## Problem
halfvec data type was introduced in pgvector 0.7.0 and is popular
because
it allows smaller vectors, smaller indexes and potentially better
performance.
So far we have not tested halfvec in our periodic performance tests.
This PR adds halfvec indexing and halfvec queries to the test.
## Problem
We want to regularly verify the performance of pgvector HNSW parallel
index builds and parallel similarity search using HNSW indexes.
The first release that considerably improved the index-build parallelism
was pgvector 0.7.0 and we want to make sure that we do not regress by
our neon compute VM settings (swap, memory over commit, pg conf etc.)
## Summary of changes
Prepare a Neon project with 1 million openAI vector embeddings (vector
size 1536).
Run HNSW indexing operations in the regression test for the various
distance metrics.
Run similarity queries using pgbench with 100 concurrent clients.
I have also added the relevant metrics to the grafana dashboards pgbench
and olape
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Co-authored-by: Alexander Bayandin <alexander@neon.tech>
