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Posted to github@datafusion.apache.org by "feniljain (via GitHub)" <gi...@apache.org> on 2025/12/19 17:59:35 UTC
[PR] wip(arrow_intersect, arrow_union): row converter panic [datafusion]
feniljain opened a new pull request, #19415:
URL: https://github.com/apache/datafusion/pull/19415
## Which issue does this PR close?
- Closes #9706
## Rationale for this change
Mentioned in issue.
## What changes are included in this PR?
`RowConverter` API seems to have changed since initial implementation. Columns needs to be exactly same as schema passed in, so when we were handling case of `l_values` or `r_values` being `None`, us passing empty columns was causing an assert to fail in `RowConverter`.
## Are these changes tested?
`cargo test --test sqllogictests -- array` passes
## Are there any user-facing changes?
No
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "feniljain (via GitHub)" <gi...@apache.org>.
feniljain commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3701952486
I was trying to write a detailed writeup on how I think this change would be made, and I think I now understand why you were confused by my initial observation. I must have read something wrong at that time, it is clear to me now.
But this small exercise still leaves one doubt which still holds true, if I make a change in handling of args with `NULL` [here](https://github.com/apache/datafusion/blob/b818f93416d18d06374a0707f5ef571f8a384070/datafusion/functions-nested/src/utils.rs#L60-L71), that would mean making the same change for all of the functions I listed in [this](https://github.com/apache/datafusion/pull/19415#issuecomment-3677957617) message here. Is that okay with you?
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3708582155
Thanks for debugging and fixing this @feniljain
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "feniljain (via GitHub)" <gi...@apache.org>.
feniljain commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3676132353
Hey @Jefffrey 👋🏻
I think PR should be ready for review, as you had left the message in issue, can you also review it please?
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3702129012
I think we only need to look at the `set_ops.rs` file that was modified in this PR; specifically this line:
https://github.com/apache/datafusion/blob/b818f93416d18d06374a0707f5ef571f8a384070/datafusion/functions-nested/src/set_ops.rs#L423
The last argument there, `None`, is usually where the null buffer would be provided, if any. By having it as `None` we essentially can never have nulls in the returned array, which is what we want to change.
See the distinct function in the same file:
https://github.com/apache/datafusion/blob/b818f93416d18d06374a0707f5ef571f8a384070/datafusion/functions-nested/src/set_ops.rs#L549-L559
But in our case, we would need to consider the nulls of both input arrays; I recommend exploring the APIs available to see how this would be possible.
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "feniljain (via GitHub)" <gi...@apache.org>.
feniljain commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3677957617
Hey @Jefffrey 👋🏻
Upon looking into this a bit more, it seems one of the limitations to returning `NULL` here stems from `make_scalar_function` expecting a function returning `Result<ArrayRef>` [source](https://github.com/apache/datafusion/blob/d8e68a404aa7955b4913bab1c658a4ec5c82f0fc/datafusion/functions-nested/src/utils.rs#L53-L58)
We can't change this function as its widely used by a lot of functions, dumping list I received here:
```
datafusion/functions-nested/src/array_has.rs|38 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/array_has.rs|541 col 9-29| make_scalar_function(array_has_all_inner)(&args.args)
datafusion/functions-nested/src/array_has.rs|615 col 9-29| make_scalar_function(array_has_any_inner)(&args.args)
datafusion/functions-nested/src/cardinality.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/cardinality.rs|112 col 9-29| make_scalar_function(cardinality_inner)(&args.args)
datafusion/functions-nested/src/concat.rs|24 col 61-81| use crate::utils::{align_array_dimensions, check_datatypes, make_scalar_function};
datafusion/functions-nested/src/concat.rs|124 col 9-29| make_scalar_function(array_append_inner)(&args.args)
datafusion/functions-nested/src/concat.rs|213 col 9-29| make_scalar_function(array_prepend_inner)(&args.args)
datafusion/functions-nested/src/concat.rs|333 col 9-29| make_scalar_function(array_concat_inner)(&args.args)
datafusion/functions-nested/src/dimension.rs|33 col 40-60| use crate::utils::{compute_array_dims, make_scalar_function};
datafusion/functions-nested/src/dimension.rs|108 col 9-29| make_scalar_function(array_dims_inner)(&args.args)
datafusion/functions-nested/src/dimension.rs|180 col 9-29| make_scalar_function(array_ndims_inner)(&args.args)
datafusion/functions-nested/src/distance.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/distance.rs|132 col 9-29| make_scalar_function(array_distance_inner)(&args.args)
datafusion/functions-nested/src/empty.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/empty.rs|101 col 9-29| make_scalar_function(array_empty_inner)(&args.args)
datafusion/functions-nested/src/except.rs|20 col 37-57| use crate::utils::{check_datatypes, make_scalar_function};
datafusion/functions-nested/src/except.rs|117 col 9-29| make_scalar_function(array_except_inner)(&args.args)
datafusion/functions-nested/src/extract.rs|51 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/extract.rs|179 col 9-29| make_scalar_function(array_element_inner)(&args.args)
