Raise explicit error when join columns cannot be found (#1698)

apache · Feb 21, 2025 · f62f67e · f62f67e
1 parent 948486e
commit f62f67e
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Showing 2 changed files with 43 additions and 10 deletions.
diff --git a/pyiceberg/table/__init__.py b/pyiceberg/table/__init__.py
@@ -1159,6 +1159,9 @@ def upsert(
                 else:
                     raise ValueError(f"Field-ID could not be found: {join_cols}")
 
+        if len(join_cols) == 0:
+            raise ValueError("Join columns could not be found, please set identifier-field-ids or pass in explicitly.")
+
         if not when_matched_update_all and not when_not_matched_insert_all:
             raise ValueError("no upsert options selected...exiting")
 

diff --git a/tests/table/test_upsert.py b/tests/table/test_upsert.py
@@ -25,6 +25,7 @@
 from pyiceberg.exceptions import NoSuchTableError
 from pyiceberg.expressions import And, EqualTo, Reference
 from pyiceberg.expressions.literals import LongLiteral
+from pyiceberg.io.pyarrow import schema_to_pyarrow
 from pyiceberg.schema import Schema
 from pyiceberg.table import UpsertResult
 from pyiceberg.table.upsert_util import create_match_filter
@@ -328,7 +329,7 @@ def test_upsert_with_identifier_fields(catalog: Catalog) -> None:
 
     schema = Schema(
         NestedField(1, "city", StringType(), required=True),
-        NestedField(2, "inhabitants", IntegerType(), required=True),
+        NestedField(2, "population", IntegerType(), required=True),
         # Mark City as the identifier field, also known as the primary-key
         identifier_field_ids=[1],
     )
@@ -338,30 +339,30 @@ def test_upsert_with_identifier_fields(catalog: Catalog) -> None:
     arrow_schema = pa.schema(
         [
             pa.field("city", pa.string(), nullable=False),
-            pa.field("inhabitants", pa.int32(), nullable=False),
+            pa.field("population", pa.int32(), nullable=False),
         ]
     )
 
     # Write some data
     df = pa.Table.from_pylist(
         [
-            {"city": "Amsterdam", "inhabitants": 921402},
-            {"city": "San Francisco", "inhabitants": 808988},
-            {"city": "Drachten", "inhabitants": 45019},
-            {"city": "Paris", "inhabitants": 2103000},
+            {"city": "Amsterdam", "population": 921402},
+            {"city": "San Francisco", "population": 808988},
+            {"city": "Drachten", "population": 45019},
+            {"city": "Paris", "population": 2103000},
         ],
         schema=arrow_schema,
     )
     tbl.append(df)
 
     df = pa.Table.from_pylist(
         [
-            # Will be updated, the inhabitants has been updated
-            {"city": "Drachten", "inhabitants": 45505},
+            # Will be updated, the population has been updated
+            {"city": "Drachten", "population": 45505},
             # New row, will be inserted
-            {"city": "Berlin", "inhabitants": 3432000},
+            {"city": "Berlin", "population": 3432000},
             # Ignored, already exists in the table
-            {"city": "Paris", "inhabitants": 2103000},
+            {"city": "Paris", "population": 2103000},
         ],
         schema=arrow_schema,
     )
@@ -388,3 +389,32 @@ def test_create_match_filter_single_condition() -> None:
         EqualTo(term=Reference(name="order_id"), literal=LongLiteral(101)),
         EqualTo(term=Reference(name="order_line_id"), literal=LongLiteral(1)),
     )
+
+
+def test_upsert_without_identifier_fields(catalog: Catalog) -> None:
+    identifier = "default.test_upsert_without_identifier_fields"
+    _drop_table(catalog, identifier)
+
+    schema = Schema(
+        NestedField(1, "city", StringType(), required=True),
+        NestedField(2, "population", IntegerType(), required=True),
+        # No identifier field :o
+        identifier_field_ids=[],
+    )
+
+    tbl = catalog.create_table(identifier, schema=schema)
+    # Write some data
+    df = pa.Table.from_pylist(
+        [
+            {"city": "Amsterdam", "population": 921402},
+            {"city": "San Francisco", "population": 808988},
+            {"city": "Drachten", "population": 45019},
+            {"city": "Paris", "population": 2103000},
+        ],
+        schema=schema_to_pyarrow(schema),
+    )
+
+    with pytest.raises(
+        ValueError, match="Join columns could not be found, please set identifier-field-ids or pass in explicitly."
+    ):
+        tbl.upsert(df)