
Below is the code that will create the query you can use. I wrote it in c# but it will work in other languages in the same way.
What you need to do is to create a BooleanQuery and set that at least 1 of its condition has to match. Then add a condition for every document field you want to be checked with Occur.SHOULD enum value:
BooleanQuery searchQuery = new BooleanQuery();
searchQuery.SetMinimumNumberShouldMatch(1);
QueryParser parser = new QueryParser(Lucene.Net.Util.Version.LUCENE_29, "title", new StandardAnalyzer(Lucene.Net.Util.Version.LUCENE_29));
Query titleQuery = parser.Parse("I have a big nose");
searchQuery.Add(titleQuery, BooleanClause.Occur.SHOULD);
parser = new QueryParser(Lucene.Net.Util.Version.LUCENE_29, "description", new StandardAnalyzer(Lucene.Net.Util.Version.LUCENE_29));
Query descriptionQuery = parser.Parse("I have a big nose");
searchQuery.Add(titleQuery, BooleanClause.Occur.SHOULD);
parser = new QueryParser(Lucene.Net.Util.Version.LUCENE_29, "keywords", new StandardAnalyzer(Lucene.Net.Util.Version.LUCENE_29));
Query keywordsQuery = parser.Parse("I have a big nose");
searchQuery.Add(titleQuery, BooleanClause.Occur.SHOULD);
Query queryThatShouldBeExecuted.Add(searchQuery, BooleanClause.Occur.MUST);
Here is the link to an example in java http://www.javadocexamples.com/java_source/org/apache/lucene/search/TestBooleanMinShouldMatch.java.html
The according JSON object to perform a HTTP Post request would be this:
{
"bool": {
"should": [
{
"query_string": {
"query": "I have a big nose",
"default_field": "title"
}
},
{
"query_string": {
"query": "I have a big nose",
"default_field": "description"
}
},
{
"query_string": {
"query": "I have a big nose",
"default_field": "keywords"
}
}
],
"minimum_number_should_match": 1,
"boost": 1
}
}