Using elastic search, I am trying to get data for nested object
BoolQueryBuilder boolBuilder = QueryBuilders.boolQuery();
NestedQueryBuilder nestedBuilder = QueryBuilders.nestedQuery("Attributes", boolBuilder);
boolBuilder.must(QueryBuilders.termQuery("Attributes.attributeId", "1001"));
Result comes if the query is like this,
{
"nested" : {
"query" : {
"bool" : {
"must" : [ {
"term" : {
"Attributes.attributeId" : "1001"
}
]
}
},
"path" : "Attributes"
}'
Result not coming if the query is like this,
{
"nested" : {
"query" : {
"bool" : {
"must" : [ {
"term" : {
"attributeId" : "1001"
}
]
}
},
"path" : "Attributes"
}
Can somebody help me.Here i have to get result without using "Attributes.attributeId".ie. using "attributeId" alone data have to come.
This is expected as per the nested query documentation
The query path points to the nested object path, and the query (or
filter) includes the query that will run on the nested docs matching
the direct path, and joining with the root parent docs. Note that any
fields referenced inside the query must use the complete path (fully
qualified).
Related
I am getting the results based on various filters in the Elasticsearch which also includes pagination.
Now I need to navigate between previous and next record from that search results, when we open a record of the search results.
Is there a way to achieve this through Elasticsearch?
You could use the from and size parameters of the Search API.
GET /_search
{
"from" : 0, "size" : 10,
"query" : {
"term" : { "user" : "kimchy" }
}
}
or
GET /_search?from=0&size=10
{
"query" : {
"term" : { "user" : "kimchy" }
}
}
Note the default value for size is 10.
I have this schema in elastic search.
79[
'ID' : '1233',
Geomtries:[{
'doc1' : 'F1',
'doc2' : 'F2'
},
(optional for some of the documents)
{
'doc2' : 'F1',
'doc3' : 'F2'
}]
]
the Geometries is a nested element.
I want to get all of the documents that have one object inside Geometries.
Tried so far :
"script" : {"script" : "if (Geomtries.size < 2) return true"}
But i get exceptions : no such property GEOMTRIES
If you have the field as type nested in the mapping, the typical doc[fieldkey].values.size() approached does not seem to work. I found the following script to work:
{
"from" : 0,
"size" : <SIZE>,
"query" : {
"filtered" : {
"filter" : {
"script" : {
"script" : "_source.containsKey('Geomtries') && _source['Geomtries'].size() == 1"
}
}
}
}
}
NB: You must use _source instead of doc.
The problem is in the way you access fields in your script, use:
doc['Geometry'].size()
or
_source.Geometry.size()
By the way for performance reasons, I would denormalize and add GeometryNumber field. You can use the transform mapping to compute size at index time.
I have multiple mappings which come from the same datasource but have small differences, like the example below.
{
"type_A" : {
"properties" : {
"name" : {
"type" : "string"
}
"meta_A" : {
"type" : "string"
}
}
}
}
{
"type_B" : {
"properties" : {
"name" : {
"type" : "string"
}
"meta_B" : {
"type" : "string"
}
}
}
}
What I want to be able to is:
Directly query specific fields (like meta_A)
Directly query all documents from the datsource
Query all documents from a specific mapping
What I was looking into is the type filter, so preferably I could write a query like this:
{
"query": {
"filtered" : {
"filter" : {
"type" : { "value" : "unified_type" }
}
}
// other query clauses
}
}
So instead of typing "type_A","type_B" in an or clause in the type filter I would like to have this "unified_type", but without giving up the possibility to directly query "type_A".
How could I achive this?
I don't think that it's possible. However, you could use copy_to functionality, so you would have your fields as they are now and their values copied into unified name.
The copy_to parameter allows you to create custom _all fields. In
other words, the values of multiple fields can be copied into a group
field, which can then be queried as a single field. For instance, the
first_name and last_name fields can be copied to the full_name field
as follows:
So you'd be copying both "meta_A" and "meta_B" into some "unified_meta" field and query this one.
Is there a way in Elasticsearch through filters, queries, aggregations etc to search for a list of document ids and have returned which ids did not hit?
With a small list it is easy enough to compare the results against the requested ids list but I'm dealing with lists of ids in the tens of thousands and it is not going to be performant to do that.
Do you mean, from https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-not-filter.html
"filtered" : {
"query" : {
"term" : { "name.first" : "shay" }
},
"filter" : {
"not" : {
"range" : {
"postDate" : {
"from" : "2010-03-01",
"to" : "2010-04-01"
}
}
}
}
}
Take a look at the guide at https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
For my project, I thought of using Span Near Queries of ElasticSearch, with the constraint that is, certain tokens may have to searched with Fuzziness. I was able to generate a set of SpanQuery (org.apache.lucene.search.spans.SpanQuery) objects some with fuzzy enabled, some without. I couldn't figure out how to use these set of SpanQueries in ElasticSearch spanNearQuery.
Can someone help me out with right pointers to samples or docs. And is there any way to construct ES SpanNearQueryBuilder with some clauses fuzzy enabled ?
You can wrap an fuzzy query into a span query with Span Multi Term Query:
{
"span_near" : {
"clauses" : [
{ "span_term" : { "field" : "value1" } },
{ "span_multi" :
"match" : {
"prefix" : { "user" : { "field" : "value2" } }
}
}
],
...
}
}