Add benchmarking results for S3 to Bigquery transfer

[utkarsharma2]

Description

What is the current behavior?

Benchmarking results for the S3 to bigquery is missing

related: #429

What is the new behavior?

Added benchmarking results for S3 to Bigquery

Does this introduce a breaking change?

No

Checklist

• Extended the README / documentation, if necessary

[codecov]

Codecov Report

Merging #568 (2826784) into main (9c7d7cc) will decrease coverage by 0.08%.
The diff coverage is n/a.

❗ Current head 2826784 differs from pull request most recent head 9276b9a. Consider uploading reports for the commit 9276b9a to get more accurate results

@@            Coverage Diff             @@
##             main     #568      +/-   ##
==========================================
- Coverage   92.68%   92.59%   -0.09%     
==========================================
  Files          40       40              
  Lines        1613     1594      -19     
  Branches      206      205       -1     
==========================================
- Hits         1495     1476      -19     
  Misses         93       93              
  Partials       25       25              

Impacted Files	Coverage Δ
src/astro/databases/snowflake.py	95.20% <0.00%> (-0.49%)	⬇️

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[sunank200]

I think the results are missing for 5 GB and 10 GB

[utkarsharma2]

Note -

1. We didn't publish the results with all the datasets because not all the datasets were working with native as well as the default path. The ones that were working are published in this PR.
2. The idea with this benchmarking results was to check at what file size we should use the native path VS the default path.
3. For larger files we needed to make changes in the dataset and benchmarking script, due to limitations in pandas and Bigquey DB for that reason we ran these tests in VM and not K8 Cluster.

cc: @kaxil @tatiana @sunank200

[utkarsharma2]

Since we are seeing significant disadvantages of using the native path for smaller file sizes. Added following ticket as one possible way of dealing with the issue - #573

cc: @kaxil @tatiana

[utkarsharma2]

@tatiana - #574