[BUG] Fix join errors with same key name joins (resolves Eventual-Inc…

…#2649) (Eventual-Inc#2877)

The issue fixed here had a workaround previously - aliasing the
duplicate column name. This is not needed anymore as the aliasing is
performed under the hood, taking care of uniqueness of individual column
keys to avoid the duplicate issue.

---------

Co-authored-by: AnmolS <[email protected]>

src/daft-plan/Cargo.toml

@@ -34,6 +34,7 @@ log = {workspace = true}
 pyo3 = {workspace = true, optional = true}
 serde = {workspace = true, features = ["rc"]}
 snafu = {workspace = true}
+uuid = {version = "1", features = ["v4"]}
 
 [dev-dependencies]
 daft-dsl = {path = "../daft-dsl", features = ["test-utils"]}

src/daft-plan/src/logical_ops/join.rs

@@ -3,7 +3,7 @@ use std::{
     sync::Arc,
 };
 
-use common_error::DaftError;
+use common_error::{DaftError, DaftResult};
 use daft_core::prelude::*;
 use daft_dsl::{
     col,
@@ -13,6 +13,7 @@ use daft_dsl::{
 };
 use itertools::Itertools;
 use snafu::ResultExt;
+use uuid::Uuid;
 
 use crate::{
     logical_ops::Project,
@@ -54,14 +55,31 @@ impl Join {
         join_type: JoinType,
         join_strategy: Option<JoinStrategy>,
     ) -> logical_plan::Result<Self> {
-        let (left_on, left_fields) =
-            resolve_exprs(left_on, &left.schema(), false).context(CreationSnafu)?;
-        let (right_on, right_fields) =
+        let (left_on, _) = resolve_exprs(left_on, &left.schema(), false).context(CreationSnafu)?;
+        let (right_on, _) =
             resolve_exprs(right_on, &right.schema(), false).context(CreationSnafu)?;
 
-        for (on_exprs, on_fields) in [(&left_on, left_fields), (&right_on, right_fields)] {
-            let on_schema = Schema::new(on_fields).context(CreationSnafu)?;
-            for (field, expr) in on_schema.fields.values().zip(on_exprs.iter()) {
+        let (unique_left_on, unique_right_on) =
+            Self::rename_join_keys(left_on.clone(), right_on.clone());
+
+        let left_fields: Vec<Field> = unique_left_on
+            .iter()
+            .map(|e| e.to_field(&left.schema()))
+            .collect::<DaftResult<Vec<Field>>>()
+            .context(CreationSnafu)?;
+
+        let right_fields: Vec<Field> = unique_right_on
+            .iter()
+            .map(|e| e.to_field(&right.schema()))
+            .collect::<DaftResult<Vec<Field>>>()
+            .context(CreationSnafu)?;
+
+        for (on_exprs, on_fields) in [
+            (&unique_left_on, &left_fields),
+            (&unique_right_on, &right_fields),
+        ] {
+            for (field, expr) in on_fields.iter().zip(on_exprs.iter()) {
+                // Null type check for both fields and expressions
                 if matches!(field.dtype, DataType::Null) {
                     return Err(DaftError::ValueError(format!(
                         "Can't join on null type expressions: {expr}"
@@ -167,6 +185,60 @@ impl Join {
         }
     }
 
+    /// Renames join keys for the given left and right expressions. This is required to
+    /// prevent errors when the join keys on the left and right expressions have the same key
+    /// name.
+    ///
+    /// This function takes two vectors of expressions (`left_exprs` and `right_exprs`) and
+    /// checks for pairs of column expressions that differ. If both expressions in a pair
+    /// are column expressions and they are not identical, it generates a unique identifier
+    /// and renames both expressions by appending this identifier to their original names.
+    ///
+    /// The function returns two vectors of expressions, where the renamed expressions are
+    /// substituted for the original expressions in the cases where renaming occurred.
+    ///
+    /// # Parameters
+    /// - `left_exprs`: A vector of expressions from the left side of a join.
+    /// - `right_exprs`: A vector of expressions from the right side of a join.
+    ///
+    /// # Returns
+    /// A tuple containing two vectors of expressions, one for the left side and one for the
+    /// right side, where expressions that needed to be renamed have been modified.
+    ///
+    /// # Example
+    /// ```
+    /// let (renamed_left, renamed_right) = rename_join_keys(left_expressions, right_expressions);
+    /// ```
+    ///
+    /// For more details, see [issue #2649](https://github.com/Eventual-Inc/Daft/issues/2649).
+
+    fn rename_join_keys(
+        left_exprs: Vec<Arc<Expr>>,
+        right_exprs: Vec<Arc<Expr>>,
+    ) -> (Vec<Arc<Expr>>, Vec<Arc<Expr>>) {
+        left_exprs
+            .into_iter()
+            .zip(right_exprs)
+            .map(
+                |(left_expr, right_expr)| match (&*left_expr, &*right_expr) {
+                    (Expr::Column(left_name), Expr::Column(right_name))
+                        if left_name == right_name =>
+                    {
+                        (left_expr, right_expr)
+                    }
+                    _ => {
+                        let unique_id = Uuid::new_v4().to_string();
+                        let renamed_left_expr =
+                            left_expr.alias(format!("{}_{}", left_expr.name(), unique_id));
+                        let renamed_right_expr =
+                            right_expr.alias(format!("{}_{}", right_expr.name(), unique_id));
+                        (renamed_left_expr, renamed_right_expr)
+                    }
+                },
+            )
+            .unzip()
+    }
+
     pub fn multiline_display(&self) -> Vec<String> {
         let mut res = vec![];
         res.push(format!("Join: Type = {}", self.join_type));

tests/dataframe/test_joins.py

@@ -53,6 +53,17 @@ def test_columns_after_join(make_df):
     assert set(joined_df2.schema().column_names()) == set(["A", "B"])
 
 
+def test_rename_join_keys_in_dataframe(make_df):
+    df1 = make_df({"A": [1, 2], "B": [2, 2]})
+
+    df2 = make_df({"A": [1, 2]})
+    joined_df1 = df1.join(df2, left_on=["A", "B"], right_on=["A", "A"])
+    joined_df2 = df1.join(df2, left_on=["B", "A"], right_on=["A", "A"])
+
+    assert set(joined_df1.schema().column_names()) == set(["A", "B"])
+    assert set(joined_df2.schema().column_names()) == set(["A", "B"])
+
+
 @pytest.mark.parametrize("n_partitions", [1, 2, 4])
 @pytest.mark.parametrize(
     "join_strategy",