mustafasrepo commented on code in PR #6501:
URL: https://github.com/apache/arrow-datafusion/pull/6501#discussion_r1214945396
##########
datafusion/physical-expr/src/equivalence.rs:
##########
@@ -115,6 +113,53 @@ impl<T: Eq + Hash + Clone> EquivalenceProperties<T> {
}
}
+/// Remove duplicates inside the `in_data` vector, returned vector would
consist of unique entries
+fn deduplicate_vector<T: PartialEq>(in_data: Vec<T>) -> Vec<T> {
+ let mut result = vec![];
+ for elem in in_data {
+ if !result.contains(&elem) {
+ result.push(elem);
+ }
+ }
+ result
+}
+
+/// Find the position of `entry` inside `in_data`, if `entry` is not found
return `None`.
+fn get_entry_position<T: PartialEq>(in_data: &[T], entry: &T) -> Option<usize>
{
+ in_data.iter().position(|item| item.eq(entry))
+}
+
+/// Remove `entry` for the `in_data`, returns `true` if removal is successful
(e.g `entry` is indeed in the `in_data`)
+/// Otherwise return `false`
+fn remove_from_vec<T: PartialEq>(in_data: &mut Vec<T>, entry: &T) -> bool {
Review Comment:
Since, we remove by giving element inside the vector. We already have
removed element. If we return `Option<T>` the value inside `Option` will be
`entry` argument to the function. Hence this function is more akin to `HashSet`
`remove`. Also inside `remove` function we are interested in whether removal
was successful, in this case we need to introduce `is_some` checks inside
`remove` function.
Hence I think, current API is more clear, However, if it is misleading, or
counter intuitive I can implement as your suggestion.
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