Fokko commented on code in PR #931:
URL: https://github.com/apache/iceberg-python/pull/931#discussion_r1680739942
##########
tests/integration/test_writes/test_partitioned_writes.py:
##########
@@ -181,6 +181,73 @@ def test_query_filter_appended_null_partitioned(
assert len(rows) == 6
[email protected]
[email protected](
+ "part_col",
+ [
+ "int",
+ "bool",
+ "string",
+ "string_long",
+ "long",
+ "float",
+ "double",
+ "date",
+ "timestamp",
+ "binary",
+ "timestamptz",
+ ],
+)
[email protected](
+ "format_version",
+ [1, 2],
+)
+def test_query_filter_dynamic_overwrite_null_partitioned(
+ session_catalog: Catalog, spark: SparkSession, arrow_table_with_null:
pa.Table, part_col: str, format_version: int
+) -> None:
+ # Given
+ identifier =
f"default.arrow_table_v{format_version}_appended_with_null_partitioned_on_col_{part_col}"
+ nested_field = TABLE_SCHEMA.find_field(part_col)
+ partition_spec = PartitionSpec(
+ PartitionField(source_id=nested_field.field_id, field_id=1001,
transform=IdentityTransform(), name=part_col)
+ )
+
+ # When
+ tbl = _create_table(
+ session_catalog=session_catalog,
+ identifier=identifier,
+ properties={"format-version": str(format_version)},
+ data=[],
+ partition_spec=partition_spec,
+ )
+ # Append with arrow_table_1 with lines [A,B,C] and then arrow_table_2 with
lines[A,B,C,A,B,C]
+ tbl.append(arrow_table_with_null)
+ tbl.append(pa.concat_tables([arrow_table_with_null,
arrow_table_with_null]))
+ # Then
+ assert tbl.format_version == format_version, f"Expected v{format_version},
got: v{tbl.format_version}"
+ df = spark.table(identifier)
+ for col in arrow_table_with_null.column_names:
+ df = spark.table(identifier)
Review Comment:
Makes the tests a faster :)
```suggestion
```
##########
tests/integration/test_writes/test_partitioned_writes.py:
##########
@@ -181,6 +181,73 @@ def test_query_filter_appended_null_partitioned(
assert len(rows) == 6
[email protected]
[email protected](
+ "part_col",
+ [
+ "int",
+ "bool",
+ "string",
+ "string_long",
+ "long",
+ "float",
+ "double",
+ "date",
+ "timestamp",
+ "binary",
+ "timestamptz",
+ ],
+)
[email protected](
+ "format_version",
+ [1, 2],
+)
+def test_query_filter_dynamic_overwrite_null_partitioned(
+ session_catalog: Catalog, spark: SparkSession, arrow_table_with_null:
pa.Table, part_col: str, format_version: int
+) -> None:
+ # Given
+ identifier =
f"default.arrow_table_v{format_version}_appended_with_null_partitioned_on_col_{part_col}"
+ nested_field = TABLE_SCHEMA.find_field(part_col)
+ partition_spec = PartitionSpec(
+ PartitionField(source_id=nested_field.field_id, field_id=1001,
transform=IdentityTransform(), name=part_col)
+ )
+
+ # When
+ tbl = _create_table(
+ session_catalog=session_catalog,
+ identifier=identifier,
+ properties={"format-version": str(format_version)},
+ data=[],
+ partition_spec=partition_spec,
+ )
+ # Append with arrow_table_1 with lines [A,B,C] and then arrow_table_2 with
lines[A,B,C,A,B,C]
+ tbl.append(arrow_table_with_null)
+ tbl.append(pa.concat_tables([arrow_table_with_null,
arrow_table_with_null]))
+ # Then
+ assert tbl.format_version == format_version, f"Expected v{format_version},
got: v{tbl.format_version}"
+ df = spark.table(identifier)
+ for col in arrow_table_with_null.column_names:
+ df = spark.table(identifier)
Review Comment:
Makes the tests a bit faster :)
```suggestion
```
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