diff --git a/src/daft-connect/src/translation/logical_plan/sort.rs b/src/daft-connect/src/translation/logical_plan/sort.rs
index 15baccbcd8..695c4d5756 100644
--- a/src/daft-connect/src/translation/logical_plan/sort.rs
+++ b/src/daft-connect/src/translation/logical_plan/sort.rs
@@ -50,7 +50,8 @@ pub fn sort(sort: spark_connect::Sort) -> eyre::Result<LogicalPlanBuilder> {
         // 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,
@@ -59,7 +60,8 @@ pub fn sort(sort: spark_connect::Sort) -> eyre::Result<LogicalPlanBuilder> {
         // todo(correctness): is this correct?
         let tentative_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,
diff --git a/tests/connect/test_sort.py b/tests/connect/test_sort.py
index 653510db18..112a1fc658 100644
--- a/tests/connect/test_sort.py
+++ b/tests/connect/test_sort.py
@@ -3,14 +3,33 @@
 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") % 2).alias("num"),
+        (col("id") % 2).cast("string").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"), (0, "0"), (1, "1"), (1, "1")]
+    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") % 2).alias("num"),
+        (col("id") % 2).cast("string").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 = [(1, "1"), (1, "1"), (0, "0"), (0, "0")]
+    assert [(row.num, row.letter) for row in actual] == expected