I have trouble combining term, must_not queries on nested documents.
Sense example can be found here : http://sense.qbox.io/gist/be436a1ffa01e4630a964f48b2d5b3a1ef5fa176
Here my mapping :
{
"mappings": {
"docs" : {
"properties": {
"tags" : {
"type": "nested",
"properties" : {
"type": {
"type": "string",
"index": "not_analyzed"
}
}
},
"label" : {
"type": "string"
}
}
}
}
}
with two documents in this index :
{
"tags" : [
{"type" : "POST"},
{"type" : "DELETE"}
],
"label" : "item 1"
},
{
"tags" : [
{"type" : "POST"}
],
"label" : "item 2"
}
When I query this index like this :
{
"query": {
"nested": {
"path": "tags",
"query": {
"bool": {
"must": {
"term": {
"tags.type": "DELETE"
}
}
}
}
}
}
}
I've got one hit (which is correct)
When I want to get documents WHICH DON'T CONTAIN the tag "DELETE", with this query :
{
"query": {
"nested": {
"path": "tags",
"query": {
"bool": {
"must_not": {
"term": {
"tags.type": "delete"
}
}
}
}
}
}
}
I've got 2 hits (which is incorrect).
This issue seems very close to this one (Elasticsearch array must and must_not) but it's not...
Can you give me some clues to resolve this issue ?
Thank you
Your original query would search in each individual nested object and eliminate the objects that don't match, but if there are some nested objects left, they do match with your query and so you get your results. This is because nested objects are indexed as a hidden separate document
Original code:
{
"query": {
"nested": {
"path": "tags",
"query": {
"bool": {
"must_not": {
"term": {
"tags.type": "delete"
}
}
}
}
}
}
}
The solution is then quite simple really, you should bring the bool query outside the nested documents. Now all the documents are discarded who have a nested object with the "DELETE" type. Just what you wanted!
The solution:
{
"query": {
"bool": {
"must_not": {
"nested": {
"path": "tags",
"query": {
"term": {
"tags.type": "DELETE"
}
}
}
}
}
}
}
NOTE: Your strings are "not analyzed" and you searched for "delete" instead of "DELETE". If you want to search case insensitive, make your strings analyzed
This should fix your problem: http://sense.qbox.io/gist/f4694f542bc76c29624b5b5c9b3ecdee36f7e3ea
Two most important things:
include_in_root on "tags.type". This will tell ES to index tag types as "doc.tags.types" : ['DELETE', 'POSTS'], so you can access an array of those values "flattened" on the root doc . This means you no longer need a nested query (see #2)
Drop the nested query.
{
"mappings": {
"docs" : {
"properties": {
"tags" : {
"type": "nested",
"properties" : {
"type": {
"type": "string",
"index": "not_analyzed"
}
},
"include_in_root": true
},
"label" : {
"type": "string"
}
}
}
}
}
{
"query": {
"bool": {
"must_not": {
"term": {
"tags.type": "DELETE"
}
}
}
}
}
Related
Suppose I have the following mapping:
"mappings": {
"doc": {
"properties": {
"name": {
"type": "text"
},
"location": {
"type": "nested",
"properties": {
"point": {
"type": "geo_shape"
}
}
}
}
}
}
}
There is one document in the index:
POST /example/doc?refresh
{
"name": "Wind & Wetter, Berlin, Germany",
"location": {
"type": "point",
"coordinates": [13.400544, 52.530286]
}
}
How can I make a nested geo-shape query?
Example of usual geo-shape query from the documentation (the "bool" block can be skipped):
{
"query":{
"bool": {
"must": {
"match_all": {}
},
"filter": {
"geo_shape": {
"location": {
"shape": {
"type": "envelope",
"coordinates" : [[13.0, 53.0], [14.0, 52.0]]
},
"relation": "within"
}
}
}
}
}
}
Example of a nested query is:
{
"query": {
"nested" : {
"path" : "obj1",
"score_mode" : "avg",
"query" : {
"bool" : {
"must" : [
{ "match" : {"obj1.name" : "blue"} },
{ "range" : {"obj1.count" : {"gt" : 5}} }
]
}
}
}
}
}
Now how to combine them? In the documentation it is mentioned that nested filter has been replaced by nested query. And that it behaves as a query in “query context” and as a filter in “filter context”.
