Adding semantic search workload that includes vector and bm25 search

[martin-gaievski]

Description

Adding workload for semantic search that is based on customized trec-covid dataset and includes vector, text and integer fields. That allows to run queries like neural search and hybrid query where neural is one of sub queries.

Modified version of trec-covid dataset has ~1M documents, 6 copies of each document from original dataset.

Issues Resolved

#341

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[martin-gaievski]

@VijayanB can I get initial feedback for this PR while we're waiting for feedback on opensearch-project/opensearch-benchmark#591 from other folks?

[martin-gaievski]

I'm going to restore works for this PR and I want to summarize the feedback I got last time:

• merge this workload with https://github.com/opensearch-project/opensearch-benchmark-workloads/tree/main/treccovid_semantic_search, let user to choose which dataset flavor they want to use
• better class structure in workload.py, reuse code where possible instead of copy-pasting
• host all artifacts related to the dataset in cloudfront (example for vectorsearch workload), use those URLs instead of github based

I put together main points from this list in a private branch: https://github.com/martin-gaievski/opensearch-benchmark-workloads/tree/adding_vectordataset_for_semantic_search/treccovid_semantic_search

@VijayanB please let me know if I've missed any important point from your comments