Capture engine setup/teardown durations

[TomAugspurger]

Description

This measures the time it takes to start / stop our engines when running benchmarks, and includes them in cudf-polars' benchmark output. It'll aid with things like measuring the impact of pinned host memory pools with initialization.

Checklist

• I am familiar with the Contributing Guidelines.
• New or existing tests cover these changes.
• The documentation is up to date with these changes.

[coderabbitai]

📝 Walkthrough

Summary by CodeRabbit

• New Features
  • Benchmark results now include engine startup and shutdown durations in milliseconds.
  • Lifecycle timings are reported for in-memory, SPMD, Ray, and Dask execution modes.
  • CPU execution reports no engine lifecycle timings.

Walkthrough

Benchmark runs now measure engine startup and shutdown durations in milliseconds. The timings are serialized with engine configuration for in-memory, SPMD, Ray, and Dask frontends. CPU execution records no lifecycle timings.

Changes

Benchmark lifecycle timing

Layer / File(s)	Summary
Timing fields and basic frontends python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py	The finalization function accepts optional lifecycle durations and writes them into the serialized engine configuration. CPU reports no timings. In-memory GPU execution records startup time.
SPMD and Ray lifecycle timing python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py	SPMD and Ray frontends measure startup during context entry and shutdown during context exit.
Dask lifecycle timing python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py	Dask measures startup after engine creation and shutdown after cleanup, then serializes both durations.

Estimated code review effort: 2 (Simple) | ~10 minutes

Merge Risk: 🔵 Low · up to d334d

The PR adds engine lifecycle timing to benchmark output, but shutdown measurements currently also include trace processing and file I/O in three execution paths. The change is mergeable with explicit owner awareness or follow-up because the reported teardown metric may be overstated.

Suggested reviewers: pentschev, mroeschke, madsbk

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description check	✅ Passed	The description clearly explains that benchmark output will include engine startup and shutdown durations.
Title check	✅ Passed	The title clearly and concisely summarizes the main change: capturing engine setup and teardown durations.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 8 functions across 1 files.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

✨ Finishing Touches 💡 1

🛠️ Fix failing CI checks 💡

• Create stacked PR
• Commit on current branch

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[coderabbitai]

Actionable comments posted: 1

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Inline comments:
In `@python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py`:
- Around line 1463-1471: Move the _elapsed_ms call so shutdown_duration_ms is
captured immediately after each engine context exits and before trace writing.
Apply this consistently in
python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py at lines 1463-1471
(SPMD), 1529-1536 (Ray), and 1601-1611 (Dask); keep _write_quent_traces after
timing in each frontend.

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Fix all unresolved CodeRabbit comments on this PR:

• Push a commit to this branch (recommended)
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ℹ️ Review info

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📥 Commits

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• python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py

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