If I try query for intersect with the point:
{
"query": {
"nested": {
"path": "location",
"query": {
"geo_shape": {
"location.point": {
"shape": {
"type": "point",
"coordinates": [
13.400544,
52.530286
]
},
"relation": "disjoint"
}
}
}
}
}
}
I still get back the document even if relation is "disjoint", so it's not correct. I tried different combinations, with "bool" and "filter", etc. but query is ignored, returning the whole index. Maybe it's impossible with this type of mapping?
Clearly I am missing something here. Can somebody help me out with that, please? Any help is greatly appreciated.
The mapping contains nested fields which shouldn't be analyzed (not sure if the 'not_analyzed' value is accurate). Is it possible to do an exact match on a nested field? In the query below the "metadata.value": "2014.NWJSD.47" still gets analyzed. Elasticsearch breaks up the string into several terms ("2014", "NWJSD", "47"). I tried to use "term" instead of "match" but this didn't return any result.
"mappings" : {
"metadata" : {
"type" : "nested",
"properties" : {
"name" : {
"type" : "text",
"index" : "not_analyzed"
},
"value" : {
"type" : "text",
"index" : "not_analyzed"
}
}
}
}
The Query:
"query": {
"bool": {
"must": [
{
"nested": {
"path": "metadata",
"query": {
"bool": {
"must": [
{
"match": {
"metadata.name": "number"
}
},
{
"match": {
"metadata.value": "2014.NWJSD.47"
}
}
]
}
}
}
}
]
}
}
Try to use keyword instead of text in your mapping like:
{
"mappings": {
"your_type_name": {
"properties": {
"metadata" : {
"type" : "nested",
"properties" : {
"name" : {
"type" : "keyword"
},
"value" : {
"type" :"keyword"
}
}
}
}
}
}
}
These fields won't be analyzed. Then you should reindex your data and to query your data you should replace match (which is analyzed query) with term.
{
"query": {
"bool": {
"must": [
{
"nested": {
"path": "metadata",
"query": {
"bool": {
"must": [
{
"term": {
"metadata.name": "number"
}
},
{
"term": {
"metadata.value": "2014.NWJSD.47"
}
}
]
}
}
}
}
]
}
}
}
I think you are looking for a query string query.
You can freely disable "analyze" option for that field in mapping option and reindex everything again but you could also check this query out:
as written here:
GET /_search
{
"query": {
"query_string" : {
"query" : "your string"
}
}
}
I have indexed JSON like below format
JSON:
{"work":[{"organization":"abc", end:"present"},{"organization":"edf", end:"old"}]}
{"work":[{"organization":"edf", end:"present"},{"organization":"abc", end:"old"}]}
I want to query records where organization is "abc" and end is "present"
but below query is not working
work.0.organization: "abc" AND work.0.end:"present"
No records are matched
if I give query like below
work.organization: "abc" AND work.end:"present"
Both the records are matched. Whereas only the first record is what I want
The matched record should be only the below
{"work":[{"organization":"abc", end:"present"},{"organization":"edf", end:"old"}]}
You have to use nested_types. First map work as nested type in elastic using following mappings
PUT index_name_3
{
"mappings": {
"document_type" : {
"properties": {
"work" : {
"type": "nested",
"properties": {
"organization" : {
"type" : "text"
},
"end" : {
"type" : "text"
}
}
}
}
}
}
}
Use the following query to do nested filter match and innerhits
{
"query": {
"nested": {
"path": "work",
"inner_hits": {},
"query": {
"bool": {
"must": [{
"term": {
"work.organization": {
"value": "abc"
}
}
},
{
"term": {
"work.end": {
"value": "present"
}
}
}
]
}
}
}
}
}
I am trying to crack the elasticsearch query language, and so far I'm not doing very good.
I've got the following mapping for my documents.
{
"mappings": {
"jsondoc": {
"properties": {
"header" : {
"type" : "nested",
"properties" : {
"plainText" : { "type" : "string" },
"title" : { "type" : "string" },
"year" : { "type" : "string" },
"pages" : { "type" : "string" }
}
},
"sentences": {
"type": "nested",
"properties": {
"id": { "type": "integer" },
"text": { "type": "string" },
"tokens": { "type": "nested" },
"rhetoricalClass": { "type": "string" },
"babelSynsetsOcc": {
"type": "nested",
"properties" : {
"id" : { "type" : "integer" },
"text" : { "type" : "string" },
"synsetID" : { "type" : "string" }
}
}
}
}
}
}
}
}
It mainly resembles a JSON file referring to a pdf document.
