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# milvus driver adapter

The milvus driver adapter is a nb adapter for the milvus driver, an open source Java driver for connecting to and
performing operations on an instance of a Milvus/Zilliz Vector database. The driver is hosted on github at
https://github.com/milvus-io/milvus-sdk-java
https://github.com/milvus-io/milvus-sdk-java.

## activity parameters

The following parameters must be supplied to the adapter at runtime in order to successfully connect to an
instance of the Milvus/Zilliz database:

* token - In order to use the pinecone database you must have an account. Once the account is created you can [request
an api key](https://docs.pinecone.io/docs/quickstart#2-get-your-api-key). This key will need to be provided any time a database connection is desired.
an api key/token](https://milvus.io/docs/users_and_roles.md#Users-and-Roles). This key will need to be provided any
time a
database connection is desired.
* uri - When an Index is created in the database the uri must be specified as well. The adapter will
use the default value of localhost:19530 if none is provided at runtime.
use the default value of localhost:19530 if none is provided at runtime.

## Op Templates

The Milvus adapter supports all operations supported by the Java driver published by Milvus.
The Milvus adapter supports [**all operations**](../java/io/nosqlbench/adapter/milvus/ops) supported by the Java
driver
published by Milvus.
The official Milvus API reference can be found at
https://docs.pinecone.io/reference/describe_index_stats_post
https://milvus.io/api-reference/java/v2.3.x/About.md

The operations include:
The operations include a full-fledged support for all the APIs available in the Milvus Java driver.
The following are a couple high level API operations.

* Delete
* DescribeIndexStats
* Fetch
* Query
* Update
* Upsert
* Create Collection
* Create Index
* Drop Collection
* Drop Index
* Search (vectors)

## Examples

```yaml
ops:
example_create_collection:
description: "https://milvus.io/api-reference/java/v2.3.x/Collection/createCollection().md"
collection_name: "example_collection""
shards_num: 10
field_types:
field1:
primary_key: true # only for Int64 and Varchar types
description: field description
data_type: Varchar
# Bool, Int8, Int16, Int32, Int64,
# Float, Double, String, Varchar, BinaryVector, FloatVector
type_param:
example_param1: example_pvalue1
dimension: 1024 # >0
max_length: 1024 # for String only, >0
auto_id: false # Generate primary key?
partition_key: true
consistency_level: BOUNDED # BOUNDED, SESSION, EVENTUAL
partition_num: 1024 # number of partitions
example_create_collection:
create_collection: "example_collection"
description: "https://milvus.io/api-reference/java/v2.3.x/Collection/createCollection().md"
collection_name: "example_collection"
shards_num: 10
consistency_level: BOUNDED # BOUNDED, SESSION, EVENTUAL
field_types:
field1:
primary_key: true # only for Int64 and VarChar types
description: "field description"
data_type: "Varchar"
# Bool, Int8, Int16, Int32, Int64,
# Float, Double, String, Varchar, BinaryVector, FloatVector
type_param:
example_param1: example_pvalue1
dimension: 1024 # >0
max_length: 1024 # for String only, >0
auto_id: false # Generate primary key?
partition_key: false # Primary key cannot be the partition key too
field2:
primary_key: false
description: "vector column/field"
data_type: "FloatVector"
dimension: 3

# https://milvus.io/api-reference/java/v2.3.x/Collection/dropCollection().md
example_drop_index:
drop_index: "exampe_collection_idx_name"
database_name: "my_database"
collection_name: "example_collection""
example_drop_collection:
drop_collection: "example_collection"
database_name: "my_database"

# https://milvus.io/api-reference/java/v2.3.x/High-level%20API/insert().md
example_insert_op:
insert: "example_collection_name"
rows:
field1: "row_key"
field2: "[1.2, 3.4, 5.6]"

# https://milvus.io/api-reference/java/v2.3.x/High-level%20API/search().md
# https://milvus.io/api-reference/java/v2.3.x/Query%20and%20Search/search().md
search_op:
search: "example_collection"
vector: "[-0.4, 0.3, 0.99]"
metric_type: "COSINE"
out_fields:
- field1
- field2
vector_field_name: "field2"
top_k: 100
consistency_level: "EVENTUALLY"
```

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