Expose `ExecutionPlan::metrics()` across the FFI boundary

[mailmindlin]

Is your feature request related to a problem or challenge?

ExecutionPlan::metrics() is not currently reachable through datafusion-ffi: FFI_ExecutionPlan exposes most of the trait (properties, children, with_new_children, name, execute, repartitioned) but has no function pointer for metrics(), so ForeignExecutionPlan::metrics() falls through to the trait default implementation and always returns None.

The user-visible consequences:

• EXPLAIN ANALYZE produces empty metric blocks for FFI plans.
  AnalyzeExec exhausts the input stream and then formats metrics via
  DisplayableExecutionPlan::with_metrics(...). For any plan node loaded
  through datafusion-ffi, the rendered output shows no output_rows,
  elapsed_compute, etc. — even though those metrics are being recorded
  on the producer side.
• Anything calling DisplayableExecutionPlan::with_metrics(...) on a
  plan tree containing a foreign node is similarly affected — tooling,
  dashboards, tests, etc.

This makes foreign-loaded operators behave noticeably differently from
locally-defined operators in a way that's surprising and not documented.
The expectation, especially given the FFI crate's stated goal of allowing
extensions to "interface to DataFusion" transparently, is that a foreign
plan should be observationally indistinguishable from a local plan with
respect to instrumentation.

Describe the solution you'd like

Pass metrics across the FFI boundary as a snapshot: read all
atomic-backed counters/gauges/timers into plain integer fields at marshal
time. Specifically:

1. Add a new function pointer to FFI_ExecutionPlan for metrics
2. Define FFI-stable mirrors of MetricsSet, Metric, MetricValue, etc. plus bidirectional From
   conversions.
3. For MetricValue::Custom { value: Arc<dyn CustomMetricValue> },
   marshal (name, Display output, as_usize()) and reconstruct on the
   consumer side via a small FfiCustomMetricValue shim. This preserves
   Display (the common case for EXPLAIN ANALYZE) and as_usize()
   (used for sorting), at the cost of losing aggregate and
   as_any downcasting.

Snapshot semantics are sufficient because every in-tree caller of
.metrics() reads after the input stream has been exhausted — see
AnalyzeExec exhausting its input before formatting, and
DisplayableExecutionPlan rendering during post-execution display.

Describe alternatives you've considered

• Share live atomics across the FFI boundary. Expose the underlying
  Arc<AtomicUsize> such that the consumer can poll updated values without
  re-calling metrics(). Rejected: no in-tree caller polls metrics during
  streaming, and sharing Arcs across the FFI boundaries is complex for little benefit.

• A separate FFI_ExecutionPlanMetrics struct queried independently
  from FFI_ExecutionPlan. Preserves the existing ABI but forces
  consumers to coordinate two structs and complicates lifetime/identity
  reasoning. The function-pointer-on-the-struct pattern matches every
  other method exposed on FFI_ExecutionPlan and reads more naturally.

• A full FFI trait object for CustomMetricValue. Define an
  FFI_CustomMetricValue with function pointers for display, as_usize,
  aggregate, clone, and release. Rejected for the initial pass:
  significant surface area, while Display + as_usize() covers the only
  in-tree consumer of Custom metrics (display via EXPLAIN ANALYZE).
  Can be added later if extension authors need round-trippable custom
  metrics.

Additional context

I have a PR written for this issue that I will file shortly.