Jefffrey commented on code in PR #6758:
URL: https://github.com/apache/arrow-rs/pull/6758#discussion_r1903204631
##########
arrow-array/src/record_batch.rs:
##########
@@ -394,6 +396,104 @@ impl RecordBatch {
)
}
+ /// Normalize a semi-structured [`RecordBatch`] into a flat table.
+ ///
+ /// `separator`: Nested [`Field`]s will generate names separated by
`separator`, e.g. for
+ /// separator= "." and the schema:
+ /// ```text
+ /// "foo": StructArray<"bar": Utf8>
+ /// ```
+ /// will generate:
+ /// ```text
+ /// "foo.bar": Utf8
+ /// ```
+ /// `max_level`: The maximum number of levels (depth of the `Schema` and
`Columns`) to
+ /// normalize. If `0`, normalizes all levels.
+ ///
+ /// # Example
+ ///
+ /// ```
+ /// # use std::sync::Arc;
+ /// # use arrow_array::{ArrayRef, Int64Array, StringArray, StructArray,
RecordBatch};
+ /// # use arrow_schema::{DataType, Field, Fields, Schema};
+ ///
+ /// let animals: ArrayRef = Arc::new(StringArray::from(vec!["Parrot",
""]));
+ /// let n_legs: ArrayRef = Arc::new(Int64Array::from(vec![Some(2),
Some(4)]));
+ ///
+ /// let animals_field = Arc::new(Field::new("animals", DataType::Utf8,
true));
+ /// let n_legs_field = Arc::new(Field::new("n_legs", DataType::Int64,
true));
+ ///
+ /// let a = Arc::new(StructArray::from(vec![
+ /// (animals_field.clone(), Arc::new(animals.clone()) as ArrayRef),
+ /// (n_legs_field.clone(), Arc::new(n_legs.clone()) as ArrayRef),
+ /// ]));
+ ///
+ /// let schema = Schema::new(vec![
+ /// Field::new(
+ /// "a",
+ /// DataType::Struct(Fields::from(vec![animals_field,
n_legs_field])),
+ /// false,
+ /// )
+ /// ]);
+ ///
+ /// let normalized = RecordBatch::try_new(Arc::new(schema), vec![a])
+ /// .expect("valid conversion")
+ /// .normalize(".", 0)
+ /// .expect("valid normalization");
+ ///
+ /// let expected = RecordBatch::try_from_iter_with_nullable(vec![
+ /// ("a.animals", animals.clone(), true),
+ /// ("a.n_legs", n_legs.clone(), true),
+ /// ])
+ /// .expect("valid conversion");
+ ///
+ /// assert_eq!(expected, normalized);
+ /// ```
+ pub fn normalize(&self, separator: &str, mut max_level: usize) ->
Result<Self, ArrowError> {
+ if max_level == 0 {
+ max_level = usize::MAX;
+ }
+ let mut queue: VecDeque<(usize, &ArrayRef, Vec<&str>, &DataType,
bool)> = VecDeque::new();
Review Comment:
You should be able to `rev()` the iter
`self.columns.iter().zip(self.schema.fields())` and then collect straight into
a Vec I believe
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