Is possible in Elastisearch to have an aggregation which will have a filter/query including fuzzy?
ATM i have documents which contains nested object[]. What I want to achieve:
- select from each document 0..n nested objects which match a filter
- from this array of nested objects take the distinct one
- sort them by _score
- take the top 5 or X
- use the terms for an autocomplete/suggestions (should work more as a "like" and not autocomplete)
Until now I tried different types of aggregations like: significant_terms, top_hits but not in a good combination so I don't get the desired result.
Problems:
significant_terms doesn't return a value until he figures out when a term is significant (maybe i did not use a good analyzer)
top-hits returns any nested obj from the selected document and also contains duplicates
Here is an example of my query
GET customerinsights/_search
{
"query": {
"bool": {
"must": [
{
"nested": {
"path": "CustomerInsightTargets",
"query": {
"bool": {
"must": [
{
"match": {
"CustomerInsightTargets.CustomerInsightValue": {
"query": "2017",
"operator": "AND",
"fuzziness": 2
}
}
}
]
}
}
}
}
]
}
} ,
"aggs": {
"root": {
"nested": {
"path": "CustomerInsightTargets"
},
"aggs": {
"top_tags": {
"terms": {
"field": "CustomerInsightTargets.CustomerInsightSource.keyword"
},
"aggs": {
"top_tag_hits": {
"top_hits": {
"sort": [
{
"_score": {
"order": "desc"
}
}
],
"size": 5,
"_source": "CustomerInsightTargets"
}
}
}
}
}
}
},
"size": 0,
"_source": "CustomerInsightTargets"
}
Related
I'm quite new to ES and have been trying many different ways to sort on a subset results from Query/Filter. The aggs always sort on the whole collection instead of the result from the above query. My final goal is to sort on field price from the result of query (which was already sorted by _score and only 5 docs)
{
"query": {
"bool": {
"must": {
"function_score": {
"functions": [....],
"query": {....}
},
"score_mode": "sum",
"max_boost": 1.5
}
},
"filter": [...]
}
},
"size": 5,
"from": 0,
"sort": {
"_score": "desc"
},
"_source": [
"title",
"price"
],
"aggs": {
"i_am_confused": {
"terms": {
"field": "price",
"order": {
"_term": "desc"
}
}
}
}
}
I don't want to sort on client (because the subset result would be at least 700 docs).
I appreciate your help.
I've tried a couple of aggs they all don't work as I want, probably I didn't use them right.
I have a query with multiple keywords with an aggregation on author ID.
I want the ranking to be based on combining must and should.
For example for query 'X', 'Y' the authors containing both 'X' and 'Y' in the document field should be ranked higher, followed by authors who have either 'X' or 'Y'.
Doing each of them (AND/OR) is easy, I need the idea/direction how to achieve both in one ES query.
The current query I have for both X and Y is:
GET /docs/_search
{
"size": 0,
"query": {
"bool": {
"must": [
{
"query_string": {
"query": "X",
"fields": [
"fulltext"
],
"default_operator": "AND"
}
},
{
"query_string": {
"query": "Y",
"fields": [
"fulltext"
],
"default_operator": "AND"
}
}
]
}
},
"aggs": {
"search-users": {
"terms": {
"field": "author.id.keyword",
"size": 200
},
"aggs": {
"top-docs": {
"top_hits": {
"size": 100
}
}
}
}
}
}
Changing must to should change it to OR but I want the combination of both ranking authors with must a higher ranking in aggregation.
The usual way of boosting results is by adding a should clause looking for both terms, like this.
GET /docs/_search
{
"size": 10,
"query": {
"bool": {
"should": [
{
"match": {
"fulltext": "X Y",
"operator": "AND"
}
}
],
"must": [
{
"match": {
"fulltext": "X Y",
"operator": "OR"
}
}
]
}
},
"aggs": {
"search-users": {
"terms": {
"field": "author.id.keyword",
"size": 200
},
"aggs": {
"top-docs": {
"top_hits": {
"size": 100
}
}
}
}
}
}
What I want to search is to extract documents among certain range of documents, not the whole documents. I know ids of documents. For example, I want to query matching some sentences with query field - 'pLabel' among the documents ids of which I know via different process. My trial is as below but I got bunch of documents which is different with my expectation.
For example, in such documents as eid1, eid2...etc groups, I want to query filtering out the matching documents out of the groups (eid1, eid2, eid3, ...). Query is shown as below.
How I fix query statement to get the right search result?
{
"query": {
"bool": {
"must": [
{
"query_string": {
"default_field": "pLabel" ,
"query": "search words here"
}
}
] ,
"must_not": [] ,
"should": [
{
"term": {
"eid": "eid1"
}
} ,
{
"term": {
"eid": "eid2"
}
}
]
}
} ,
"size": 0 ,
"_source": [
"eid"
] ,
"aggs": {
"eids": {
"terms": {
"field": "eid" ,
"size": 1000
}
}
}
}
You need to move the should clause of the Doc IDs inside the must clause.
