Dandandan commented on a change in pull request #9116:
URL: https://github.com/apache/arrow/pull/9116#discussion_r557968302
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File path: rust/datafusion/src/physical_plan/hash_join.rs
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@@ -604,6 +562,199 @@ fn build_join_indexes(
}
}
}
+use core::hash::BuildHasher;
+
+/// `Hasher` that returns the same `u64` value as a hash, to avoid re-hashing
+/// it when inserting/indexing or regrowing the `HashMap`
+struct IdHasher {
+ hash: u64,
+}
+
+impl Hasher for IdHasher {
+ fn finish(&self) -> u64 {
+ self.hash
+ }
+
+ fn write_u64(&mut self, i: u64) {
+ self.hash = i;
+ }
+
+ fn write(&mut self, _bytes: &[u8]) {
+ unreachable!("IdHasher should only be used for u64 keys")
+ }
+}
+
+#[derive(Debug)]
+struct IdHashBuilder {}
+
+impl BuildHasher for IdHashBuilder {
+ type Hasher = IdHasher;
+
+ fn build_hasher(&self) -> Self::Hasher {
+ IdHasher { hash: 0 }
+ }
+}
+
+// Combines two hashes into one hash
+fn combine_hashes(l: u64, r: u64) -> u64 {
+ let hash = (17 * 37u64).overflowing_add(l).0;
+ hash.overflowing_mul(37).0.overflowing_add(r).0
+}
+
+macro_rules! equal_rows_elem {
+ ($array_type:ident, $l: ident, $r: ident, $left: ident, $right: ident) => {
+ $l.as_any()
+ .downcast_ref::<$array_type>()
+ .unwrap()
+ .value($left)
+ == $r
+ .as_any()
+ .downcast_ref::<$array_type>()
+ .unwrap()
+ .value($right)
+ };
+}
+
+/// Left and right row have equal values
+fn equal_rows(
+ left: usize,
+ right: usize,
+ left_arrays: &[ArrayRef],
+ right_arrays: &[ArrayRef],
+) -> Result<bool> {
+ let mut err = None;
+ let res = left_arrays
+ .iter()
+ .zip(right_arrays)
+ .all(|(l, r)| match l.data_type() {
+ DataType::Null => true,
+ DataType::Boolean => {
+ equal_rows_elem!(BooleanArray, l, r, left, right)
+ }
+ DataType::Int8 => {
+ equal_rows_elem!(Int8Array, l, r, left, right)
+ }
+ DataType::Int16 => {
+ equal_rows_elem!(Int16Array, l, r, left, right)
+ }
+ DataType::Int32 => {
+ equal_rows_elem!(Int32Array, l, r, left, right)
+ }
+ DataType::Int64 => {
+ equal_rows_elem!(Int64Array, l, r, left, right)
+ }
+ DataType::UInt8 => {
+ equal_rows_elem!(UInt8Array, l, r, left, right)
+ }
+ DataType::UInt16 => {
+ equal_rows_elem!(UInt16Array, l, r, left, right)
+ }
+ DataType::UInt32 => {
+ equal_rows_elem!(UInt32Array, l, r, left, right)
+ }
+ DataType::UInt64 => {
+ equal_rows_elem!(UInt64Array, l, r, left, right)
+ }
+ DataType::Timestamp(_, None) => {
+ equal_rows_elem!(Int64Array, l, r, left, right)
+ }
+ DataType::Utf8 => {
+ equal_rows_elem!(StringArray, l, r, left, right)
+ }
+ DataType::LargeUtf8 => {
+ equal_rows_elem!(LargeStringArray, l, r, left, right)
+ }
+ _ => {
+ // This is internal because we should have caught this before.
+ err = Some(Err(DataFusionError::Internal(
+ "Unsupported data type in hasher".to_string(),
+ )));
+ false
+ }
+ });
+
+ err.unwrap_or(Ok(res))
+}
+
+macro_rules! hash_array {
+ ($array_type:ident, $column: ident, $f: ident, $hashes: ident,
$random_state: ident) => {
+ let array = $column.as_any().downcast_ref::<$array_type>().unwrap();
+
+ for (i, hash) in $hashes.iter_mut().enumerate() {
+ let mut hasher = $random_state.build_hasher();
+ hasher.$f(array.value(i));
+ *hash = combine_hashes(hasher.finish(), *hash);
+ }
+ };
+}
+
+/// Creates hash values for every element in the row based on the values in
the columns
+fn create_hashes(arrays: &[ArrayRef], random_state: &RandomState) ->
Result<Vec<u64>> {
Review comment:
Not 100% sure how that would work for multiple columns? An earlier
version of the PR also tried to reuse a bit of the allocation, but didn't seem
to have a large impact on performance.
I think this can be looked at in a following PR. I am also wondering if
there are some cool SIMD hash algorithms on multiple elements of arrays (rather
than the common `Vec<u8>`) if we want to optimize`create_hashes`. Or maybe we
can write one ourselves. I am not sure how that would work with an iterator?
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