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Posted to github@arrow.apache.org by "izveigor (via GitHub)" <gi...@apache.org> on 2023/07/16 14:23:06 UTC
[GitHub] [arrow-datafusion] izveigor opened a new pull request, #6986: feat: array functions treat an array as an element
izveigor opened a new pull request, #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986
# Which issue does this PR close?
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Closes https://github.com/apache/arrow-datafusion/issues/6985
Follow on to https://github.com/apache/arrow-datafusion/pull/6879
Follow on to https://github.com/apache/arrow-datafusion/pull/6805
# Rationale for this change
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# What changes are included in this PR?
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# Are these changes tested?
Yes
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# Are there any user-facing changes?
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[GitHub] [arrow-datafusion] jayzhan211 commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "jayzhan211 (via GitHub)" <gi...@apache.org>.
jayzhan211 commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1266031831
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
Review Comment:
Does 1D + 2D pass? Do only descending-order dimensions work?
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[GitHub] [arrow-datafusion] izveigor commented on pull request #6986: feat: array functions treat an array as an element
Posted by "izveigor (via GitHub)" <gi...@apache.org>.
izveigor commented on PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#issuecomment-1637849146
Ready for the review, @alamb and @jayzhan211!
When I was writing the code, I found new bugs related to the topic of arrays: https://github.com/apache/arrow-datafusion/issues/6993 and https://github.com/apache/arrow-datafusion/issues/6992.
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[GitHub] [arrow-datafusion] izveigor commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "izveigor (via GitHub)" <gi...@apache.org>.
izveigor commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1265157934
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
+----
+[[30, 40, 50], [12]]
+[[, , 60], [13]]
+[[70, , ], [14]]
+[[]]
+[[]]
+[[]]
+
+# array_concat column-wise #10 (3D + 2D + 1D)
Review Comment:
When I was writing these examples, I suddenly found a bug: https://github.com/apache/arrow-datafusion/issues/6992
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[GitHub] [arrow-datafusion] alamb merged pull request #6986: feat: array functions treat an array as an element
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb merged PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986
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[GitHub] [arrow-datafusion] izveigor commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "izveigor (via GitHub)" <gi...@apache.org>.
izveigor commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1265144992
##########
datafusion/physical-expr/src/array_expressions.rs:
##########
@@ -543,7 +545,18 @@ fn align_array_dimensions(args: Vec<ArrayRef>) -> Result<Vec<ArrayRef>> {
let mut aligned_array = array.clone();
for _ in 0..(max_ndim - ndim) {
let data_type = aligned_array.as_ref().data_type().clone();
- aligned_array = array_array(&[aligned_array], data_type)?;
+ let offsets: Vec<i32> =
+ (0..downcast_arg!(aligned_array, ListArray).offsets().len())
+ .map(|i| i as i32)
+ .collect();
+ let field = Arc::new(Field::new("item", data_type, true));
+
+ aligned_array = Arc::new(ListArray::try_new(
Review Comment:
Is there a method how to push `NULL`s into `ListArray::try_new` with saving values? 🤔
@tustvold, can you give me some advice if you have free time.
##########
datafusion/physical-expr/src/array_expressions.rs:
##########
@@ -543,7 +545,18 @@ fn align_array_dimensions(args: Vec<ArrayRef>) -> Result<Vec<ArrayRef>> {
let mut aligned_array = array.clone();
for _ in 0..(max_ndim - ndim) {
let data_type = aligned_array.as_ref().data_type().clone();
- aligned_array = array_array(&[aligned_array], data_type)?;
+ let offsets: Vec<i32> =
+ (0..downcast_arg!(aligned_array, ListArray).offsets().len())
+ .map(|i| i as i32)
+ .collect();
+ let field = Arc::new(Field::new("item", data_type, true));
+
+ aligned_array = Arc::new(ListArray::try_new(
Review Comment:
Is there a method how to push `NULL`s into `ListArray::try_new` with saving values? 🤔
@tustvold, can you give me some advice if you have free time.