datafusion/functions-nested/src/extract.rs|402 col 9-29| make_scalar_function(array_slice_inner)(&args.args)
datafusion/functions-nested/src/extract.rs|849 col 9-29| make_scalar_function(array_pop_front_inner)(&args.args)
datafusion/functions-nested/src/extract.rs|945 col 9-29| make_scalar_function(array_pop_back_inner)(&args.args)
datafusion/functions-nested/src/extract.rs|1050 col 9-29| make_scalar_function(array_any_value_inner)(&args.args)
datafusion/functions-nested/src/flatten.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/flatten.rs|121 col 9-29| make_scalar_function(flatten_inner)(&args.args)
datafusion/functions-nested/src/length.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/length.rs|124 col 9-29| make_scalar_function(array_length_inner)(&args.args)
datafusion/functions-nested/src/make_array.rs|24 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/make_array.rs|120 col 9-29| make_scalar_function(make_array_inner)(&args.args)
datafusion/functions-nested/src/map_entries.rs|20 col 41-61| use crate::utils::{get_map_entry_field, make_scalar_function};
datafusion/functions-nested/src/map_entries.rs|118 col 9-29| make_scalar_function(map_entries_inner)(&args.args)
datafusion/functions-nested/src/map_extract.rs|20 col 41-61| use crate::utils::{get_map_entry_field, make_scalar_function};
datafusion/functions-nested/src/map_extract.rs|117 col 9-29| make_scalar_function(map_extract_inner)(&args.args)
datafusion/functions-nested/src/map_keys.rs|20 col 41-61| use crate::utils::{get_map_entry_field, make_scalar_function};
datafusion/functions-nested/src/map_keys.rs|108 col 9-29| make_scalar_function(map_keys_inner)(&args.args)
datafusion/functions-nested/src/map_values.rs|20 col 41-61| use crate::utils::{get_map_entry_field, make_scalar_function};
datafusion/functions-nested/src/map_values.rs|118 col 9-29| make_scalar_function(map_values_inner)(&args.args)
datafusion/functions-nested/src/min_max.rs|19 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/min_max.rs|104 col 9-29| make_scalar_function(array_max_inner)(&args.args)
datafusion/functions-nested/src/min_max.rs|190 col 9-29| make_scalar_function(array_min_inner)(&args.args)
datafusion/functions-nested/src/position.rs|45 col 45-65| use crate::utils::{compare_element_to_list, make_scalar_function};
datafusion/functions-nested/src/position.rs|132 col 9-29| make_scalar_function(array_position_inner)(&args.args)
datafusion/functions-nested/src/position.rs|283 col 9-29| make_scalar_function(array_positions_inner)(&args.args)
datafusion/functions-nested/src/range.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/range.rs|266 col 17-37| make_scalar_function(|args| self.gen_range_inner(args))(args)
datafusion/functions-nested/src/range.rs|269 col 17-37| make_scalar_function(|args| self.gen_range_date(args))(args)
datafusion/functions-nested/src/range.rs|272 col 17-37| make_scalar_function(|args| self.gen_range_timestamp(args))(args)
datafusion/functions-nested/src/remove.rs|21 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/remove.rs|117 col 9-29| make_scalar_function(array_remove_inner)(&args.args)
datafusion/functions-nested/src/remove.rs|212 col 9-29| make_scalar_function(array_remove_n_inner)(&args.args)
datafusion/functions-nested/src/remove.rs|296 col 9-29| make_scalar_function(array_remove_all_inner)(&args.args)
datafusion/functions-nested/src/repeat.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/repeat.rs|122 col 9-29| make_scalar_function(array_repeat_inner)(&args.args)
datafusion/functions-nested/src/replace.rs|37 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/replace.rs|136 col 9-29| make_scalar_function(array_replace_inner)(&args.args)
datafusion/functions-nested/src/replace.rs|218 col 9-29| make_scalar_function(array_replace_n_inner)(&args.args)
datafusion/functions-nested/src/replace.rs|298 col 9-29| make_scalar_function(array_replace_all_inner)(&args.args)
datafusion/functions-nested/src/resize.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/resize.rs|143 col 9-29| make_scalar_function(array_resize_inner)(&args.args)
datafusion/functions-nested/src/reverse.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/reverse.rs|111 col 9-29| make_scalar_function(array_reverse_inner)(&args.args)
datafusion/functions-nested/src/set_ops.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/set_ops.rs|149 col 9-29| make_scalar_function(array_union_inner)(&args.args)
datafusion/functions-nested/src/set_ops.rs|234 col 9-29| make_scalar_function(array_intersect_inner)(&args.args)
datafusion/functions-nested/src/set_ops.rs|299 col 9-29| make_scalar_function(array_distinct_inner)(&args.args)
datafusion/functions-nested/src/sort.rs|20 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/sort.rs|155 col 9-29| make_scalar_function(array_sort_inner)(&args.args)
datafusion/functions-nested/src/string.rs|33 col 19-39| use crate::utils::make_scalar_function;
datafusion/functions-nested/src/string.rs|216 col 9-29| make_scalar_function(array_to_string_inner)(&args.args)
datafusion/functions-nested/src/string.rs|315 col 32-52| Utf8 | Utf8View => make_scalar_function(string_to_array_inner::<i32>)(args),
datafusion/functions-nested/src/string.rs|316 col 26-46| LargeUtf8 => make_scalar_function(string_to_array_inner::<i64>)(args),
datafusion/functions-nested/src/utils.rs|53 col 15-35| pub(crate) fn make_scalar_function<F>(
```
This raises two points in my head:
- Should we check implementation of each of these functions above and see how is `NULL` handled in each of them?
