Doc Opeartion

http://router_server is the router service, $db_name is the name of the created database, $space_name is the name of the created space, $ID is the unique ID of the data record.

Single Insertion

Insert without a unique ID

curl -XPOST -H "content-type: application/json"  -d'
{
    "field1": "value1",
    "field2": "value2",
    "field3": {
        "feature": [0.1, 0.2]
    }
}
' http://router_server/$db_name/$space_name

field1 and field2 are scalar field and field3 is feature field. All field names, value types, and table structures are consistent

The return value format is as follows:

{
    "_index": "db1",
    "_type": "space1",
    "_id": "AW5J1lNmJG6WbbCkHrFW",
    "status": 201,
    "_version": 1,
    "_shards": {
        "total": 0,
        "successful": 1,
        "failed": 0
    },
    "result": "created",
    "_seq_no": 1,
    "_primary_term": 1
}

Among them, _index is the name of the database, _type is the name of the tablespace. ID is the unique identification of the record generated by the server, which can be specified by the user. The unique identification needs to be used for data modification and deletion.

Specify a unique ID when inserting

curl -XPOST -H "content-type: application/json"  -d'
{
    "field1": "value1",
    "field2": "value2",
    "field3": {
        "feature": [0.1, 0.2]
    }
}

' http://router_server/$db_name/$space_name/$id

$id is the unique ID generated by the server with the specified value when inserting data. The $id value cannot use special characters such as URL path. Overwrite if the unique record already exists in the library.

Batch insertion

curl -H "content-type: application/json" -XPOST -d'
{"index": {"_id": "v1"}}\n
{"field1": "value", "field2": {"feature": []}}\n
{"index": {"_id": "v2"}}\n
{"field1": "value", "field2": {"feature": []}}\n
' http://router_server/$db_name/$space_name/_bulk

like json format, {“index”: {“_id”: “v1”}} specify the record id, {“field1”: “value”, “field2”: {“feature”: []}} specify inserted data，every line is json string.

Update

Unique ID must be specified when updating

curl -H "content-type: application/json" -XPOST -d'
{
    "doc": {
        "field1": 32
    }
}
' http://router_server/$db_name/$space_name/$id/_update

The unique $id is specified in the request path. The field1 is the field to be modified. The modification of the vector field uses the method of inserting the specified $id to update the data coverage.

Delete

Delete data according to unique ID

curl -XDELETE http://router_server/$db_name/$space_name/$id

Delete data according to query filtering results

curl -H "content-type: application/json" -XPOST -d'
{
    "query": {
        "sum": [{}]
    }
}
' http://router_server/$db_name/$space_name/_delete_by_query

Batch delete according to ID

curl -H "content-type: application/json" -XPOST -d'
{"delete": {"_id": "v1"}}
{"delete": {"_id": "v2"}}
{"delete": {"_id": "v3"}}
' http://router_server/$db_name/$space_name/_bulk

See the following for query syntax

ID query

curl -XGET http://router_server/$db_name/$space_name/$id

Batch query

curl -H "content-type: application/json" -XPOST -d'
{
    "query": {
        "sum": [{
            "field": "vector_field_name",
            "feature": [0.1, 0.2]
        }]
    }
}
' http://router_server/$db_name/$space_name/_msearch

The difference between batch query and single query is that the batch features are spliced into a feature array in order, and the background service will split according to the feature dimension when defining the table space structure. For example, define 10-dimensional feature fields, query 50 features in batches, and splice features into a 500 dimensional array in order to assign them to feature parameters. The request suffix uses “_msearch”.

Multi vector query

The definition of tablespace supports multiple feature fields, so the query can support the features of corresponding data. Take two vectors per record as an example: define table structure fields

{
    "field1": {
        "type": "vector",
        "dimension": 128
    },
    "field2": {
        "type": "vector",
        "dimension": 256
    }
}

Field1 and field2 are vector fields, and two vectors can be specified for search criteria during query:

{
    "query": {
        "sum": [{
            "field": "filed1",
            "feature": [0.1, 0.2, 0.3, 0.4, 0.5],
            "min_score": 0.9
        },
        {
            "field": "filed2",
            "feature": [0.8, 0.9],
            "min_score": 0.8
        }]
    }
}

The results of field1 and field2 are intersected, and other parameters and request addresses are consistent with those of ordinary queries.