feat: analyze memory usage for `size` functions

### Is your feature request related to a problem or challenge?

A follow up on https://github.com/apache/datafusion/pull/23357

Asked Claude to create tests for `size` functions available in datafusion and compare values obtained from functions versus `mimalloc` to track where `size` return inaccurate values. Please see analysis below. So idea is to create small framework to fix and maintain sizes for DF objects

### Summary

Several `Accumulator::size()`, `GroupsAccumulator::size()`, and related implementations report far less memory than they actually hold, which lets the `MemoryPool` limits be silently bypassed. An audit of
~157 `fn size()` sites plus a measurement test against a tracking allocator surface both worst-case defects and a systemic pattern.

### Evidence

Measured with a tracking global allocator around each populated struct, comparing `struct.size()` to real heap-live bytes:

| struct | rows / inputs | `size()` reports | actual heap | undercount |
|---|---|---:|---:|---:|
| `SlidingDistinctCountAccumulator` | 1 024 distinct | **64 B** | 165 960 B | **−100.0%** |
| `SlidingDistinctCountAccumulator` | 16 384 distinct | **64 B** | 2 654 280 B | **−100.0%** |
| `SlidingDistinctCountAccumulator` | 8 192 distinct | **64 B** | 1 425 480 B | **−100.0%** |
| `ArrayAggAccumulator` | 8 192 unique strings | 131 208 B | 164 288 B | −20.1% |
| `ArrowBytesSet` | 32 768 unique utf8 | 2 419 608 B | 2 687 136 B | −10.0% |
| `ArrowBytesViewSet` | 32 768 unique utf8-view | 2 592 992 B | 2 949 352 B | −12.1% |

`ScalarValue::size()` and `TrivialFirst/LastValueAccumulator::size()` were byte-exact — the pattern is fixable, not intrinsic.

End-to-end, on `SELECT k, count(v), sum(v), avg(v) FROM t GROUP BY k` over 200 k rows the aggregate operators reserve **55 MB** against a real live peak of **~7 MB** (720% ratio) — accounted allocations
*also* don't get released as batches emit downstream.

### Root causes found in the audit (25 verified findings, high-severity subset)

- `SlidingDistinctCountAccumulator` / `SlidingDistinctSumAccumulator` — `size()` returns only `size_of_val(self)`, ignoring the `HashMap` bucket capacity and ScalarValue key heap.
`functions-aggregate/src/count.rs:557`, `sum.rs:619`.
- `CountGroupsAccumulator` — uses `size_of::()` for a `Vec`. Wrong element type. `count.rs:771`.
- `SymmetricHashJoinStream` — omits `batch_transformer`, which can hold multi-MB `RecordBatch`. `symmetric_hash_join.rs:1650`.
- `OneSideHashJoiner` — double-counts fields already in `size_of_val(self)`; `HashSet` counted at 8 B/slot instead of 16 B. `symmetric_hash_join.rs:1170`.
- `ArrowBytesViewMap::size()` — sums `buffer.len()` instead of `buffer.capacity()`; misses the `completed: Vec` container. `binary_view_map.rs:476`.
- `GroupValuesPrimitive::size` / `GroupValuesRows::size` — missing `size_of::()`.
- `GroupValuesColumn::size` — ignores `group_index_lists`, `emit_group_index_list_buffer`, and the 5 Vecs in `vectorized_operation_buffers` (can be 100s of KB).
- `GroupOrdering::size` — **over**counts by adding both `size_of::()` and the inner variant's `size()` (which already includes it). `aggregates/order/mod.rs:137`.
- `FirstLastGroupsAccumulator`, `ArrayAggGroupsAccumulator`, `VarianceGroupsAccumulator`, `AvgGroupsAccumulator`, `HllGroupsAccumulator`, `PercentileContGroupsAccumulator`, `MinMaxBytesState`, `ArrayMap`,
`TopK` (missing `common_sort_prefix_converter`), `TrivialNthValueAccumulator`, `StringAggAccumulator`, and `ExprIntervalGraph` — all confirmed under/over-count issues.

Full list with concrete failure scenarios and recommended fixes available on request.

### Describe the solution you'd like

_No response_

### Describe alternatives you've considered

_No response_

### Additional context

_No response_

Start with the follow-up PR 23357 and the tracking-allocator measurement test described in the issue. Audit the listed size implementations, including functions-aggregate/src/count.rs, sum.rs, and symmetric_hash_join.rs, then define the small framework needed to maintain accurate sizes across the reported findings. Done means the framework and its measurements provide a repeatable basis for correcting the identified undercounts and overcounts.

Written by the indexing model from the issue text.