jorgecarleitao commented on pull request #8118:
URL: https://github.com/apache/arrow/pull/8118#issuecomment-687891730
> Maybe I am misunderstanding, but I think there may be a flaw with this
approach and we're not comparing apples with apples when looking at the
benchmarks.
>
> The original code is dynamically building a struct using the builder. The
new code starts with a `vec!` where everything is known at compile time. In
theory, the builders should be more efficient than building a `Vec` and then
converting it.
I though that `criterion::black_box()` would block the compiler from
optimizing the code on it, so that the benchmark would not be tainted by
compiler optimizations. I use these in both the Builder and `From`.
Regardless, the reason I used this approach was because I looked through the
code on where we use Builders, and I found two main inputs:
* a vector:
* constructed from reading batches of rows (e.g. `StringRecord` in CSV,
`&[Value]` in json)
* constructed in memory from some external source (e.g. `MemoryScan`)
* an Arrow Array, in most in-memory calculations (e.g. `RecordBatch` and
`ArrayRef`, in `compute` and DataFusion)
In all cases, we use the builders to append rows row-by-row:
* see
[here](https://github.com/apache/arrow/blob/master/rust/arrow/src/csv/reader.rs#L432)
for CSV
* see
[here](https://github.com/apache/arrow/blob/master/rust/arrow/src/json/reader.rs#L491)
for JSON
* in parquet [we do not use Array
builders](https://github.com/apache/arrow/blob/master/rust/parquet/src/arrow/array_reader.rs#L27)
* see
[here](https://github.com/apache/arrow/blob/master/rust/arrow/src/compute/kernels/cast.rs#L207)
for an example in compute
Based on this analysis, I though that:
* this benchmark was a good representation of our use-cases
* we can use `[Try]From` to build our results instead of a builder. The
`from` is essentially `builder.append_data().finish()`, with a significantly
simpler API
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