Right now the query can return any document that matches the query_string clause, it'll only prefer docs that matches the Doc IDs.
Also, you should use terms query
{
"query": {
"bool": {
"must": [
{
"query_string": {
"default_field": "pLabel",
"query": "search words here"
}
},
{
"terms": {
"user": ["eid1", "eid2"]
}
}
]
}
},
"size": 0,
"_source": [
"eid"
],
"aggs": {
"eids": {
"terms": {
"field": "eid",
"size": 1000
}
}
}
}
I have a query that gets me some user post data from an elastic index. I am happy with that query, though I need to make it return rows with unique usernames. Current, it displays relevant posts by users, but it may display one user twice..
{
"query": {
"bool": {
"should": [
{ "match_phrase": { "gtitle": {"query": "voice","boost": 1}}},
{ "match_phrase": { "gdesc": {"query": "voice","boost": 1}}},
{ "match": { "city": {"query": "voice","boost": 2}}},
{ "match": { "gtags": {"query": "voice","boost": 1} }}
],"must_not": [
{ "term": { "profilepicture": ""}}
],"minimum_should_match" : 1
}
}
}
I have read about aggregations but didn't understand much (also tried to use aggs but didn't work either).... any help is appreciated
You would need to use terms aggregation to get all unique users and then use top hits aggregation to get only one result for each user. This is how it looks.
{
"query": {
"bool": {
"should": [
{
"match_phrase": {
"gtitle": {
"query": "voice",
"boost": 1
}
}
},
{
"match_phrase": {
"gdesc": {
"query": "voice",
"boost": 1
}
}
},
{
"match": {
"city": {
"query": "voice",
"boost": 2
}
}
},
{
"match": {
"gtags": {
"query": "voice",
"boost": 1
}
}
}
],
"must_not": [
{
"term": {
"profilepicture": ""
}
}
],
"minimum_should_match": 1
}
},
"aggs": {
"unique_user": {
"terms": {
"field": "userid",
"size": 100
},
"aggs": {
"only_one_post": {
"top_hits": {
"size": 1
}
}
}
}
},
"size": 0
}
Here size inside user aggregation is 100, you can increase that if you have more unique users(default is 10), also the outermost size is zero to get only aggregation results. One important thing to remember is your user ids have to be unique, i.e ABC and abc will be considered different users, you might have to make your userid not_analyzed to be sure about that. More on that.
Hope this helps!!
Elasticsearch documentation states that The top_hits aggregation returns regular search hits, because of this many per hit features can be supported Crucially, the list includes Named filters and queries
But trying to add any filter or query throws SearchParseException: Unknown key for a START_OBJECT
Use case: I have items which have list of nested comments
items{id} -> comments {date, rating}
I want to get top rated comment for each item in the last week.
{
"query": {
"match_all": {}
},
"aggs": {
"items": {
"terms": {
"field": "id",
"size": 10
},
"aggs": {
"comment": {
"nested": {
"path": "comments"
},
"aggs": {
"top_comment": {
"top_hits": {
"size": 1,
//need filter here to select only comments of last week
"sort": {
"comments.rating": {
"order": "desc"
}
}
}
}
}
}
}
}
}
}
So is the documentation wrong, or is there any way to add a filter?
https://www.elastic.co/guide/en/elasticsearch/reference/2.1/search-aggregations-metrics-top-hits-aggregation.html
Are you sure you have mapped them as Nested? I've just tried to execute such query on my data and it did work fine.
If so, you could simply add a filter aggregation, right after nested aggregation (hopefully I haven't messed up curly brackets):
POST data/_search
{
"size": 0,
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"nested": {
"path": "comments",
"query": {
"range": {
"comments.date": {
"gte": "now-1w",
"lte": "now"
}
}
}
}
}
}
},
"aggs": {
"items": {
"terms": {
"field": "id",
"size": 10
},
"aggs": {
"nested": {
"nested": {
"path": "comments"
},
"aggs": {
"filterComments": {
"filter": {
"range": {
"comments.date": {
"gte": "now-1w",
"lte": "now"
}
}
},
"aggs": {
"topComments": {
"top_hits": {
"size": 1,
"sort": {
"comments.rating": "desc"
}
}
}
}
}
}
}
}
}
}
}
P.S. Always include FULL path for nested objects.
So this query will:
Filter documents that have comments younger than one week to narrow down documents for aggregation and to find those, who actually have such comments (filtered query)
Do terms aggregation based on id field
Open nested sub documents (comments)
Filter them by date
Return the most badass one (most rated)