@@ -207,9 +207,8 @@ impl<const STREAMING: bool> GroupValuesColumn<STREAMING> {
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/// Scalarized intern
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///
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- /// This is used only for `streaming aggregation`,
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- /// because it depends on the order between `input rows` and their corresponding
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- /// `group indices`.
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+ /// This is used only for `streaming aggregation`, because `streaming aggregation`
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+ /// depends on the order between `input rows` and their corresponding `group indices`.
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///
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/// For example, assuming `input rows` in `cols` with 4 new rows
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/// (not equal to `exist rows` in `group_values`, and need to create
@@ -222,7 +221,7 @@ impl<const STREAMING: bool> GroupValuesColumn<STREAMING> {
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/// row4
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/// ```
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///
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- /// # In [`GroupValuesColumn`] , their `group indices` will be
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+ /// # In `scalarized_intern` , their `group indices` will be
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///
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/// ```text
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/// row1 --> 0
@@ -234,7 +233,7 @@ impl<const STREAMING: bool> GroupValuesColumn<STREAMING> {
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/// `Group indices` order agrees with their input order, and the `streaming aggregation`
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/// depends on this.
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///
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- /// # However In [`VectorizedGroupValuesColumn`] , their `group indices` will be
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+ /// # However In `vectorized_intern` , their `group indices` will be
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///
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/// ```text
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/// row1 --> 2
@@ -376,12 +375,12 @@ impl<const STREAMING: bool> GroupValuesColumn<STREAMING> {
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//
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// 3. Perform `vectorized_equal_to` for `vectorized_equal_to_row_indices`
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// and `vectorized_equal_to_group_indices`. If found some rows in input `cols`
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- // not equal to `exist rows` in `group_values`, place them in `scalarized_indices `
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- // and perform `scalarized_intern ` for them similar as what in [`GroupValuesColumn`]
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+ // not equal to `exist rows` in `group_values`, place them in `remaining_row_indices `
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+ // and perform `scalarized_intern_remaining ` for them similar as `scalarized_intern`
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// after.
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//
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- // 4. Perform `scalarized_intern ` for rows mentioned above, when we process like this
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- // can see the comments of `scalarized_intern `.
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+ // 4. Perform `scalarized_intern_remaining ` for rows mentioned above, about in what situation
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+ // we will process this can see the comments of `scalarized_intern_remaining `.
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//
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// 1. Collect vectorized context by checking hash values of `cols` in `map`
@@ -394,7 +393,7 @@ impl<const STREAMING: bool> GroupValuesColumn<STREAMING> {
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self . vectorized_equal_to ( cols, groups) ;
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// 4. Perform scalarized inter for remaining rows
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- // (about remaining rows, can see comments for `remaining_rows `)
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+ // (about remaining rows, can see comments for `remaining_row_indices `)
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self . scalarized_intern_remaining ( cols, & batch_hashes, groups) ;
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self . hashes_buffer = batch_hashes;
@@ -1020,7 +1019,7 @@ impl<const STREAMING: bool> GroupValues for GroupValuesColumn<STREAMING> {
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self . hashes_buffer . clear ( ) ;
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self . hashes_buffer . shrink_to ( count) ;
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- // Such structure is only used in `non-streaming` case
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+ // Such structures are only used in `non-streaming` case
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if !STREAMING {
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self . group_index_lists . clear ( ) ;
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self . emit_group_index_list_buffer . clear ( ) ;
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