- If we decide to just fix `array_intersect` and `array_union`, we would have to create a new function similar to `make_scalar_function` which would can return `NULL` too
Either way, this seems like it needs a new PR, I can add `array_union` test and we can continue work on fixing support for all of these (I can file a new issue). What do you think?
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on code in PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#discussion_r2636768778
##########
datafusion/sqllogictest/test_files/array.slt:
##########
@@ -6765,6 +6776,17 @@ from large_array_intersect_table_1D_UTF8;
[bc] [arrow, rust] []
[] [arrow, datafusion, rust] [arrow, rust]
+query ?
+select array_intersect(column1, column2)
Review Comment:
Could we add a test case for `array_union` too?
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "feniljain (via GitHub)" <gi...@apache.org>.
feniljain commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3707237598
I think I finally understood what you mean, looking back I don't understand how I was confused with all this 🤦🏻
I again typed out a big message and at the end it clicked me what is the behavior 🙈
Well, I have replicated the behavior in accordance with [array_intersect](https://github.com/apache/datafusion/pull/19415#pullrequestreview-3600703746) and [array_union](https://github.com/apache/datafusion/pull/19415#issuecomment-3677969443) output of spark now, thanks for being patient with me! 😄
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "feniljain (via GitHub)" <gi...@apache.org>.
feniljain commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3677463849
>I lean towards what Spark would do here; would it be a big change to see if we can implement this semantic?
Can definitely give it a try!
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey merged PR #19415:
URL: https://github.com/apache/datafusion/pull/19415
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "feniljain (via GitHub)" <gi...@apache.org>.
feniljain commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3677969443
For `array_union` I checked behaviour of spark:
```
spark-sql (default)> select array_union(cast(null as array<string>), array());
NULL
Time taken: 0.693 seconds, Fetched 1 row(s)
spark-sql (default)> select array_intersect(cast(null as array<string>), cast(null as array<string>));
NULL
Time taken: 0.058 seconds, Fetched 1 row(s)
spark-sql (default)> select array_intersect(array(), cast(null as array<string>));
NULL
Time taken: 0.075 seconds, Fetched 1 row(s)
spark-sql (default)> select array_intersect(array(), array());
[]
Time taken: 0.071 seconds, Fetched 1 row(s)
```
Seems consistent with above result: `If either array is null, it returns null`
And current behaviour of `array_union` with this PR:
```
query ?
select array_union(column1, column2)
from array_intersect_table_1D_NULL;
----
[1, 2, 3, 4]
[2, 3]
[3, 4]
[3, 4]
[1, 2]
[]
```
i.e. follows array same like `array_intersect`
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3678380285
> Upon looking into this a bit more, it seems one of the limitations to returning `NULL` here stems from `make_scalar_function` expecting a function returning `Result<ArrayRef>` [source](https://github.com/apache/datafusion/blob/d8e68a404aa7955b4913bab1c658a4ec5c82f0fc/datafusion/functions-nested/src/utils.rs#L53-L58)
Could you elaborate on this point? I'm having trouble seeing how it is related to the issue at hand 🤔
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "feniljain (via GitHub)" <gi...@apache.org>.
feniljain commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3699129287
>Could you elaborate on this point? I'm having trouble seeing how it is related to the issue at hand 🤔
I was talking about the case of making the behaviour same as spark, for that we would need to return `NULL` itself rather than current behaviour of empty arrays. Just to be sure, I also checked [documentation](https://docs.rs/arrow/latest/arrow/array/trait.Array.html#implementors) of `Array` it is not implemented by [`Null`](https://docs.rs/arrow/latest/arrow/datatypes/enum.DataType.html#variant.Null)
Am I still missing your question?
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Re: [PR] fix: NULL handling in arrow_intersect and arrow_union [datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on PR #19415:
URL: https://github.com/apache/datafusion/pull/19415#issuecomment-3699673423
> > Could you elaborate on this point? I'm having trouble seeing how it is related to the issue at hand 🤔
>
> I was talking about the case of making the behaviour same as spark, for that we would need to return `NULL` itself rather than current behaviour of empty arrays. Just to be sure, I also checked [documentation](https://docs.rs/arrow/latest/arrow/array/trait.Array.html#implementors) of `Array` it is not implemented by [`Null`](https://docs.rs/arrow/latest/arrow/datatypes/enum.DataType.html#variant.Null)
>
> Am I still missing your question?
I still don't quite follow; what I mean is we return a null value instead of an empty array value. Keep in mind we are dealing with ListArrays, so each element is a list itself (or null). There is nothing about `make_scalar_function` or the `Array` trait that should prevent this.
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