Create and Drop a Collection

This article provides Python sample codes for creating or droping collections.

See example program for more detailed usage.

Create a collection

  1. Prepare the parameters needed to create the collection:

    # Prepare collection parameters.
    >>> param = {'collection_name':'test01', 'dimension':256, 'index_file_size':1024, 'metric_type':MetricType.L2}
    
  2. Create a collection named test01, with a dimension of 256 and an index file size of 1024 MB. It uses Euclidean distance (L2) as the distance measurement method.

    # Create a collection.
    >>> milvus.create_collection(param)
    

Drop a collection

# Drop a collection.
>>> milvus.drop_collection(collection_name='test01')

FAQ

How can I get the best performance from Milvus through setting index_file_size?

You need to set index_file_size when creating a collection from a client. This parameter specifies the size of each segment, and its default value is 1024 in MB. When the size of newly inserted vectors reaches the specified volume, Milvus packs these vectors into a new segment. In other words, newly inserted vectors do not go into a segment until they grow to the specified volume. When it comes to creating indexes, Milvus creates one index file for each segment. When conducting a vector search, Milvus searches all index files one by one.

As a rule of thumb, we would see a 30% ~ 50% increase in the search performance after changing the value of index_file_size from 1024 to 2048. Note that an overly large index_file_size value may cause failure to load a segment into the memory or graphics memory. Suppose the graphics memory is 2 GB and index_file_size 3 GB, each segment is obviously too large.

In situations where vectors are not frequently inserted, we recommend setting the value of index_file_size to 1024 MB or 2048 MB. Otherwise, we recommend setting the value to 256 MB or 512 MB to keep unindexed files from getting too large.

See Performance Tuning > Index for more information.
Can I update index_file_size and metric_type after creating a collection? No, you cannot.
Is there a limit on the total number of collections and partitions? Yes. The total number of collections and partitions must not exceed 4,096.
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