dsl_search
The function dsl_search(query_schema, size, function_name, collection_name) runs search queries Iin DSL syntaxt inside a collection.
Input
query_schema – the DLS query object.
size – Specifies the number of results to return.
function_name – Specifies the scoring function to be used in the Classic Search query, as described in Step 1, Creating the Scoring Function.
collection_name – Specifies the Collection in which to search.
fields (optional) – Specifies the document fields to be returned with each result.
Example
query = {
"query": {
"bool": {
"must": [
{"term": {"name": "John"}}
]
}
}
}
results = hyperspace_client.dsl_search(query,
size=10,
collection_name=collection_name)String queryJson = "{" +
" \"query\": {" +
" \"bool\": {" +
" \"must\": [" +
" {" +
" \"term\":{" +
" \"name\":\"John\"" +
" }" +
" }" +
" ]" +
" }" +
" }" +
"}";
JsonObject query = JsonParser.parseString(queryJson).getAsJsonObject();
Object response = client.dslSearch(collectionName, 10, query));const size = 10;
const query = {
"query": {
"bool": {
"must": [
{"term": {"name": "John"}}
]
}
}
};
await hyperspaceClient.search(collectionName, size, query);Where query_string is your query logic, see example below.
{
"query": {
"function_score": {
"query": {
"bool": {
"must": [
{
"term": {
"genres": "genres_value"
}
},
{
"term": {
"adult": "adult_value"
}
},
{
"bool": {
"must_not": [
{
"term": {
"title": "title_value"
}
}
]
}
}
],
"should": [
{
"range": {
"rating": {
"gt": 7.0
}
}
}
]
}
},
"boost_mode": "multiply",
"boost": 2.0
}
}
}ResponseA list of candidates, as shown in the example below
{ "candidates": 1, "similarity": [ { "document_id": "29", "score": 10.0, "fields": { "FirstSeenTime": 1506116398, "City": "Jakarta" } } ], "took_ms": 33.625 }
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