Off-heap memory is used for index construction and query in vector retrieval. Therefore, the required cluster capacity is related to the index type and off-heap memory size. You can estimate the off-heap memory required by full indexing to select proper cluster specifications.
- Graph Index
If you need to update indexes in real time, consider the off-heap memory overhead required for vector index construction and automatic merge. The actual size of required mem_needs is at least 1.5 to 2 times of the original estimation.
- PQ Index
- FALT and IVF Indexes
Parameter |
Description |
|---|---|
dim |
Vector dimensions |
neighbors |
Number of neighbors of a graph node. The default value is 64. |
dim_size |
Number of bytes required by each dimension. The default value is four bytes in the float type. |
num |
Total number of vectors |
delta |
Metadata size. This parameter can be left blank. |
frag_num |
Number of vector segments during quantization and coding. If this parameter is not specified when an index is created, the value is determined by the vector dimension dim. if dim <= 256: frag_num = dim / 4 elif dim <= 512: frag_num = dim / 8 else : frag_num = 64 |
frag_size |
Size of the center point during quantization and coding. The default value is 1. If the value of frag_num is greater than 256, the value of frag_size is 2. |
These calculation methods can estimate the size of off-heap memory required by a complete vector index. To determine cluster specifications, you also need to consider the heap memory overhead of each node.
Heap memory allocation policy: The size of the heap memory of each node is half of the node physical memory, and the maximum size is 31 GB.
For example, if you create a Graph index for the SIFT10M dataset, set dim to 128, dim_size to 4, neighbors to default value 64, and num to 10 million, the off-heap memory required by the Graph index is as follows:
Considering the overhead of heap memory, a single server with 8 vCPUs and 16 GB memory is recommended. If real-time write or update is required, you need to apply for larger memory.