I have been trying to make queries with aggregations and so far is going great. I've gotten to the point of grouping by (aggregating) rhetoricalClass, get the total number of repetitions of babelSynsetsOcc.synsetID. Heck, even the same query even by grouping the whole result by header.year
But, right now, I am struggling with filtering the documents that contain a term and doing the same query.
So, how could I make a query such that grouping by rhetoricalClass and only taking into account those documents whose field header.plainText contains either ["Computational", "Compositional", "Semantics"]. I mean contain instead of equal!.
If I were to make a rough translation to SQL it would be something similar to
SELECT count(sentences.babelSynsetsOcc.synsetID)
FROM jsondoc
WHERE header.plainText like '%Computational%' OR header.plainText like '%Compositional%' OR header.plainText like '%Sematics%'
GROUP BY sentences.rhetoricalClass
WHERE clauses are just standard structured queries, so they translate to queries in Elasticsearch.
GROUP BY and HAVING loosely translate to aggregations in Elasticsearch's DSL. Functions like count, min max, and sum are a function of GROUP BY and it's therefore also an aggregation.
The fact that you're using nested objects may be necessary, but it adds an extra layer to each part that touches them. If those nested objects are not arrays, then do not use nested; use object in that case.
I would probably look at translating your query to:
{
"query": {
"nested": {
"path": "header",
"query": {
"bool": {
"should": [
{
"match": {
"header.plainText" : "Computational"
}
},
{
"match": {
"header.plainText" : "Compositional"
}
},
{
"match": {
"header.plainText" : "Semantics"
}
}
]
}
}
}
}
}
Alternatively, it could be rewritten as this, which is a little less obvious of its intent:
{
"query": {
"nested": {
"path": "header",
"query": {
"match": {
"header.plainText": "Computational Compositional Semantics"
}
}
}
}
}
The aggregation would then be:
{
"aggs": {
"nested_sentences": {
"nested": {
"path": "sentences"
},
"group_by_rhetorical_class": {
"terms": {
"field": "sentences.rhetoricalClass",
"size": 10
},
"aggs": {
"nested_babel": {
"path": "sentences.babelSynsetsOcc"
},
"aggs": {
"count_synset_id": {
"count": {
"field": "sentences.babelSynsetsOcc.synsetID"
}
}
}
}
}
}
}
}
Now, if you combine them and throw away hits (since you're just looking for the aggregated result), then it looks like this:
{
"size": 0,
"query": {
"nested": {
"path": "header",
"query": {
"match": {
"header.plainText": "Computational Compositional Semantics"
}
}
}
},
"aggs": {
"nested_sentences": {
"nested": {
"path": "sentences"
},
"group_by_rhetorical_class": {
"terms": {
"field": "sentences.rhetoricalClass",
"size": 10
},
"aggs": {
"nested_babel": {
"path": "sentences.babelSynsetsOcc"
},
"aggs": {
"count_synset_id": {
"count": {
"field": "sentences.babelSynsetsOcc.synsetID"
}
}
}
}
}
}
}
}
I am trying to use Elastic Search and I am stuck trying to query for the nested object.
Basically my object is of the following format
{
"name" : "Some Name",
"field2": [
{
"prop1": "val1",
"prop2": "val2"
},
{
"prop1": "val3",
"prop2":: "val4"
}
]
}
Mapping I used for the nested field is the following.
PUT /someval/posts/_mapping
{
"posts": {
"properties": {
"field2": {
"type": "nested"
}
}
}
}
Say now i insert elements for /field/posts/1 and /field/posts/2 etc. I have k values for field2.prop1 and i want a query which gets the posts sorted based on most match of field2.prop1 among the K values i have. What would be the appropriate query for that.
Also I tried a simple filter but even that doesnt seem to work right.
GET /someval/posts/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
}
},
"filter" : {
"nested" : {
"path" : "field2",
"filter" : {
"bool" : {
"must" : [
{
"term" : {"field2.prop1" : "val1"}
}
]
}
},
"_cache" : true
}
}
}
}
The above query should match atleast the first post. But it returns no match. Can anyone help to clarify whats wrong here ?
There was problem in your json structure, you used filtered query , but filter(object) was in different level than query.
Find the difference.
POST /someval/posts/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"nested": {
"path": "field2",
"filter": {
"bool": {
"must": [
{
"term": {
"field2.prop1": "val1"
}
}
]
}
},
"_cache": true
}
}
}
}
}