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[GitHub] [arrow-datafusion] alamb commented on pull request #6986: feat: array functions treat an array as an element
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#issuecomment-1638923033
Thank you for this PR @izveigor -- I ran out of time today but I have this PR on my list to review tomorrow
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[GitHub] [arrow-datafusion] izveigor commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "izveigor (via GitHub)" <gi...@apache.org>.
izveigor commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1265142387
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
Review Comment:
I was able to solve this problem.
cc @jayzhan211
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[GitHub] [arrow-datafusion] izveigor commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "izveigor (via GitHub)" <gi...@apache.org>.
izveigor commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1265165845
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
Review Comment:
When I was trying to use `make_array` with lists, I accidentally found a new bug: https://github.com/apache/arrow-datafusion/issues/6993
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[GitHub] [arrow-datafusion] jayzhan211 commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "jayzhan211 (via GitHub)" <gi...@apache.org>.
jayzhan211 commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1266046670
##########
datafusion/physical-expr/src/array_expressions.rs:
##########
@@ -543,7 +545,18 @@ fn align_array_dimensions(args: Vec<ArrayRef>) -> Result<Vec<ArrayRef>> {
let mut aligned_array = array.clone();
for _ in 0..(max_ndim - ndim) {
let data_type = aligned_array.as_ref().data_type().clone();
- aligned_array = array_array(&[aligned_array], data_type)?;
+ let offsets: Vec<i32> =
+ (0..downcast_arg!(aligned_array, ListArray).offsets().len())
+ .map(|i| i as i32)
+ .collect();
+ let field = Arc::new(Field::new("item", data_type, true));
+
+ aligned_array = Arc::new(ListArray::try_new(
Review Comment:
There are `downcast_arg()` in this file, `as_list_array` in `datafusion/common/src/cast.rs` and `as_list, as_list_opt` in arrow-array. Which one to use among these methods?
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[GitHub] [arrow-datafusion] jayzhan211 commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "jayzhan211 (via GitHub)" <gi...@apache.org>.
jayzhan211 commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1266043363
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
+----
+[[30, 40, 50], [12]]
+[[, , 60], [13]]
+[[70, , ], [14]]
+[[]]
+[[]]
+[[]]
+
+# array_concat column-wise #10 (3D + 2D + 1D)
+query ?
+select array_concat(column4, column1, column2) from nested_arrays;
+----
+[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]], [[1, 2, 3], [2, 9, 1], [7, 8, 9], [1, 2, 3], [1, 7, 4], [4, 5, 6]], [[7, 8, 9]]]
+[[[11, 12, 13], [14, 15, 16]], [[17, 18, 19], [20, 21, 22]], [[4, 5, 6], [10, 11, 12], [4, 9, 8], [7, 8, 9], [10, 11, 12], [1, 8, 7]], [[10, 11, 12]]]
-# array_concat column-wise #11 (1D + Integers)
Review Comment:
I think we don't need to support this.
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[GitHub] [arrow-datafusion] jayzhan211 commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "jayzhan211 (via GitHub)" <gi...@apache.org>.
jayzhan211 commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1266046670
##########
datafusion/physical-expr/src/array_expressions.rs:
##########
@@ -543,7 +545,18 @@ fn align_array_dimensions(args: Vec<ArrayRef>) -> Result<Vec<ArrayRef>> {
let mut aligned_array = array.clone();
for _ in 0..(max_ndim - ndim) {
let data_type = aligned_array.as_ref().data_type().clone();
- aligned_array = array_array(&[aligned_array], data_type)?;
+ let offsets: Vec<i32> =
+ (0..downcast_arg!(aligned_array, ListArray).offsets().len())
+ .map(|i| i as i32)
+ .collect();
+ let field = Arc::new(Field::new("item", data_type, true));
+
+ aligned_array = Arc::new(ListArray::try_new(
Review Comment:
There are `downcast_arg()` in this file, `as_list_array` in `datafusion/common/src/cast.rs` and `as_list, as_list_opt` in arrow-array. Which one to use among these methods?
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[GitHub] [arrow-datafusion] alamb commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1267305845
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -55,6 +55,13 @@ AS VALUES
(make_array(make_array(15, 16),make_array(NULL, 18)), make_array(16.6, 17.7, 18.8), NULL)
;
+statement ok
+CREATE TABLE nested_arrays
+AS VALUES
+ (make_array(make_array(1, 2, 3), make_array(2, 9, 1), make_array(7, 8, 9), make_array(1, 2, 3), make_array(1, 7, 4), make_array(4, 5, 6)), make_array(7, 8, 9), 2, make_array([[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]])),
Review Comment:
I recommend adding NULL values -- both as elements as well as the arrays as that is often a corner case that gets overlooked
Perhaps something like
```suggestion
(make_array(make_array(1, 2, 3), NULL, make_array(7, 8, 9), make_array(1, 2, 3), make_array(1, 7, 4), make_array(4, 5, 6)), make_array(7, 8, 9), 2, make_array([[NULL, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]])),
```
##########
datafusion/physical-expr/src/array_expressions.rs:
##########
@@ -543,7 +545,18 @@ fn align_array_dimensions(args: Vec<ArrayRef>) -> Result<Vec<ArrayRef>> {
let mut aligned_array = array.clone();
for _ in 0..(max_ndim - ndim) {
let data_type = aligned_array.as_ref().data_type().clone();
- aligned_array = array_array(&[aligned_array], data_type)?;
+ let offsets: Vec<i32> =
+ (0..downcast_arg!(aligned_array, ListArray).offsets().len())
+ .map(|i| i as i32)
+ .collect();
+ let field = Arc::new(Field::new("item", data_type, true));
+
+ aligned_array = Arc::new(ListArray::try_new(
Review Comment:
The last argument to `try_new` is the `Option<NullBuffer>` right which defines which elements are nulls.
