Update test_sort.py

src/daft-connect/src/translation/logical_plan/sort.rs

@@ -47,31 +47,24 @@ pub fn sort(sort: spark_connect::Sort) -> eyre::Result<Plan> {
         let null_ordering = NullOrdering::try_from(*null_ordering)
             .wrap_err_with(|| format!("Invalid null ordering: {null_ordering:?}"))?;
 
-        // todo(correctness): is this correct?
         let is_descending = match direction {
             SortDirection::Unspecified => {
-                bail!("Unspecified sort direction is not yet supported")
+                // default to ascending order
+                false
             }
             SortDirection::Ascending => false,
             SortDirection::Descending => true,
         };
 
-        // todo(correctness): is this correct?
-        let tentative_sort_nulls_first = match null_ordering {
+        let sort_nulls_first = match null_ordering {
             NullOrdering::SortNullsUnspecified => {
-                bail!("Unspecified null ordering is not yet supported")
+                // default: match is_descending
+                is_descending
             }
             NullOrdering::SortNullsFirst => true,
             NullOrdering::SortNullsLast => false,
         };
 
-        // https://github.com/Eventual-Inc/Daft/blob/7922d2d810ff92b00008d877aa9a6553bc0dedab/src/daft-core/src/utils/mod.rs#L10-L19
-        let sort_nulls_first = is_descending;
-
-        if sort_nulls_first != tentative_sort_nulls_first {
-            warn!("Ignoring nulls_first {sort_nulls_first}; not yet implemented");
-        }
-
         sort_by.push(child);
         descending.push(is_descending);
         nulls_first.push(sort_nulls_first);

tests/connect/test_sort.py

@@ -3,14 +3,27 @@
 from pyspark.sql.functions import col
 
 
-def test_sort(spark_session):
-    # Create DataFrame from range(10)
-    df = spark_session.range(10)
+def test_sort_multiple_columns(spark_session):
+    # Create DataFrame with two columns using range
+    df = spark_session.range(4).select(col("id").alias("num"), col("id").alias("letter"))
 
-    # Sort the DataFrame by 'id' column in descending order
-    df_sorted = df.sort(col("id").desc())
+    # Sort by multiple columns
+    df_sorted = df.sort(col("num").asc(), col("letter").desc())
 
     # Verify the DataFrame is sorted correctly
-    df_pandas = df.toPandas()
-    df_sorted_pandas = df_sorted.toPandas()
-    assert df_sorted_pandas["id"].equals(df_pandas["id"].sort_values(ascending=False).reset_index(drop=True)), "Data should be sorted in descending order"
+    actual = df_sorted.collect()
+    expected = [(0, 0), (1, 1), (2, 2), (3, 3)]
+    assert [(row.num, row.letter) for row in actual] == expected
+
+
+def test_sort_mixed_order(spark_session):
+    # Create DataFrame with two columns using range
+    df = spark_session.range(4).select(col("id").alias("num"), col("id").alias("letter"))
+
+    # Sort with mixed ascending/descending order
+    df_sorted = df.sort(col("num").desc(), col("letter").asc())
+
+    # Verify the DataFrame is sorted correctly
+    actual = df_sorted.collect()
+    expected = [(3, 3), (2, 2), (1, 1), (0, 0)]
+    assert [(row.num, row.letter) for row in actual] == expected