Originally I've been trying to get a list of parents and a single most recent child for each one of them. I've figured how to do that with the following query
{"query":
{"has_child":
{"inner_hits":
{"name": "latest", "size": 1, "sort":
[{"started_at": {"order": "desc"}}]
},
"type": "child_type",
"query": {"match_all": {}}
}
}
}
But the problem is — the results do not include parents with no children. Adding min_children: 0 doesn't help either. So I thought I could make a query for all parents with no children and combine those two in a single OR query. But I'm having trouble building such a query. Would appreciate any suggestions.
Here is your query:
{
"query":{
"bool":{
"should":[
{
"bool":{
"must_not":[
{
"has_child":{
"type":"child_type",
"query":{
"match_all":{}
}
}
}
]
}
},
{
"has_child":{
"inner_hits":{
"name":"latest",
"size":1, "sort":[{"started_at": {"order": "desc"}}]
},
"type":"child_type",
"query":{
"match_all":{}
}
}
}
]
}
}
}
Another point: just use must_not for has_child will not only show parents without child, but all the child(s) as well, because they all don't have any child...
So another limitation should be added in the bool query:
{
"query":{
"bool": {
"must_not": [
{
"has_child": {
"type": "<child-type>",
"query": {
"match_all": {}
}
}
}
],
"should": [
{
"term": {
"<the join field>": {
"value": "<parent-type>"
}
}
}
]
}
}
}
Related
Hello I have the following query that I am running:
{
"_source": [
"source1",
"source2",
"source3",
"source4",
],
"query": {
"bool": {
"minimum_should_match": 1,
"must": {
"filter": [
{
"term": {
"_type": {
"value": "someval1"
}
}
},
{
"term": {
"_type": {
"value": "someval2"
}
}
}
],
"query_string": {
"analyze_wildcard": "true",
"query": "tesla*",
"rewrite": "scoring_boolean"
}
}
}
},
"size": 50,
"sort": [
"_score"
]
}
That is currently returning:
'"reason":"[bool] malformed query, expected [END_OBJECT] but found [FIELD_NAME]","line":1,"col":343},"status":400}'
Any idea how to use multiple filters on a query? I was able to do it just fine on elastic 2.4 but since OR is now deprecated as well as filtered, I am a bit lost.
Thanks!
The syntax of the query is wrong. filter should not be wrapped into the must statement. It should be in the same level with must. Also bool queries must statement should be an array, not an object. So your query should look like this
{
"_source":[
"source1",
"source2",
"source3",
"source4"
],
"query":{
"bool":{
"minimum_should_match":1,
"must":[
{
"query_string":{
"analyze_wildcard":"true",
"query":"tesla*",
"rewrite":"scoring_boolean"
}
}
],
"filter":{
"bool":{
"should":[
{
"term":{
"_type":{
"value":"someval1"
}
}
},
{
"term":{
"_type":{
"value":"someval2"
}
}
}
]
}
}
}
},
"size":50,
"sort":[
"_score"
]
}
I think your filter is OR, that's why I wrap it inside should
Suppose, in ElasticSearch 5, I have data with nesting like:
{"number":1234, "names": [
{"firstName": "John", "lastName": "Smith"},
{"firstName": "Al", "lastName": "Jones"}
]},
...
And I want to query for hits with number 1234 but return only the names that match "lastName": "Jones", so that my result omits names that don't match. In other words, I want to get back only part of the matching document, based on a term query or similar.
A simple nested query won't do, as such would be filtering top-level results. Any ideas?
{ "query" : { "bool": { "filter":[
{ "term": { "number":1234} },
???? something with "lastName": "Jones" ????
] } } }
I want back:
hits: [
{"number":1234, "names": [
{"firstName": "Al", "lastName": "Jones"}
]},
...
]
hits section returns a _source - this is exactly the same document you have indexed.
