[MAINTENANCE] Reduce test duration of flakey test

[tyler-hoffman]

This test fails with some regularity in CI, but not in the way the test expects. See this example. It fails with Failed: Timeout >2.0s because we currently invoke pytest with --timeout=2, so we would would never fail the assertion as written.

We could also throw a mark.pytest.slow on this instead of cutting the time in half, but I'm not sure if that matters.

The fix here:

• Reduce the expected time and large_number by half so we can see the expected error if appropriate. I'm assuming complexity is O(n) with large_number.
• Then reduce large_number by another 25% to avoid the flakiness.

• Description of PR changes above includes a link to an existing GitHub issue
• PR title is prefixed with one of: [BUGFIX], [FEATURE], [DOCS], [MAINTENANCE], [CONTRIB]
• Code is linted - run invoke lint (uses ruff format + ruff check)
• Appropriate tests and docs have been updated

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 80.45%. Comparing base (a3058e5) to head (bb7cb65).
Report is 4 commits behind head on develop.

✅ All tests successful. No failed tests found.

Additional details and impacted files

@@             Coverage Diff             @@
##           develop   #10663      +/-   ##
===========================================
- Coverage    80.45%   80.45%   -0.01%     
===========================================
  Files          462      462              
  Lines        40102    40102              
===========================================
- Hits         32264    32263       -1     
- Misses        7838     7839       +1     

Flag	Coverage Δ
3.10	68.15% <ø> (ø)
3.10 athena or openpyxl or pyarrow or project or sqlite or aws_creds	?
3.10 aws_deps	?
3.10 big	?
3.10 clickhouse	?
3.10 filesystem	?
3.10 mssql	?
3.10 mysql	?
3.10 postgresql	?
3.10 spark_connect	?
3.10 trino	?
3.11	68.13% <ø> (-0.02%)	⬇️
3.11 athena or openpyxl or pyarrow or project or sqlite or aws_creds	?
3.11 aws_deps	?
3.11 big	?
3.11 clickhouse	?
3.11 filesystem	?
3.11 mssql	?
3.11 mysql	?
3.11 postgresql	?
3.11 spark	?
3.11 spark_connect	?
3.11 trino	?
3.12	68.15% <ø> (-0.01%)	⬇️
3.12 athena or openpyxl or pyarrow or project or sqlite or aws_creds	55.49% <ø> (ø)
3.12 aws_deps	46.14% <ø> (ø)
3.12 big	54.74% <ø> (ø)
3.12 databricks	47.88% <ø> (ø)
3.12 filesystem	61.71% <ø> (ø)
3.12 mssql	51.49% <ø> (ø)
3.12 mysql	51.56% <ø> (ø)
3.12 postgresql	54.64% <ø> (ø)
3.12 snowflake	48.85% <ø> (ø)
3.12 spark	58.06% <ø> (ø)
3.12 spark_connect	46.44% <ø> (ø)
3.12 trino	52.68% <ø> (ø)
3.9	68.18% <ø> (ø)
3.9 athena or openpyxl or pyarrow or project or sqlite or aws_creds	55.49% <ø> (ø)
3.9 aws_deps	46.16% <ø> (ø)
3.9 big	54.76% <ø> (ø)
3.9 clickhouse	43.03% <ø> (ø)
3.9 databricks	47.89% <ø> (ø)
3.9 filesystem	61.73% <ø> (ø)
3.9 mssql	51.47% <ø> (ø)
3.9 mysql	51.54% <ø> (ø)
3.9 postgresql	54.62% <ø> (ø)
3.9 snowflake	48.87% <ø> (ø)
3.9 spark	58.02% <ø> (ø)
3.9 spark_connect	46.45% <ø> (ø)
3.9 trino	52.66% <ø> (ø)
cloud	0.00% <ø> (ø)
docs-basic	53.35% <ø> (ø)
docs-creds-needed	52.92% <ø> (ø)
docs-spark	52.40% <ø> (ø)

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[dctalbot]

If this test continues to be a problem, we can just remove it. It's shoehorning a benchmark into a test, and really we could use a more holistic performance assessment setup in CI.