Failed to run performance case, reason = Performance case optimize timeout [PG Vector Scale]

I ran multiple tests with PGvector scale using diskann and one of the biggest problem is that the vectordbbench just exits the execution with optmize timeout , this is very true for PGVECTOR SCALE and pgvectorRS.

I know we can increase the time in the scripts , but did anyone observed or recommend any configuration settings that can complete the execution with in the 5hours(default timeout) for 10M cohere 768 Dimension dataset ,we want to look at the cross comparison with out editing the default time outs for a large datastes , did any successfully completed with in that timeout (Milvus Yes , but other DBs ?)

Error message :

024-09-17 22:14:02,230 | WARNING: VectorDB optimize timeout in 18000 (task_runner.py:249) (3816719) 2024-09-17 22:14:02,274 | WARNING: Failed to run performance case, reason = Performance case optimize timeout (task_runner.py:191) (3816719) Traceback (most recent call last): File "/root/vectordbbench_runs/lib/python3.12/site-packages/vectordb_bench/backend/task_runner.py", line 247, in _optimize return future.result(timeout=self.ca.optimize_timeout)[1]

Query:

`CREATE INDEX IF NOT EXISTS "pgvectorscale_index" ON public. "pg_vectorscale_collection"
USING "diskann" (embedding "vector_cosine_ops" )
WITH ( "storage_layout" = "memory_optimized", "num_neighbors" = "50", "search_list_size" = "100", "max_alpha" = "1.2", "num_bits_per_dimension" = "2" ); (pgvectorscale.py:200) (3935818)

`

My Postgres server infra configuration :

1. Installed on baremetal Ubuntu 22
2. postgre 16.4 v(untuned)
3. Memory available :

# free -mh total used free shared buff/cache available Mem: 1.0Ti 13Gi 986Gi 152Mi 7.3Gi 988Gi Swap: 0B 0B 0B
4. Extensions used :

`
pgdiskann=# \dx;
List of installed extensions
Name | Version | Schema | Description
-------------+---------+------------+------------------------------------------------------
plpgsql | 1.0 | pg_catalog | PL/pgSQL procedural language
vector | 0.7.4 | public | vector data type and ivfflat and hnsw access methods
vectorscale | 0.3.0 | public | pgvectorscale: Advanced indexing for vector data
(3 rows)

`

Start with backend/task_runner.py around _optimize and the timeout warnings, then inspect pgvectorscale.py around the CREATE INDEX query. Reproduce the 10M Cohere 768-dimension DiskANN case with the reported PostgreSQL and extension versions, and determine whether the default timeout can complete or what configuration is required.