Perhaps I don't understand your question
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[GitHub] [arrow-datafusion] izveigor commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "izveigor (via GitHub)" <gi...@apache.org>.
izveigor commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1265156556
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
+----
+[[30, 40, 50], [12]]
+[[, , 60], [13]]
+[[70, , ], [14]]
+[[]]
+[[]]
+[[]]
+
+# array_concat column-wise #10 (3D + 2D + 1D)
+query ?
+select array_concat(column4, column1, column2) from nested_arrays;
+----
+[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]], [[1, 2, 3], [2, 9, 1], [7, 8, 9], [1, 2, 3], [1, 7, 4], [4, 5, 6]], [[7, 8, 9]]]
+[[[11, 12, 13], [14, 15, 16]], [[17, 18, 19], [20, 21, 22]], [[4, 5, 6], [10, 11, 12], [4, 9, 8], [7, 8, 9], [10, 11, 12], [1, 8, 7]], [[10, 11, 12]]]
-# array_concat column-wise #11 (1D + Integers)
Review Comment:
It seems like the regression, but PostgreSQL does not support concatenation between scalars (integers) and arrays.
Should we keep this feature or is it better to follow the PostgreSQL standard? 🤔
What do you think about it, @jayzhan211?
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
+----
+[[30, 40, 50], [12]]
+[[, , 60], [13]]
+[[70, , ], [14]]
+[[]]
+[[]]
+[[]]
+
+# array_concat column-wise #10 (3D + 2D + 1D)
+query ?
+select array_concat(column4, column1, column2) from nested_arrays;
+----
+[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]], [[1, 2, 3], [2, 9, 1], [7, 8, 9], [1, 2, 3], [1, 7, 4], [4, 5, 6]], [[7, 8, 9]]]
+[[[11, 12, 13], [14, 15, 16]], [[17, 18, 19], [20, 21, 22]], [[4, 5, 6], [10, 11, 12], [4, 9, 8], [7, 8, 9], [10, 11, 12], [1, 8, 7]], [[10, 11, 12]]]
-# array_concat column-wise #11 (1D + Integers)
Review Comment:
It seems like the regression, but PostgreSQL does not support concatenation between scalars (integers) and arrays.
Should we keep this feature or is it better to follow the PostgreSQL standard? 🤔
What do you think about it, @jayzhan211?
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[GitHub] [arrow-datafusion] jayzhan211 commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "jayzhan211 (via GitHub)" <gi...@apache.org>.
jayzhan211 commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1266031831
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
Review Comment:
Does 1D + 2D pass? or only descending order dimensions works?
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[GitHub] [arrow-datafusion] jayzhan211 commented on a diff in pull request #6986: feat: array functions treat an array as an element
Posted by "jayzhan211 (via GitHub)" <gi...@apache.org>.
jayzhan211 commented on code in PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#discussion_r1266031831
##########
datafusion/core/tests/sqllogictests/test_files/array.slt:
##########
@@ -554,28 +595,36 @@ select array_concat(column1, column2) from arrays_values_v2;
[11, 12]
NULL
-# TODO: Concat columns with different dimensions fails
-# array_concat column-wise #10 (1D + 2D)
-# query error DataFusion error: Arrow error: Invalid argument error: column types must match schema types, expected List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) but found List\(Field \{ name: "item", data_type: List\(Field \{ name: "item", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: \{\} \}\) at column index 0
-# select array_concat(make_array(column3), column4) from arrays_values_v2;
+# array_concat column-wise #9 (2D + 1D)
+query ?
+select array_concat(column4, make_array(column3)) from arrays_values_v2;
Review Comment:
Does 1D + 2D pass?
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[GitHub] [arrow-datafusion] alamb commented on pull request #6986: feat: array functions treat an array as an element
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on PR #6986:
URL: https://github.com/apache/arrow-datafusion/pull/6986#issuecomment-1641000477
Thanks @izveigor and @jayzhan211
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