perf: Cast entire Date32 array to Date64 on 1st failure

[huymq1710]

Which issue does this PR close?

• Closes Optimize to_char for array conversions #17152

Rationale for this change

• 1. Vec<Option<String>> extra allocations

  • Resolved in perf: Optimize to_char to allocate less, fix NULL handling #20635 by using StringBuilder

• 2. Per-row cast on fallback

  • Will be resolved in this PR

// When `Date32` formatting fails (due to time specifiers),
// the code called cast individually for each row instead of converting the entire array
let date64_value = cast(&data_array.slice(idx, 1), &Date64)?;

What changes are included in this PR?

Cast the entire Date32 array to Date64 once on first failure, instead of per-row

cast(data_array.as_ref(), &Date64

Are these changes tested?

Yes

• Add 2 benchmarks:
  • Date32 + datetime patterns (all rows trigger the fallback)
  • Date32 + mixed patterns (roughly half do)

  ┌─────────────────────────────────────┬───────────────────┬───────────┐
  │              Benchmark              │      Format       │  Change   │
  ├─────────────────────────────────────┼───────────────────┼───────────┤
  │ array_date_only_patterns_1000       │ array, date-only  │ No change │
  ├─────────────────────────────────────┼───────────────────┼───────────┤
  │ array_datetime_patterns_1000        │ array, datetime   │ -3.21%    │
  ├─────────────────────────────────────┼───────────────────┼───────────┤
  │ array_mixed_patterns_1000           │ array, mixed      │ +1.41%    │
  ├─────────────────────────────────────┼───────────────────┼───────────┤
  │ scalar_date_only_pattern_1000       │ scalar, date-only │ No change │
  ├─────────────────────────────────────┼───────────────────┼───────────┤
  │ scalar_datetime_pattern_1000        │ scalar, datetime  │ No change │
  ├─────────────────────────────────────┼───────────────────┼───────────┤
  │ array_date32_datetime_patterns_1000 │ array, datetime   │ -20.24%   │
  ├─────────────────────────────────────┼───────────────────┼───────────┤
  │ array_date32_mixed_patterns_1000    │ array, mixed      │ -15.74%   │
  └─────────────────────────────────────┴───────────────────┴───────────┘

Detail

cargo bench --bench to_char          
   Compiling datafusion-functions v53.1.0 (/Users/qmac/Documents/GitHub/datafusion/datafusion/functions)
    Finished `bench` profile [optimized] target(s) in 1m 10s
     Running benches/to_char.rs (target/release/deps/to_char-d2acea4b7a3e2fba)
Gnuplot not found, using plotters backend
Benchmarking to_char_array_date_only_patterns_1000: Warming up for 3.00Benchmarking to_char_array_date_only_patterns_1000: Collecting 100 sampto_char_array_date_only_patterns_1000
                        time:   [104.01 µs 104.37 µs 104.74 µs]
                        change: [−0.5692% +0.3244% +1.0788%] (p = 0.47 > 0.05)
                        No change in performance detected.
Found 3 outliers among 100 measurements (3.00%)
  1 (1.00%) low mild
  2 (2.00%) high mild

Benchmarking to_char_array_datetime_patterns_1000: Warming up for 3.000Benchmarking to_char_array_datetime_patterns_1000: Collecting 100 samplto_char_array_datetime_patterns_1000
                        time:   [165.96 µs 166.43 µs 166.94 µs]
                        change: [−4.1660% −3.2055% −2.3626%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  2 (2.00%) low mild
  3 (3.00%) high mild
  1 (1.00%) high severe

Benchmarking to_char_array_mixed_patterns_1000: Collecting 100 samples to_char_array_mixed_patterns_1000
                        time:   [139.58 µs 140.02 µs 140.49 µs]
                        change: [+1.0116% +1.4122% +1.8178%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 3 outliers among 100 measurements (3.00%)
  1 (1.00%) low mild
  2 (2.00%) high mild

Benchmarking to_char_scalar_date_only_pattern_1000: Warming up for 3.00Benchmarking to_char_scalar_date_only_pattern_1000: Collecting 100 sampto_char_scalar_date_only_pattern_1000
                        time:   [60.073 µs 63.184 µs 66.309 µs]
                        change: [−4.0228% +0.6839% +6.1581%] (p = 0.79 > 0.05)
                        No change in performance detected.

Benchmarking to_char_scalar_datetime_pattern_1000: Warming up for 3.000Benchmarking to_char_scalar_datetime_pattern_1000: Collecting 100 samplto_char_scalar_datetime_pattern_1000
                        time:   [117.65 µs 124.76 µs 131.84 µs]
                        change: [−3.3009% +2.6889% +8.6148%] (p = 0.37 > 0.05)
                        No change in performance detected.
Found 30 outliers among 100 measurements (30.00%)
  16 (16.00%) low mild
  14 (14.00%) high mild

Benchmarking to_char_array_date32_datetime_patterns_1000: Warming up foBenchmarking to_char_array_date32_datetime_patterns_1000: Collecting 10to_char_array_date32_datetime_patterns_1000
                        time:   [289.67 µs 290.77 µs 291.88 µs]
                        change: [−20.661% −20.240% −19.863%] (p = 0.00 < 0.05)
                        Performance has improved.

Benchmarking to_char_array_date32_mixed_patterns_1000: Warming up for 3Benchmarking to_char_array_date32_mixed_patterns_1000: Collecting 100 sto_char_array_date32_mixed_patterns_1000
                        time:   [194.47 µs 195.28 µs 196.11 µs]
                        change: [−16.230% −15.738% −15.285%] (p = 0.00 < 0.05)
                        Performance has improved.

Are there any user-facing changes?

No

[huymq1710]

Thank you. I updated