You are right, nested query filters top-level results, but with inner_hits it will show you which inner nested objects caused these top-level documents to be returned, and this is exactly what you need.
names field can be excluded from top-level hits using _source parameter.
{
"_source": {
"excludes": ["names"]
},
"query":{
"bool":{
"must":[
{
"term":{
"number":{
"value":"1234"
}
}
},
{
"nested":{
"path":"names",
"query":{
"term":{
"names.lastName":"Jones"
}
},
"inner_hits":{
}
}
}
]
}
}
}
So now top-level documents are returned without names field, and you have an additional inner_hits section with the names that match.
You should treat nested objects as part of a top-level document.
If you really need them to be separate - consider parent/child relations.
Try something like this
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"bool": {
"must": [
{
{ "term": { "number":1234} }
},
{
"nested": {
"path": "something",
"query": {
"term": {
"something.lastName": "Jones"
}
},
"inner_hits" : {}
}
}
]
}
}
}
}
}
I used this Refrence
Similar but a bit different, use the should parameter and then look at inner hits for the names. This will return the top level doc and then inner_hits will have any hits.
{
"_source": {
"excludes": ["names"]
},
"query":{
"bool":{
"must":[
{
"term":{
"number":{
"value":"1234"
}
}
}
],
should: [
{
"nested":{
"path":"names",
"query":{
"term":{
"names.lastName":"Jones"
}
},
"inner_hits":{
}
}
}
]
}
}
}
I am facing issue in migrating from elastic search 1.5 to 5.1.
Following is my elastic search - 1.5 Query:
{
"_source":["_id","spotlight"],
"query":{
"filtered":{
"filter":{
"and":[
{"term":{"gender":"female"}},
{"range":{"lastlogindate":{"gte":"2016-10-19 12:39:57"}}}
]
}
}
},
"filter":{
"and":[
{"term":{"maritalstatus":"1"}}
]
},
"sort":[{"member2_dummy7":{"order":"desc"}}],
"size":"0",
"aggs": {
"maritalstatus": {
"filter": {},
"aggs" : {
"filtered_maritalstatus": {"terms":{"field":"maritalstatus","size":5000}}
}
}
}
}
This query is giving me correct doc_count in aggregations. This doc_count is calculated over result set returned by query context and it ignores filter context.
I have written same query in elastic search 5.1:
{
"_source":["_id","spotlight"],
"query":{
"bool":{
"must":[
{"term":{"gender":"female"}},
{"range":{"lastlogindate":{"gte":"2016-10-19 12:39:57"}}}
],
"filter":{
"bool":{
"must":[
{"term":{"maritalstatus":"1"}}
]
}
}
}
},
"sort":[{"member2_dummy7":{"order":"DESC"}}],
"size":"0",
"aggs": {
"maritalstatus": {
"filter": {},
"aggs" : {
"filtered_maritalstatus": {"terms":{"field":"maritalstatus","size":5000}}
}
}
}
}
But in elastic search 5.1, it is returning me wrong doc_count in aggregation. I think it is taking filter in query context and hence, it is returning wrong doc_cout. Can someone tell me correct way to separate query and filter in elastic search 5.1?
Your 1.5 query uses post_filter which you have removed in your 5.1 query.
The equivalent query in ES 5.1 is the following (filtered/filter simply gets replaced as bool/filter and the top-level filter renamed to post_filter):
{
"_source": [
"_id",
"spotlight"
],
"query": {
"bool": {
"filter": [
{
"term": {
"gender": "female"
}
},
{
"range": {
"lastlogindate": {
"gte": "2016-10-19 12:39:57"
}
}
}
]
}
},
"post_filter": {
"term": {
"maritalstatus": "1"
}
},
"sort": [
{
"member2_dummy7": {
"order": "desc"
}
}
],
"size": "0",
"aggs": {
"maritalstatus": {
"filter": {},
"aggs": {
"filtered_maritalstatus": {
"terms": {
"field": "maritalstatus",
"size": 5000
}
}
}
}
}
}
I'm building up the following search in code, the idea being that it filters down the set of matches then queries this so I can add score based on certain fields. For some reason the filter part works but whatever I put in the query (i.e. in the below I have no index sdfsdfsdf) it still returns anything matching the filter.
