rewrite array_append/array_prepend to remove deplicate codes

[Veeupup]

Which issue does this PR close?

One issue from #7988array_append && array_prepend.

Rationale for this change

What changes are included in this PR?

Are these changes tested?

Are there any user-facing changes?

[Veeupup]

@alamb@jayzhan211 PTAL ^ . ^

[alamb]

Thanks @Veeupup -- I'll check it out shortly

[Weijun-H]

Thank you @Veeupup ! Could you also move the related tests to sqllogictest?

[jayzhan211]

My expected way for array_append/array_prepend is building array via MutableArrayData, so I need to think about whether row converter is the better choice or not.

[jayzhan211]

I wrote another function with MutableArrayData and it is a lot faster. 30000 micro second vs 300 micro second. @Veeupup Can you also try with MutableArrayData and compare it yourself, if you also got the same result, we can go with MutableArrayData approach.

[Veeupup]

Thank you @Veeupup ! Could you also move the related tests to sqllogictest?

Sure！ I'll make it later

[Veeupup]

I wrote another function with MutableArrayData and it is a lot faster. 30000 micro second vs 300 micro second. @Veeupup Can you also try with MutableArrayData and compare it yourself, if you also got the same result, we can go with MutableArrayData approach.

Appreciate your advice！ I'll try this way and benchmark it then

[Veeupup]

Thank you @Veeupup ! Could you also move the related tests to sqllogictest?

hi @Weijun-H ! it seems that I do not need to do anything? (Or just remove ut fn test_array_prepend and fn test_array_append)

I have checked the sqllogictests with array_append/prepend, and it seems that sqllogictests already have these cases.

[Veeupup]

@jayzhan211 I have implemented the array_append in MutableArray and RowConverter and it shows that Mutable performs better too.

Here are the benchmarks for sqllogictests:

MutableArray	RowConverter
29.297µs	93.433µs
20.555µs	32.201µs
19.251µs	86.561µs
102.495µs	143.772µs
58.49µs	35.456µs
56.035µs	33.316µs
45.607µs	79.701µs
23.508µs	33.592µs
22.87µs	37.584µs
39.27µs	56.071µs
23.973µs	35.368µs
24.97µs	37.753µs
44.644µs	59.515µs
26.602µs	35.498µs
22.272µs	37.957µs
97.846µs	169.643µs
107.068µs	123.551µs
55.058µs	178.546µs
45.853µs	109.962µs
82.722µs	90.556µs
43.62µs	44.157µs

[alamb]

Very nice!

[alamb]

Thank you @Veeupup and @jayzhan211 -- this looks a lot nicer to me. I think there is even more performance to be gained here by avoiding concat (and using ArrayData to build up the final output) but this is a lot better than what we have currently.

Thanks a lot 🙏