Is the syntax wrong?
{
"query":{
"filtered":{
"query":{
"bool":{
"must":{
"match":{
"sdfsdfsdf":{
"query":"4",
"boost":2.0
}
}
}
},
"filter":{
"bool":{
"must":[
{
"terms":{
"_id":[
"55f93ead5df34f1900abc20b",
"55f8ab0226ec4bb216d7c938",
"55dc4e949dcf833308c63d6b"
]
}
},
{
"range":{
"published_date":{
"lte":"now"
}
}
}
],
"must_not":{
"terms":{
"_id":[
"55f0a799acccc28204a5058c"
]
}
}
}
}
}
}
}
}
Your filter is not at the right level. It should not be inside query but at the same level as query like this:
{
"query": {
"filtered": {
"query": { <--- query and filter at the same level
"bool": {
"must": {
"match": {
"sdfsdfsdf": {
"query": "4",
"boost": 2
}
}
}
}
},
"filter": { <--- query and filter at the same level
"bool": {
"must": [
{
"terms": {
"_id": [
"55f93ead5df34f1900abc20b",
"55f8ab0226ec4bb216d7c938",
"55dc4e949dcf833308c63d6b"
]
}
},
{
"range": {
"published_date": {
"lte": "now"
}
}
}
],
"must_not": {
"terms": {
"_id": [
"55f0a799acccc28204a5058c"
]
}
}
}
}
}
}
}
You need to replace sdfsdfsdf with your existing field name in your type, e.g. title, otherwise I think it will fallback to match_all query.
"match":{
"title":{
"query": "some text here",
"boost":2.0
}
}
For one case I need to put multiple search conditions in one query to reduce the number of queries we need.
However, I need to distinguish the returning items based on the conditions.
Currently I achieved this goal by using function score query, specifically: each condition is assigned with a score, and I can differentiate the results based on those scores.
However, the performance is not that good. Plus now we need to get the doc count of each condition.
So is there any way to do it? I'm thinking using aggregation, but not sure if I can do it.
Thanks!
update:
curl -X GET 'localhost:9200/locations/_search?fields=_id&from=0&size=1000&pretty' -d '{
"query":{
"bool":{
"should":[
{
"filtered":{
"filter":{
"bool":{
"must":[{"term":{"city":"new york"}},{"term":{"state":"ny"}}]
}
}
}
},
{
"filtered":{
"filter":{
"bool":{
"must":[{"term":{"city":"los angeles"}},{"term":{"state":"ca"}}]
}
}
}
}
]
}
}}'
Well to answer the first part of your question , names queries are the best.
For eg:
{
"query": {
"bool": {
"should": [
{
"match": {
"field1": {
"query": "qbox",
"_name": "firstQuery"
}
}
},
{
"match": {
"field2": {
"query": "hosted Elasticsearch",
"_name": "secondQuery"
}
}
}
]
}
}
}
This will return an additional field called matched_queries for each hit which will have the information on queries matched for that document.
You can find more info on names queries here
But this this information cant be used for aggregation.
So you need to handle the second part of your question in a separate manner.
Filter aggregation for each query type would be the idea solution here.
For eg:
{
"query": {
"bool": {
"should": [
{
"match": {
"text": {
"query": "qbox",
"_name": "firstQuery"
}
}
},
{
"match": {
"source": {
"query": "elasticsearch",
"_name": "secondQuery"
}
}
}
]
}
},
"aggs": {
"firstQuery": {
"filter": {
"term": {
"text": "qbox"
}
}
},
"secondQuery": {
"filter": {
"term": {
"source": "elasticsearch"
}
}
}
}
}
You can find more on filter aggregation here